[upstream-sync] docs/data/resources.json from inoue0426/awesome-computational-biology@c6f07d90 [catalogue]

Reviewed-on: #83

upstream/ai-boost-awesome-ai-for-science/catalogue/README.md

@@ -2,9 +2,9 @@
 title: "Readme"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/ai-boost/awesome-ai-for-science/blob/024f42bf/README.md
-upstream_sha: 024f42bf
-imported_at: 2026-08-09
+upstream_source: https://github.com/ai-boost/awesome-ai-for-science/blob/ec6f3650/README.md
+upstream_sha: ec6f3650
+imported_at: 2026-08-21
 prompt_class: catalogue
 upstream_changes: accepted
 author: upstream
@@ -63,6 +63,7 @@ validated: false
   - [🌍 Earth & Climate Science](#-earth--climate-science)
   - [🌾 Agriculture & Ecology](#-agriculture--ecology)
   - [🧠 Social Sciences](#-social-sciences)
+  - [🏗 Engineering & Built Environment](#-engineering--built-environment)
 - [🤖 Foundation Models for Science](#-foundation-models-for-science)
 - [📈 Datasets & Benchmarks](#-datasets--benchmarks)
 - [💻 Computing Frameworks](#-computing-frameworks)
@@ -302,6 +303,7 @@ validated: false
 - [Science-Star (USTC AI4Science, 2025)](https://github.com/ustc-ai4science/Science-Star) - Open-source platform for building, extending, and experimenting with scientific agents, providing modular agent construction tools and standardized evaluation pipelines for accelerating autonomous scientific discovery research (748+ stars, MIT License)
 - [SR-Scientist (ICLR 2026)](https://github.com/GAIR-NLP/SR-Scientist) - Scientific equation discovery with agentic AI, elevating LLMs from equation proposers to autonomous scientists that write code, analyze data, implement equations, and optimize based on experimental feedback; outperforms baselines by 6-35% across four science disciplines with robustness to noise and out-of-domain generalization (GAIR-NLP / SJTU, 49+ stars, Apache 2.0)
 - [ARA (Agent-Native Research Artifact)](https://github.com/ARA-Labs/Agent-Native-Research-Artifact) - Research ecosystem for rigorous and trustworthy AI scientists — a protocol and skill bundle that makes autonomous research verifiable, crystallized, and observable through structured, machine-executable research artifacts and five agent skills for research management, compilation, verification, visualization, and publication (ARA-Labs, 447+ stars, MIT License, 2026)
+- [XScientist](https://github.com/smileformylove/XScientist) - Local-first autonomous research system implementing a Git-like research protocol for long-running scientific discovery; explores competing explanations, executes experiments inside an isolation boundary, self-criticizes results, and exports the entire path as typed Agent-Native Research Artifacts (ARA) with exploration DAGs, claim-to-evidence anchors, content hashes, and re-execution hooks (126+ stars, Apache 2.0, arXiv 2026)
 - [Scholar Loop](https://github.com/renee-jia/scholar-loop) - Autonomous multi-agent AI scientist that mirrors a PhD workflow: literature review → grounded hypothesis → real ML experiments → self-critique → write-up; features a deterministic harness with frozen-metric scoring, edit allowlists, and a verified registry to make reward-hacking and hallucination impossible, plus 108 unit tests runnable without API keys or GPUs (461+ stars, MIT License, 2026)
 - [ResearchStudio (Microsoft)](https://github.com/microsoft/ResearchStudio) - AI co-author covering the entire research lifecycle — from an under-specified research direction to a published paper; includes ResearchStudio-Idea for evidence-grounded research ideation and ResearchStudio-Reel for turning finished papers into posters, narrated videos, blogs, and interactive reels; runs as skills on Claude Code and Codex (1.2K+ stars, MIT License, 2026)
 - [Principia](https://github.com/pzqpzq/Principia) - Principle-first scientific idea discovery framework that extracts reusable principles from public literature and private research materials, composes them into traceable Idea Cards with prior-art comparisons, and exports validation-ready research packs; emphasizes inspectable scientific objects, risk disclosure, and falsification paths (ICML 2026, 411+ stars, MIT License)
@@ -328,14 +330,17 @@ validated: false
 ### Domain-Specific Research Agents
 - [Aletheia](https://arxiv.org/abs/2602.10177) - Google DeepMind's autonomous mathematics research agent powered by Gemini Deep Think, autonomously solving 4 open problems from 700 Erdős conjectures and generating complete research papers without human intervention (February 2026)
 - [AlphaProof Nexus (Google DeepMind, arXiv 2026)](https://github.com/google-deepmind/alphaproof-nexus-results) - LLM-driven formal proof search system that pairs large language models with Lean verification to solve open mathematics problems; autonomously resolved 9 of 353 Erdős problems and 44 of 492 OEIS conjectures, with proofs and natural-language prose released for combinatorics, optimization, graph theory, algebraic geometry, and quantum optics collaborations (282+ stars, Apache 2.0)
+- [Ten Proofs (OpenAI, 2026)](https://github.com/openai/ten-proofs) - Lean 4 formalizations of ten major advances in mathematics and theoretical computer science, including improved sphere-packing bounds, non-sofic groups, a counterexample to Connes's rigidity conjecture, and quantum parallel repetition; released with the OpenAI paper and reasoning walkthroughs (57+ stars, Apache 2.0)
 - [AlphaGeometry](https://github.com/google-deepmind/alphageometry) - DeepMind's Olympiad-level geometry theorem prover combining neural language model with symbolic deduction engine, AlphaGeometry2 solves 84% of IMO geometry problems (42/50) at gold-medalist level (Nature 2024)
 - [Goedel-Prover-V2](https://github.com/Goedel-LM/Goedel-Prover-V2) - Strongest open-source automated theorem prover in Lean 4, 8B model matches DeepSeek-Prover-V2-671B at 84.6% MiniF2F, 32B model achieves 90.4% with self-correction, using scaffolded data synthesis and verifier-guided proof refinement (Princeton, 2025)
 - [DeepSeek-Prover-V2](https://github.com/deepseek-ai/DeepSeek-Prover-V2) - DeepSeek's open-source large language model for formal theorem proving in Lean 4, integrating informal and formal mathematical reasoning through recursive subgoal decomposition and reinforcement learning powered by DeepSeek-V3, with open weights and ProverBench evaluation (2025)
 - [LeanDojo](https://github.com/lean-dojo/LeanDojo) - Open-source toolkit and benchmark for learning-based theorem proving in Lean, providing programmatic Lean interaction, a 98K+ theorem dataset extracted from 217 Lean projects, and ReProver—the first retrieval-augmented LLM-based theorem prover for Lean—with reproducible training pipelines underpinning much subsequent Lean prover research (Caltech & NVIDIA, NeurIPS 2023 Outstanding Paper, Datasets & Benchmarks)
 - [Lean Copilot](https://github.com/lean-dojo/LeanCopilot) - LLMs as copilots for theorem proving in Lean 4, exposing native tactics (`suggest_tactics`, `search_proof`, `select_premises`) that embed language model inference and premise retrieval directly inside the Lean proof environment, supporting local CTranslate2/CUDA inference as well as remote model APIs for interactive and automated proof search (Caltech & NVIDIA, NeurIPS 2024, 1.2K+ stars)
 - [MathCode](https://github.com/math-ai-org/mathcode) - Terminal AI coding assistant with a built-in math formalization engine that converts plain-language math problems into Lean 4 theorems and attempts formal proofs; bundles a local Lean toolchain and WebUI for interactive mathematical reasoning (math-ai-org, 582+ stars, 2026)
+- [TorchLean (lean-dojo, 2026)](https://github.com/lean-dojo/TorchLean) - First unified Lean 4 framework for neural-network specification, execution, and verification; tensor shapes are part of the types, models are executable Lean programs, and the same definitions can be used by training code, graph transformations, certificate checkers, and proofs with CPU/CUDA backends (123+ stars, MIT License)
 - [Get Physics Done (PSI)](https://github.com/psi-oss/get-physics-done) - First open-source agentic AI physicist turning research questions into structured workflows with rigorous verification and multi-step analytical work for long-horizon physics projects; integrates with Claude Code, Codex, Gemini CLI, and OpenCode (804+ stars, Apache 2.0, 2026)
 - [Foam-Agent (NeurIPS 2025)](https://github.com/csml-rpi/Foam-Agent) - End-to-end composable multi-agent framework for automating OpenFOAM-based CFD simulations from natural language prompts, managing meshing, case setup, execution, error correction, and post-processing; achieves 100% success rate on 110 FoamBench tasks with Claude Opus 4.6 through Architect-Input Writer-Runner-Reviewer agent collaboration with RAG-enhanced generation and MCP tool integration (RPI CSML, 242+ stars, MIT License)
+- [AI CFD Scientist (RPI CSML, arXiv 2026)](https://github.com/csml-rpi/AI-CFD-Scientist) - Open-ended AI scientist for computational fluid dynamics that spans literature-grounded ideation, OpenFOAM execution via Foam-Agent, vision-language physics verification of rendered flow fields, source-code modification for new physical models, and figure-grounded LaTeX manuscript writing within a single inspectable workflow (43+ stars, Python)
 - [Zephyrus (ICLR 2026)](https://github.com/Rose-STL-Lab/Zephyrus) - First agentic framework for weather science, pairing an LLM with ZephyrusWorld (a code-execution environment exposing WeatherBench 2 data, geolocation, forecasting, simulation, and climatology tools) and ZephyrusBench (2,230 Q&A pairs across 49 weather-science tasks); outperforms text-only baselines by up to 44.2 percentage points (UC San Diego Rose-STL-Lab, 99+ stars, MIT License, 2026)
 - [BioDiscoveryAgent](https://github.com/snap-stanford/BioDiscoveryAgent) - AI agent for biological discovery and research automation
 - [Biomni](https://github.com/snap-stanford/Biomni) - General-purpose biomedical AI agent integrating LLM reasoning with retrieval-augmented planning and code-based execution to autonomously execute diverse biomedical research tasks and generate testable hypotheses (Stanford SNAP, bioRxiv 2025)
@@ -638,6 +643,7 @@ validated: false
 - [SpikeInterface](https://github.com/SpikeInterface/spikeinterface) - Unified Python framework for extracellular electrophysiology, standardizing interfaces to 10+ ML-based spike sorting algorithms including Kilosort for reproducible neural spike sorting workflows (792+ stars, actively maintained)
 - [CaImAn (Flatiron Institute)](https://github.com/flatironinstitute/CaImAn) - Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization, using machine learning for automated neuron detection and activity inference in two-photon and one-photon calcium imaging data (723+ stars, actively maintained)
 - [TRIBE v2](https://github.com/facebookresearch/tribev2) - Meta FAIR's foundation model of vision, audition, and language for in-silico neuroscience, predicting fMRI brain responses to naturalistic multimodal stimuli (video, audio, text) through unified Transformer architecture mapped to the cortical surface (2026)
+- [Brain2Qwerty (Meta FAIR, Nature Neuroscience 2026)](https://github.com/facebookresearch/brain2qwerty) - Non-invasive decoding of typed sentences from MEG and EEG brain recordings using a convolutional encoder, transformer, and character-level language model; official code for the Nature Neuroscience paper and Meta blog post on brain-AI communication (Meta FAIR, 894+ stars, CC BY-NC 4.0, 2026)
 - [braindecode](https://github.com/braindecode/braindecode) - Deep learning software to decode EEG, ECG or MEG signals, providing standardized neural network models, preprocessing pipelines, and evaluation workflows for brain-computer interfaces and cognitive neuroscience research (1.2K+ stars, BSD 3-Clause, actively maintained)
 - [snntorch](https://github.com/jeshraghian/snntorch) - Deep learning with spiking neural networks in Python, providing gradient-based training of SNNs via PyTorch autodifferentiation for brain-inspired computing and neuromorphic research, with online learning capabilities and extensive tutorials (1.9K+ stars, actively maintained)
 - [nilearn](https://github.com/nilearn/nilearn) - Machine learning and statistical learning for neuroimaging in Python, providing easy-to-use tools for fMRI and MRI analysis including decoding, connectivity estimation, and parcellation with seamless scikit-learn integration (INRIA Parietal team, 1.4K+ stars)
@@ -726,6 +732,7 @@ validated: false
 
 #### Lab Automation & Robotics
 - [PyLabRobot](https://github.com/PyLabRobot/pylabrobot) - Interactive and hardware-agnostic SDK for laboratory automation, enabling programmatic control of liquid handlers, plate readers, and other lab instruments across multiple vendors; foundational infrastructure for self-driving laboratories and AI-driven experimental execution (447+ stars)
+- [RoboChem-Flex](https://github.com/Noel-Research-Group/Robochem_Flex) - Low-cost, modular self-driving laboratory platform democratizing autonomous chemical experimentation with open control software, device CAD/PCB files, and example optimization campaigns (Noël Research Group, University of Amsterdam, Apache 2.0, 2026)
 
 ### 🌌 Physics & Astronomy
 
@@ -741,6 +748,7 @@ validated: false
 - [TORAX](https://github.com/google-deepmind/torax) - Differentiable tokamak core transport simulator for fusion energy research, coupling PDE solvers with JAX auto-differentiation and neural-network surrogates for fast forward modelling, pulse-design, and trajectory optimization (Google DeepMind, Apache 2.0)
 - [DiffPhysDrone (Nature Machine Intelligence 2025)](https://github.com/HenryHuYu/DiffPhysDrone) - First real quadrotor robot trained end-to-end with differentiable physics for vision-based agile flight, bridging simulation-based learning and real-world deployment with physics-informed neural network controllers (558+ stars)
 - [Walrus (arXiv 2025)](https://github.com/PolymathicAI/walrus) - Cross-domain foundation model for continuum dynamics trained on 19 physical scenarios spanning 63 variables, featuring adaptive compute via stride modulation and patch jittering for long-run stability (Polymathic AI, 293+ stars, MIT License)
+- [GeoPT (ICML 2026)](https://github.com/Physics-Scaling/GeoPT) - Unified pre-trained model for general physics simulation via lifted geometric pre-training, augmenting static geometry with synthetic dynamics to enable dynamics-aware self-supervision without physics labels; improves industrial-fidelity benchmarks spanning fluid mechanics and solid mechanics while reducing labeled data requirements by 20–60% (Physics-Scaling, 224+ stars)
 
 #### Astronomy & Astrophysics
 - [AstroCLIP](https://github.com/PolymathicAI/AstroCLIP) - Cross-modal self-supervised foundation model for galaxies by Polymathic AI, jointly embedding multi-band galaxy imaging and optical spectra into a shared latent space to enable zero/few-shot redshift estimation, galaxy property prediction, morphology classification, and cross-modal similarity search (MNRAS Letters 2024)
@@ -785,6 +793,7 @@ validated: false
 - [SkySensePlusPlus](https://github.com/kang-wu/SkySensePlusPlus) - Semantic-enhanced multi-modal remote sensing foundation model for Earth observation (Nature Machine Intelligence 2025), enabling universal interpretation across diverse satellite imagery modalities with open-source weights and benchmarks
 - [TESSERA (CVPR 2026)](https://github.com/ucam-eo/tessera) - University of Cambridge's foundation model for time-series satellite imagery, enabling efficient extraction of temporal patterns from Earth observation for land classification, canopy height prediction, and other remote sensing tasks
 - [TerraMind (IBM & ESA, 2025)](https://github.com/IBM/terramind) - First any-to-any generative foundation model for Earth Observation, enabling unified multimodal understanding and generation across diverse satellite sensors and geospatial tasks through a single architecture (258+ stars)
+- [GeoAgent (opengeos, 2026)](https://github.com/opengeos/GeoAgent) - Shared multimodal AI agent layer for geospatial Python packages (leafmap, geoai, geemap, STAC, NASA Earthdata) and QGIS, exposing geospatial tools to LLMs with structured metadata, confirmation hooks, and support for OpenAI, Anthropic, Google Gemini, Ollama, and more; includes the OpenGeoAgent QGIS plugin (456+ stars, MIT License)
 - [Awesome Remote Sensing Foundation Models](https://github.com/Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models) - Curated collection of papers, datasets, benchmarks, code, and pre-trained weights for Remote Sensing Foundation Models (RSFMs), tracking the rapidly evolving landscape of vision, vision-language, generative, and agent-based geospatial AI (1.9K+ stars, 2024-2026)
 
 ### 🌾 Agriculture & Ecology
@@ -794,6 +803,7 @@ validated: false
 - [AgML](https://github.com/Project-AgML/AgML) - Agricultural machine learning platform
 - [FarmVibes.AI](https://github.com/microsoft/farmvibes-ai) - Multi-modal geospatial ML platform for agriculture and sustainability, fusing satellite imagery (RGB, SAR, multispectral), drone imagery, weather data, and sensor data for crop identification, carbon footprint estimation, and microclimate prediction (Microsoft Research, MIT License)
 - [PlantCV](https://github.com/danforthcenter/plantcv) - Open-source image analysis toolkit for high-throughput plant phenotyping, extracting morphological, color, and texture traits from RGB, hyperspectral, and thermal imagery with modular Python workflows for crop improvement, stress detection, and plant biology research (Donald Danforth Plant Science Center, 795+ stars, MPL-2.0)
+- [Virdis](https://github.com/Thanas-R/Virdis) - Satellite-powered agricultural and land analytics platform combining Sentinel-2 imagery, Google Earth Engine processing, real-time weather data, soil science databases, and AI-driven crop planning into a unified web dashboard (145+ stars, AGPL-3.0, 2026)
 
 #### Ecological Modeling
 - [BioSimulators](https://github.com/biosimulators/Biosimulators) - Biological simulation tools
@@ -813,6 +823,22 @@ validated: false
 
 ---
 
+## 🏗 Engineering & Built Environment
+
+### Mechanical, Aerospace & Industrial Engineering
+- [Noether (Emmi AI)](https://github.com/Emmi-AI/noether) - Open software framework for Engineering AI built on transformer building blocks, enabling teams to build, train, and operate industrial simulation models across engineering verticals; includes ready-to-use recipes for CFD (AB-UPT on DrivAerML), external aerodynamics, and heat transfer (234+ stars, ENPL non-commercial license, 2026)
+
+### Structural & Civil Engineering
+- [StructureClaw](https://github.com/structureclaw/structureclaw) - AI-assisted structural engineering workspace for AEC workflows: natural language to structural model, analysis, code-check, and report (171+ stars, MIT License, 2026)
+
+### Architectural Design & BIM
+- [Aedifex](https://github.com/TangSY/aedifex) - Open-source 3D architectural editor with an AI design assistant; build floor plans with walls, doors, windows, and furniture using natural language, with real-time WebGPU-powered previews (TangSY, 59+ stars, MIT License, 2026)
+
+### Electrical & Electronics Engineering
+- [kicad-happy](https://github.com/aklofas/kicad-happy) - AI coding agent skills for KiCad electronics design that turn Claude Code, Codex, Gemini CLI, and other coding agents into full electronics design assistants; parses schematics and PCB layouts, builds power trees, audits connectors/ESD protection, validates passive networks, runs SPICE simulation, sources components from major distributors, and prepares boards for fabrication (aklofas, 974+ stars, MIT License, 2026)
+
+---
+
 ## 🤖 Foundation Models for Science
 
 ### General Science Models
@@ -983,6 +1009,7 @@ This project builds upon and complements several excellent resources:
 
 ### 📊 Paper & Research Collections
 - [Scientific LLM Papers](https://github.com/yuzhimanhua/Awesome-Scientific-Language-Models) - 260+ scientific language models
+- [Awesome Scientific LLM Benchmarks](https://github.com/subinium/Awesome-Scientific-LLM-Benchmarks) - Curated, accuracy-first collection of benchmarks for evaluating LLMs on scientific reasoning and discovery across mathematics, physics, chemistry, materials science, biology, and agentic science (subinium, 29+ stars, MIT License, 2026)
 - [LLM4SR Repository](https://github.com/du-nlp-lab/LLM4SR) - LLM for scientific research survey materials
 - [PINNs Paper Collection](https://github.com/idrl-lab/PINNpapers) - Physics-informed neural networks research
 - [SciML Papers](https://sciml.ai/papers/) - Scientific computing and machine learning papers

upstream/inoue0426-awesome-computational-biology/catalogue/README.md

@@ -2,9 +2,9 @@
 title: "Awesome Computational Biology [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/README.md
-upstream_sha: 7a064bf0
-imported_at: 2026-08-08
+upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/c6f07d90/README.md
+upstream_sha: c6f07d90
+imported_at: 2026-08-31
 prompt_class: catalogue
 upstream_changes: accepted
 author: upstream
@@ -75,6 +75,7 @@ Browse and search the resources via the [GitHub Pages UI](https://inoue0426.gith
       - [Drug Target Interaction](#drug-target-interaction)
       - [Compound-Protein Interaction](#compound-protein-interaction)
       - [Molecular Generation](#molecular-generation)
+    - [Protein Property Prediction](#protein-property-prediction)
     - [LLM for Biology](#llm-for-biology)
     - [Foundation Models](#foundation-models)
       - [Single-cell Foundation Models](#single-cell-foundation-models)
@@ -159,6 +160,7 @@ Browse and search the resources via the [GitHub Pages UI](https://inoue0426.gith
 - [GenBank](https://www.ncbi.nlm.nih.gov/genbank/) — NCBI's database of genetic sequences.
 - [UCSC Genome Browser](https://genome.ucsc.edu/) — UCSC's genome browser.
 - [cBioPortal](https://www.cbioportal.org/) — Cancer genomics database; aggregating many patient datasets.
+- [OncoKB](https://www.oncokb.org/) — Precision oncology knowledge base of cancer genes, variants, and therapeutic implications.
 - [10x Genomics Dataset](https://www.10xgenomics.com/resources/datasets) — Collection of single-cell datasets.
 - [The Genotype-Tissue Expression (GTEx)](https://gtexportal.org/home/) — Human gene expression and regulation resource.
 - [Dependency Map (DepMap)](https://depmap.org/portal/) — CRISPR-Cas9 screens in cancer cell lines.
@@ -316,7 +318,7 @@ Browse and search the resources via the [GitHub Pages UI](https://inoue0426.gith
 - [CellCharter](https://github.com/CSOgroup/cellcharter) — Identification and characterization of spatial cell niches from spatial transcriptomics using VAEs and Gaussian mixture models.
 - [STAGATE](https://github.com/RucDongLab/STAGATE) — Adaptive graph attention auto-encoder for spatial domain identification in spatial transcriptomics.
 - [NCEM](https://github.com/theislab/ncem) — GNN-based model for learning intercellular communication from spatial graphs of cells.
-- [DeepTalk](https://github.com/JiangBioLab/DeepTalk) — Graph attention network for deciphering cell-cell communication from spatial transcriptomics data.
+- [DeepTalk](https://github.com/JiangBioLab/DeepTalk) — Graph attention network for deciphering cell-cell communication from spatial transcriptomics.
 - [COMMOT](https://github.com/zcang/COMMOT) — Optimal transport-based framework for screening cell-cell communication in spatial transcriptomics.
 - [TIGON](https://github.com/yutongo/TIGON) — Neural optimal transport method for reconstructing growth and dynamic trajectories from single-cell transcriptomics.
 - [LINGER](https://github.com/Durenlab/LINGER) — Neural network for gene regulatory network inference from single-cell multiome (RNA+ATAC-seq) data with bulk data pretraining.
@@ -383,6 +385,10 @@ Browse and search the resources via the [GitHub Pages UI](https://inoue0426.gith
 - [ReLeaSE](https://github.com/isayev/ReLeaSE) — Deep reinforcement learning framework for de novo drug design combining a generative and predictive model.
 - [PaccMannRL](https://github.com/PaccMann/paccmann_generator) — Reinforcement learning-based generative model for de novo hit-like anticancer molecule design from transcriptomic data.
 
+### Protein Property Prediction
+
+- [NbBayesLM](https://github.com/FairuzShadmaniShishir/NbBayesLM) — Bayesian neural network integrating protein language model embeddings and physicochemical features to predict nanobody thermostability with uncertainty estimates. [Paper](https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2026.1832968/full)
+
 ### LLM for Biology
 
 - [AI4Chem/ChemLLM-7B-Chat](https://huggingface.co/AI4Chem/ChemLLM-7B-Chat) — LLM for chemical & molecular science.
@@ -439,7 +445,7 @@ Browse and search the resources via the [GitHub Pages UI](https://inoue0426.gith
 - [GeneCompass](https://github.com/xCompass-AI/GeneCompass) — Large-scale foundation model integrating DNA regulatory sequences and single-cell transcriptomics from 120M+ cells across multiple species for gene regulation prediction.
 - [UnitedNet](https://github.com/LiuLab-Bioelectronics-Harvard/UnitedNet) — Interpretable multi-task deep neural network for single-cell multi-omics integration spanning transcriptomics, chromatin accessibility, and proteomics.
 - [SpatialGlue](https://github.com/zhanglabtools/SpatialGlue) — Graph attention network for spatial multi-omics integration jointly embedding spatial transcriptomics with chromatin accessibility or proteomics.
-- [MIDAS](https://github.com/labomics/midas) — Mosaic integration and differential accessibility model for single-cell multi-omics data that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics.
+- [MIDAS](https://github.com/labomics/midas) — Mosaic integration and differential accessibility model for single-cell multi-omics that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics.
 - [Concerto](https://github.com/melobio/Concerto-reproducibility) — Contrastive self-supervised learning framework for single-cell multimodal data integration, batch correction, and reference-query mapping.
 - [scButterfly](https://github.com/BioX-NKU/scButterfly) — Dual-aligned variational autoencoder for single-cell cross-modality translation between paired and unpaired multiomics data.
 - [JAMIE](https://github.com/Oafish1/JAMIE) — Joint variational autoencoder for multimodal single-cell data imputation and embedding.
@@ -521,6 +527,7 @@ If you use this list in papers, slides, or documentation, please cite this repos
 To keep quality high, additions should meet all of the following:
 
 - The resource is trustworthy and relevant to computational biology.
+- The resource has clear value to the scope and audience of this collection; highly specialized resources with limited relevance beyond a narrow application context may be declined even when technically sound.
 - The primary link points to an official source (official docs, organization site, maintained repository, or official dataset page).
 - The resource has evidence of technical substance: ideally a peer-reviewed paper; at minimum a preprint or official technical documentation.
 - The description is factual and concise (no marketing copy).

upstream/inoue0426-awesome-computational-biology/catalogue/cspell.json

@@ -2,9 +2,9 @@
 title: "Cspell"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/cspell.json
-upstream_sha: 7a064bf0
-imported_at: 2026-08-08
+upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/c6f07d90/cspell.json
+upstream_sha: c6f07d90
+imported_at: 2026-08-31
 prompt_class: unknown
 upstream_changes: accepted
 author: upstream
@@ -59,6 +59,7 @@ validated: false
     "eukaryotic",
     "metabolites",
     "OMIM",
+    "OncoKB",
     "Mendelian",
     "DisGeNET",
     "GWAS",
@@ -171,7 +172,9 @@ validated: false
     "bowang",
     "ctheodoris",
     "OpenAI",
-    "GPT"
+    "GPT",
+    "nanobody",
+    "thermostability"
   ],
   "ignorePaths": [
     "node_modules/**"

upstream/inoue0426-awesome-computational-biology/catalogue/data/resources.json

@@ -2,9 +2,9 @@
 title: "Resources"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/data/resources.json
-upstream_sha: 7a064bf0
-imported_at: 2026-08-08
+upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/c6f07d90/data/resources.json
+upstream_sha: c6f07d90
+imported_at: 2026-08-31
 prompt_class: catalogue
 upstream_changes: accepted
 author: upstream
@@ -899,10 +899,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "single-cell-rna-seq",
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "documentation": "https://www.10xgenomics.com/resources/datasets",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.10xgenomics.com/resources/datasets"
+    ]
   },
   {
     "id": "alphafold_protein_structure_database",
@@ -915,10 +925,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein"
+      "molecular-structure",
+      "protein-sequence"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "protein"
+    ],
+    "documentation": "https://alphafold.ebi.ac.uk/api-docs",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://alphafold.ebi.ac.uk/",
+      "https://alphafold.ebi.ac.uk/api-docs"
+    ]
   },
   {
     "id": "bindingdb",
@@ -932,11 +952,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein",
-      "Small Molecule"
+      "chemical-structure",
+      "molecular-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "molecule",
+      "protein"
+    ],
+    "documentation": "https://www.bindingdb.org/rwd/bind/index.jsp",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.bindingdb.org/rwd/bind/index.jsp"
+    ]
   },
   {
     "id": "biocyc",
@@ -949,10 +978,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Pathway"
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "gene",
+      "pathway",
+      "organism"
+    ],
+    "documentation": "https://biocyc.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://biocyc.org/"
+    ]
   },
   {
     "id": "biogrid",
@@ -969,7 +1008,16 @@ validated: false
       "Protein"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "gene",
+      "protein"
+    ],
+    "documentation": "https://thebiogrid.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://thebiogrid.org/"
+    ]
   },
   {
     "id": "cancer_cell_line_encyclopedia",
@@ -983,11 +1031,22 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Gene Expression",
-      "Small Molecule"
+      "genomics",
+      "transcriptomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene",
+      "disease",
+      "drug"
+    ],
+    "documentation": "https://sites.broadinstitute.org/ccle/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://sites.broadinstitute.org/ccle/"
+    ]
   },
   {
     "id": "catalogue_of_somatic_mutations_in_cancer_cosmic",
@@ -1000,10 +1059,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "disease",
+      "gene",
+      "variant"
+    ],
+    "documentation": "https://cancer.sanger.ac.uk/cosmic",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://cancer.sanger.ac.uk/cosmic"
+    ]
   },
   {
     "id": "cath_database",
@@ -1016,10 +1085,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein"
+      "molecular-structure",
+      "protein-sequence"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "protein"
+    ],
+    "documentation": "https://www.cathdb.info/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.cathdb.info/"
+    ]
   },
   {
     "id": "cbioportal",
@@ -1032,10 +1110,23 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "genomics",
+      "clinical"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "disease",
+      "gene",
+      "variant"
+    ],
+    "github": "https://github.com/cBioPortal/cbioportal",
+    "documentation": "https://www.cbioportal.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.cbioportal.org/",
+      "https://github.com/cBioPortal/cbioportal"
+    ]
   },
   {
     "id": "cellminer_cross_database_cellminercdb",
@@ -1092,10 +1183,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "compound",
+      "molecule",
+      "protein"
+    ],
+    "documentation": "https://www.ebi.ac.uk/chembl/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.ebi.ac.uk/chembl/"
+    ]
   },
   {
     "id": "chemspider",
@@ -1124,10 +1225,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Clinical"
+      "clinical"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "disease",
+      "drug"
+    ],
+    "documentation": "https://clinicaltrials.gov/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://clinicaltrials.gov/"
+    ]
   },
   {
     "id": "comparative_toxicogenomics_database",
@@ -1141,11 +1251,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Gene",
-      "Small Molecule"
+      "knowledge-graph"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "compound",
+      "gene",
+      "disease"
+    ],
+    "documentation": "https://ctdbase.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://ctdbase.org/"
+    ]
   },
   {
     "id": "critical_assessment_of_structure_prediction_casp",
@@ -1174,10 +1293,21 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Single Cell"
+      "single-cell-rna-seq",
+      "transcriptomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene",
+      "tissue"
+    ],
+    "documentation": "https://cellxgene.cziscience.com/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://cellxgene.cziscience.com/"
+    ]
   },
   {
     "id": "davis_kinase_inhibitors_db",
@@ -1208,10 +1338,21 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene",
+      "disease",
+      "drug"
+    ],
+    "documentation": "https://depmap.org/portal/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://depmap.org/portal/"
+    ]
   },
   {
     "id": "dgidb",
@@ -1225,11 +1366,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Gene",
-      "Small Molecule"
+      "knowledge-graph"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "gene"
+    ],
+    "documentation": "https://www.dgidb.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.dgidb.org/"
+    ]
   },
   {
     "id": "diseases",
@@ -1292,10 +1441,21 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Knowledge Graph"
+      "knowledge-graph"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "disease",
+      "gene",
+      "pathway"
+    ],
+    "github": "https://github.com/SuLab/DrugMechDB",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/SuLab/DrugMechDB"
+    ]
   },
   {
     "id": "drug_repurposing_hub",
@@ -1308,10 +1468,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "protein",
+      "disease"
+    ],
+    "documentation": "https://repo-hub.broadinstitute.org/repurposing",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://repo-hub.broadinstitute.org/repurposing"
+    ]
   },
   {
     "id": "drugbank",
@@ -1349,10 +1519,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "protein",
+      "disease"
+    ],
+    "documentation": "https://drugcentral.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://drugcentral.org/"
+    ]
   },
   {
     "id": "drugtargetcommons",
@@ -1365,10 +1545,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "protein"
+    ],
+    "documentation": "https://drugtargetcommons.fimm.fi/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://drugtargetcommons.fimm.fi/"
+    ]
   },
   {
     "id": "encode",
@@ -1936,6 +2125,22 @@ validated: false
     "organism": [],
     "api": false
   },
+  {
+    "id": "oncokb",
+    "name": "OncoKB",
+    "type": "database",
+    "url": "https://www.oncokb.org/",
+    "description": "Precision oncology knowledge base of cancer genes, variants, and therapeutic implications.",
+    "tags": [
+      "genome"
+    ],
+    "tasks": [],
+    "modalities": [
+      "Genomics"
+    ],
+    "organism": [],
+    "api": false
+  },
   {
     "id": "open_targets_platform",
     "name": "Open Targets Platform",
@@ -2383,10 +2588,18 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein"
+      "protein-sequence"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "protein"
+    ],
+    "documentation": "https://www.uniprot.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.uniprot.org/"
+    ]
   },
   {
     "id": "uniref",
@@ -3995,7 +4208,7 @@ validated: false
     "name": "MIDAS",
     "type": "model",
     "url": "https://github.com/labomics/midas",
-    "description": "Mosaic integration and differential accessibility model for single-cell multi-omics data that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics.",
+    "description": "Mosaic integration and differential accessibility model for single-cell multi-omics that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics.",
     "tags": [
       "foundation-models",
       "multi-omics-foundation-models",
@@ -4266,6 +4479,24 @@ validated: false
     "organism": [],
     "api": false
   },
+  {
+    "id": "nbbayeslm",
+    "name": "NbBayesLM",
+    "type": "model",
+    "url": "https://github.com/FairuzShadmaniShishir/NbBayesLM",
+    "description": "Bayesian neural network integrating protein language model embeddings and physicochemical features to predict nanobody thermostability with uncertainty estimates. [Paper](https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2026.1832968/full)",
+    "tags": [
+      "protein-property-prediction"
+    ],
+    "tasks": [
+      "Protein Property Prediction"
+    ],
+    "modalities": [
+      "Protein"
+    ],
+    "organism": [],
+    "api": false
+  },
   {
     "id": "neodti",
     "name": "NeoDTI",
@@ -5444,9 +5675,23 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "dna-sequence",
+      "protein-sequence"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "gene",
+      "protein"
+    ],
+    "github": "https://github.com/biopython/biopython",
+    "documentation": "https://biopython.org/wiki/Documentation",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/biopython/biopython",
+      "https://biopython.org/"
+    ]
   },
   {
     "id": "casper",
@@ -5476,9 +5721,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "spatial-transcriptomics"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "tissue"
+    ],
+    "github": "https://github.com/CSOgroup/cellcharter",
+    "documentation": "https://cellcharter.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/CSOgroup/cellcharter",
+      "https://cellcharter.readthedocs.io/"
+    ]
   },
   {
     "id": "cellchat",
@@ -5492,9 +5750,20 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/sqjin/CellChat",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/sqjin/CellChat"
+    ]
   },
   {
     "id": "celltypist",
@@ -5506,11 +5775,24 @@ validated: false
       "preprocessing-tools"
     ],
     "tasks": [
-      "Preprocessing"
+      "cell-type-annotation"
+    ],
+    "modalities": [
+      "single-cell-rna-seq"
     ],
-    "modalities": [],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/Teichlab/celltypist",
+    "documentation": "https://celltypist.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/Teichlab/celltypist",
+      "https://celltypist.readthedocs.io/"
+    ]
   },
   {
     "id": "chatspatial",
@@ -5572,16 +5854,30 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "chemical-structure",
+      "molecular-structure"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "molecule",
+      "protein"
+    ],
+    "github": "https://github.com/deepchem/deepchem",
+    "documentation": "https://deepchem.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/deepchem/deepchem",
+      "https://deepchem.readthedocs.io/"
+    ]
   },
   {
     "id": "deeptalk",
     "name": "DeepTalk",
     "type": "toolkit",
     "url": "https://github.com/JiangBioLab/DeepTalk",
-    "description": "Graph attention network for deciphering cell-cell communication from spatial transcriptomics data.",
+    "description": "Graph attention network for deciphering cell-cell communication from spatial transcriptomics.",
     "tags": [
       "preprocessing-tools"
     ],
@@ -5796,9 +6092,21 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "chemical-structure"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "molecule"
+    ],
+    "github": "https://github.com/rdkit/rdkit",
+    "documentation": "https://www.rdkit.org/docs/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/rdkit/rdkit",
+      "https://www.rdkit.org/docs/"
+    ]
   },
   {
     "id": "scanpy",
@@ -5812,9 +6120,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/scverse/scanpy",
+    "documentation": "https://scanpy.readthedocs.io/en/stable/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/scverse/scanpy",
+      "https://scanpy.readthedocs.io/en/stable/"
+    ]
   },
   {
     "id": "scenic",
@@ -5876,9 +6197,23 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq",
+      "multi-omics"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/scverse/scvi-tools",
+    "documentation": "https://docs.scvi-tools.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/scverse/scvi-tools",
+      "https://docs.scvi-tools.org/"
+    ]
   },
   {
     "id": "seqbench",
@@ -5908,9 +6243,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/satijalab/seurat",
+    "documentation": "https://satijalab.org/seurat/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/satijalab/seurat",
+      "https://satijalab.org/seurat/"
+    ]
   },
   {
     "id": "squidpy",
@@ -5924,9 +6272,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "spatial-transcriptomics"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "tissue"
+    ],
+    "github": "https://github.com/scverse/squidpy",
+    "documentation": "https://squidpy.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/scverse/squidpy",
+      "https://squidpy.readthedocs.io/"
+    ]
   },
   {
     "id": "stagate",

upstream/inoue0426-awesome-computational-biology/catalogue/data/resources.yml

@@ -2,9 +2,9 @@
 title: "Awesome Computational Biology - machine-readable resource list"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/data/resources.yml
-upstream_sha: 7a064bf0
-imported_at: 2026-08-08
+upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/c6f07d90/data/resources.yml
+upstream_sha: c6f07d90
+imported_at: 2026-08-31
 prompt_class: catalogue
 upstream_changes: accepted
 author: upstream
@@ -1183,6 +1183,17 @@ resources:
     organism: []
     api: false
 
+  - id: oncokb
+    name: "OncoKB"
+    type: database
+    url: https://www.oncokb.org/
+    description: "Precision oncology knowledge base of cancer genes, variants, and therapeutic implications."
+    tags: [genome]
+    tasks: []
+    modalities: [Genomics]
+    organism: []
+    api: false
+
   - id: open_targets_platform
     name: "Open Targets Platform"
     type: database
@@ -2243,7 +2254,7 @@ resources:
     name: "MIDAS"
     type: model
     url: https://github.com/labomics/midas
-    description: "Mosaic integration and differential accessibility model for single-cell multi-omics data that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics."
+    description: "Mosaic integration and differential accessibility model for single-cell multi-omics that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics."
     tags: [foundation-models, multi-omics-foundation-models, single-cell-foundation-models]
     tasks: [Foundation Model]
     modalities: [Multi-Omics, Single Cell]
@@ -2382,6 +2393,17 @@ resources:
     organism: []
     api: false
 
+  - id: nbbayeslm
+    name: "NbBayesLM"
+    type: model
+    url: https://github.com/FairuzShadmaniShishir/NbBayesLM
+    description: "Bayesian neural network integrating protein language model embeddings and physicochemical features to predict nanobody thermostability with uncertainty estimates. [Paper](https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2026.1832968/full)"
+    tags: [protein-property-prediction]
+    tasks: [Protein Property Prediction]
+    modalities: [Protein]
+    organism: []
+    api: false
+
   - id: neodti
     name: "NeoDTI"
     type: model
@@ -2980,7 +3002,7 @@ resources:
     name: "DeepTalk"
     type: toolkit
     url: https://github.com/JiangBioLab/DeepTalk
-    description: "Graph attention network for deciphering cell-cell communication from spatial transcriptomics data."
+    description: "Graph attention network for deciphering cell-cell communication from spatial transcriptomics."
     tags: [preprocessing-tools]
     tasks: [Preprocessing]
     modalities: []

upstream/inoue0426-awesome-computational-biology/catalogue/docs/data/resources.json

@@ -2,9 +2,9 @@
 title: "Resources"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/docs/data/resources.json
-upstream_sha: 7a064bf0
-imported_at: 2026-08-08
+upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/c6f07d90/docs/data/resources.json
+upstream_sha: c6f07d90
+imported_at: 2026-08-31
 prompt_class: catalogue
 upstream_changes: accepted
 author: upstream
@@ -899,10 +899,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "single-cell-rna-seq",
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "documentation": "https://www.10xgenomics.com/resources/datasets",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.10xgenomics.com/resources/datasets"
+    ]
   },
   {
     "id": "alphafold_protein_structure_database",
@@ -915,10 +925,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein"
+      "molecular-structure",
+      "protein-sequence"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "protein"
+    ],
+    "documentation": "https://alphafold.ebi.ac.uk/api-docs",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://alphafold.ebi.ac.uk/",
+      "https://alphafold.ebi.ac.uk/api-docs"
+    ]
   },
   {
     "id": "bindingdb",
@@ -932,11 +952,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein",
-      "Small Molecule"
+      "chemical-structure",
+      "molecular-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "molecule",
+      "protein"
+    ],
+    "documentation": "https://www.bindingdb.org/rwd/bind/index.jsp",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.bindingdb.org/rwd/bind/index.jsp"
+    ]
   },
   {
     "id": "biocyc",
@@ -949,10 +978,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Pathway"
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "gene",
+      "pathway",
+      "organism"
+    ],
+    "documentation": "https://biocyc.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://biocyc.org/"
+    ]
   },
   {
     "id": "biogrid",
@@ -969,7 +1008,16 @@ validated: false
       "Protein"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "gene",
+      "protein"
+    ],
+    "documentation": "https://thebiogrid.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://thebiogrid.org/"
+    ]
   },
   {
     "id": "cancer_cell_line_encyclopedia",
@@ -983,11 +1031,22 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Gene Expression",
-      "Small Molecule"
+      "genomics",
+      "transcriptomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene",
+      "disease",
+      "drug"
+    ],
+    "documentation": "https://sites.broadinstitute.org/ccle/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://sites.broadinstitute.org/ccle/"
+    ]
   },
   {
     "id": "catalogue_of_somatic_mutations_in_cancer_cosmic",
@@ -1000,10 +1059,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "disease",
+      "gene",
+      "variant"
+    ],
+    "documentation": "https://cancer.sanger.ac.uk/cosmic",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://cancer.sanger.ac.uk/cosmic"
+    ]
   },
   {
     "id": "cath_database",
@@ -1016,10 +1085,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein"
+      "molecular-structure",
+      "protein-sequence"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "protein"
+    ],
+    "documentation": "https://www.cathdb.info/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.cathdb.info/"
+    ]
   },
   {
     "id": "cbioportal",
@@ -1032,10 +1110,23 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "genomics",
+      "clinical"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "disease",
+      "gene",
+      "variant"
+    ],
+    "github": "https://github.com/cBioPortal/cbioportal",
+    "documentation": "https://www.cbioportal.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.cbioportal.org/",
+      "https://github.com/cBioPortal/cbioportal"
+    ]
   },
   {
     "id": "cellminer_cross_database_cellminercdb",
@@ -1092,10 +1183,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "compound",
+      "molecule",
+      "protein"
+    ],
+    "documentation": "https://www.ebi.ac.uk/chembl/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.ebi.ac.uk/chembl/"
+    ]
   },
   {
     "id": "chemspider",
@@ -1124,10 +1225,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Clinical"
+      "clinical"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "disease",
+      "drug"
+    ],
+    "documentation": "https://clinicaltrials.gov/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://clinicaltrials.gov/"
+    ]
   },
   {
     "id": "comparative_toxicogenomics_database",
@@ -1141,11 +1251,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Gene",
-      "Small Molecule"
+      "knowledge-graph"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "compound",
+      "gene",
+      "disease"
+    ],
+    "documentation": "https://ctdbase.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://ctdbase.org/"
+    ]
   },
   {
     "id": "critical_assessment_of_structure_prediction_casp",
@@ -1174,10 +1293,21 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Single Cell"
+      "single-cell-rna-seq",
+      "transcriptomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene",
+      "tissue"
+    ],
+    "documentation": "https://cellxgene.cziscience.com/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://cellxgene.cziscience.com/"
+    ]
   },
   {
     "id": "davis_kinase_inhibitors_db",
@@ -1208,10 +1338,21 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Genomics"
+      "genomics"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene",
+      "disease",
+      "drug"
+    ],
+    "documentation": "https://depmap.org/portal/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://depmap.org/portal/"
+    ]
   },
   {
     "id": "dgidb",
@@ -1225,11 +1366,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Gene",
-      "Small Molecule"
+      "knowledge-graph"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "gene"
+    ],
+    "documentation": "https://www.dgidb.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.dgidb.org/"
+    ]
   },
   {
     "id": "diseases",
@@ -1292,10 +1441,21 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Knowledge Graph"
+      "knowledge-graph"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "disease",
+      "gene",
+      "pathway"
+    ],
+    "github": "https://github.com/SuLab/DrugMechDB",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/SuLab/DrugMechDB"
+    ]
   },
   {
     "id": "drug_repurposing_hub",
@@ -1308,10 +1468,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "protein",
+      "disease"
+    ],
+    "documentation": "https://repo-hub.broadinstitute.org/repurposing",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://repo-hub.broadinstitute.org/repurposing"
+    ]
   },
   {
     "id": "drugbank",
@@ -1349,10 +1519,20 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "protein",
+      "disease"
+    ],
+    "documentation": "https://drugcentral.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://drugcentral.org/"
+    ]
   },
   {
     "id": "drugtargetcommons",
@@ -1365,10 +1545,19 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Small Molecule"
+      "chemical-structure"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "drug",
+      "protein"
+    ],
+    "documentation": "https://drugtargetcommons.fimm.fi/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://drugtargetcommons.fimm.fi/"
+    ]
   },
   {
     "id": "encode",
@@ -1936,6 +2125,22 @@ validated: false
     "organism": [],
     "api": false
   },
+  {
+    "id": "oncokb",
+    "name": "OncoKB",
+    "type": "database",
+    "url": "https://www.oncokb.org/",
+    "description": "Precision oncology knowledge base of cancer genes, variants, and therapeutic implications.",
+    "tags": [
+      "genome"
+    ],
+    "tasks": [],
+    "modalities": [
+      "Genomics"
+    ],
+    "organism": [],
+    "api": false
+  },
   {
     "id": "open_targets_platform",
     "name": "Open Targets Platform",
@@ -2383,10 +2588,18 @@ validated: false
     ],
     "tasks": [],
     "modalities": [
-      "Protein"
+      "protein-sequence"
     ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "protein"
+    ],
+    "documentation": "https://www.uniprot.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://www.uniprot.org/"
+    ]
   },
   {
     "id": "uniref",
@@ -3995,7 +4208,7 @@ validated: false
     "name": "MIDAS",
     "type": "model",
     "url": "https://github.com/labomics/midas",
-    "description": "Mosaic integration and differential accessibility model for single-cell multi-omics data that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics.",
+    "description": "Mosaic integration and differential accessibility model for single-cell multi-omics that handles arbitrary missing-modality combinations across transcriptomics, chromatin accessibility, and proteomics.",
     "tags": [
       "foundation-models",
       "multi-omics-foundation-models",
@@ -4266,6 +4479,24 @@ validated: false
     "organism": [],
     "api": false
   },
+  {
+    "id": "nbbayeslm",
+    "name": "NbBayesLM",
+    "type": "model",
+    "url": "https://github.com/FairuzShadmaniShishir/NbBayesLM",
+    "description": "Bayesian neural network integrating protein language model embeddings and physicochemical features to predict nanobody thermostability with uncertainty estimates. [Paper](https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2026.1832968/full)",
+    "tags": [
+      "protein-property-prediction"
+    ],
+    "tasks": [
+      "Protein Property Prediction"
+    ],
+    "modalities": [
+      "Protein"
+    ],
+    "organism": [],
+    "api": false
+  },
   {
     "id": "neodti",
     "name": "NeoDTI",
@@ -5444,9 +5675,23 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "dna-sequence",
+      "protein-sequence"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "gene",
+      "protein"
+    ],
+    "github": "https://github.com/biopython/biopython",
+    "documentation": "https://biopython.org/wiki/Documentation",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/biopython/biopython",
+      "https://biopython.org/"
+    ]
   },
   {
     "id": "casper",
@@ -5476,9 +5721,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "spatial-transcriptomics"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "tissue"
+    ],
+    "github": "https://github.com/CSOgroup/cellcharter",
+    "documentation": "https://cellcharter.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/CSOgroup/cellcharter",
+      "https://cellcharter.readthedocs.io/"
+    ]
   },
   {
     "id": "cellchat",
@@ -5492,9 +5750,20 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/sqjin/CellChat",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/sqjin/CellChat"
+    ]
   },
   {
     "id": "celltypist",
@@ -5506,11 +5775,24 @@ validated: false
       "preprocessing-tools"
     ],
     "tasks": [
-      "Preprocessing"
+      "cell-type-annotation"
+    ],
+    "modalities": [
+      "single-cell-rna-seq"
     ],
-    "modalities": [],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/Teichlab/celltypist",
+    "documentation": "https://celltypist.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/Teichlab/celltypist",
+      "https://celltypist.readthedocs.io/"
+    ]
   },
   {
     "id": "chatspatial",
@@ -5572,16 +5854,30 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "chemical-structure",
+      "molecular-structure"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "molecule",
+      "protein"
+    ],
+    "github": "https://github.com/deepchem/deepchem",
+    "documentation": "https://deepchem.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/deepchem/deepchem",
+      "https://deepchem.readthedocs.io/"
+    ]
   },
   {
     "id": "deeptalk",
     "name": "DeepTalk",
     "type": "toolkit",
     "url": "https://github.com/JiangBioLab/DeepTalk",
-    "description": "Graph attention network for deciphering cell-cell communication from spatial transcriptomics data.",
+    "description": "Graph attention network for deciphering cell-cell communication from spatial transcriptomics.",
     "tags": [
       "preprocessing-tools"
     ],
@@ -5796,9 +6092,21 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "chemical-structure"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "molecule"
+    ],
+    "github": "https://github.com/rdkit/rdkit",
+    "documentation": "https://www.rdkit.org/docs/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/rdkit/rdkit",
+      "https://www.rdkit.org/docs/"
+    ]
   },
   {
     "id": "scanpy",
@@ -5812,9 +6120,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/scverse/scanpy",
+    "documentation": "https://scanpy.readthedocs.io/en/stable/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/scverse/scanpy",
+      "https://scanpy.readthedocs.io/en/stable/"
+    ]
   },
   {
     "id": "scenic",
@@ -5876,9 +6197,23 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq",
+      "multi-omics"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/scverse/scvi-tools",
+    "documentation": "https://docs.scvi-tools.org/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/scverse/scvi-tools",
+      "https://docs.scvi-tools.org/"
+    ]
   },
   {
     "id": "seqbench",
@@ -5908,9 +6243,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "single-cell-rna-seq"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "gene"
+    ],
+    "github": "https://github.com/satijalab/seurat",
+    "documentation": "https://satijalab.org/seurat/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/satijalab/seurat",
+      "https://satijalab.org/seurat/"
+    ]
   },
   {
     "id": "squidpy",
@@ -5924,9 +6272,22 @@ validated: false
     "tasks": [
       "Preprocessing"
     ],
-    "modalities": [],
+    "modalities": [
+      "spatial-transcriptomics"
+    ],
     "organism": [],
-    "api": false
+    "api": false,
+    "entities": [
+      "cell",
+      "tissue"
+    ],
+    "github": "https://github.com/scverse/squidpy",
+    "documentation": "https://squidpy.readthedocs.io/",
+    "last_checked": "2026-08-08",
+    "metadata_sources": [
+      "https://github.com/scverse/squidpy",
+      "https://squidpy.readthedocs.io/"
+    ]
   },
   {
     "id": "stagate",