alterlab-databases
claudeConnectors to scientific databases (PubMed, ChEMBL, UniProt, GEO, and more) (38 skills)
38 skills · 1 MCP server
Chemistry and drug discovery (RDKit, docking, ADMET, mass spec) (12 skills)
Plugin alterlab-cheminformatics from marketplace alterlab-academic-skills in AlterLab-IEU/AlterLab-Academic-Skills. Commands read from the repo's manifest — 6 days ago.
alterlab-datamolWraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, r
alterlab-deepchemRuns molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for property prediction (ADMET, toxicity, solubility) via traditional ML or graph neural networks. Use when running end-to-end molecular ML experi
alterlab-diffdockPredicts protein-ligand binding poses with DiffDock diffusion-based molecular docking from PDB structures and SMILES, producing pose confidence scores for virtual screening and structure-based drug design. Use when docking ligands into a protein, generating binding poses, or screening compounds agai
alterlab-matchmsComputes mass-spectral similarity and identifies compounds for metabolomics with matchms — comparing mass spectra, scoring similarity (cosine, modified cosine), and searching spectral libraries to annotate unknowns. Use when matching MS/MS spectra, identifying metabolites, or library searching; for
alterlab-medchemApplies medicinal-chemistry filters with the medchem library — drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, and molecular complexity metrics for compound prioritization and library cleanup. Use when filtering or triaging a compound library, flagging PAINS or reactive grou
alterlab-molecular-dynamicsRuns and analyzes molecular dynamics simulations with OpenMM and MDAnalysis — setting up protein and small-molecule systems, assigning force fields, running energy minimization and production MD, and analyzing trajectories (RMSD, RMSF, contact maps, free energy surfaces). Use when simulating protein
alterlab-molfeatFeaturizes molecules for machine learning with molfeat — ECFP/MACCS/MAP4 fingerprints, RDKit and Mordred physicochemical descriptors, pharmacophore and shape descriptors, and pretrained embeddings (ChemBERTa, ChemGPT, CheMeleon) exposed as scikit-learn transformers that convert SMILES into feature v
alterlab-primekgQueries the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biomedical relationships across genes, drugs, diseases, phenotypes, pathways, and biological processes. Use when exploring drug-disease or gene-disease links, building disease-centric knowledge subgraphs, or sourcing relations f
alterlab-pytdcLoads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark dataset, applying scaffol
alterlab-rdkitProvides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling. Use when custom sanitization, specialized fingerpr
alterlab-rowanBuilds and validates Rowan computational-chemistry jobs with the rowan-python API and previews the chemistry locally with no account — constructs 3D molecules and job payloads (pKa, geometry optimization, conformers, docking, AI cofolding), validates every submission's arguments offline, and runs a
alterlab-torchdrugBuilds PyTorch-native graph neural networks with TorchDrug for molecules and proteins, exposing custom GNN architectures, task/dataset abstractions, molecular generation, retrosynthesis planning, and knowledge-graph reasoning. Use when a project specifically needs TorchDrug's datasets and tasks — Ge
Connectors to scientific databases (PubMed, ChEMBL, UniProt, GEO, and more) (38 skills)
38 skills · 1 MCP server
Genomics, proteomics, and single-cell analysis (Scanpy, BioPython, pysam, ESM) (38 skills)
38 skills
Machine learning and statistics (scikit-learn, PyTorch, transformers, SHAP) (22 skills)
22 skills
Quantum computing, geospatial, materials, astronomy, and digital humanities (18 skills)
18 skills
Stage-gated social-science methods spine — orchestrator + 5 validity gates (design/identifying-assumption, measurement, sampling/power, reflexivity, inference) and 11 analysis modules (causal inference, complex-survey analysis, SEM/psychometrics, multilevel models, QCA, SNA, ABM, text-as-data, qualitative analysis, meta-analysis, missing data) (17 skills)
17 skills
Search, discovery, Zotero, qualitative methods, ethics, and open science (14 skills)
14 skills
Early access: ruflo's cockpit as a Claude Code mod (function hooks) and the one /ruflo command for every ruflo mod — overview with health alerts, swarm topology, claims flow, federation map, plugin health, learning pipeline, MetaHarness radar, memory, cost gauge, agent timeline, approvals and events; a command palette for confirm-gated actions through the ruflo CLI; auto-opens where it docks; no network by default
1 skill
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
26 skills · 4 commands · 3 agents · 1 MCP server
Evidence-backed BioPharma research workflows over Maven Bio's drug, trial, company, and deal knowledge graph. Skills for competitive pipelines, indication landscapes, asset profiles, deal and financing activity, and evidence synthesis grounded in FDA, SEC, clinical, and press sources. Requires a Maven Bio account.
16 skills · 1 agent · 1 MCP server
Query the KEGG bioinformatics database — pathways, genes, compounds, drugs, enzymes, diseases, reactions, and more via 34 read-only MCP tools. No API key required.
1 skill · 3 commands · 1 agent · 1 MCP server
Create narrated Mandarin math and science tutorial videos or interactive explainers from problem statements and images.
1 skill
Data Science Team — 10 agents: Cast, Feat, Fit, Score, Drift, Vect, Tune, Plot, Clean, Eval
This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.