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Updated skill descrtipotions to resolve possible conflicts in their use
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name: kegg-database
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name: kegg-database
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description: "Query KEGG REST API for pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion, compound structures, for systems biology and enrichment analysis."
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description: "Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control."
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# KEGG Database
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# KEGG Database
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name: pubmed-database
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name: pubmed-database
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description: "Search PubMed biomedical literature. Advanced queries with Boolean/MeSH/field tags, E-utilities API access, batch processing, citation management, for literature review and systematic analysis."
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description: "Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations."
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# PubMed Database
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# PubMed Database
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name: uniprot-database
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name: uniprot-database
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description: "Query UniProt protein database REST API. Search proteins by name/gene/accession, retrieve sequences (FASTA), annotations, ID mapping, Swiss-Prot/TrEMBL, GO terms, for protein analysis."
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description: "Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control."
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# UniProt Database
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# UniProt Database
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name: biopython
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name: biopython
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description: "Toolkit for computational molecular biology. Manipulate sequences, parse biological file formats (FASTA, GenBank, FASTQ, PDB), access NCBI databases, run BLAST, analyze structures, build phylogenetic trees, for bioinformatics workflows."
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description: "Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database."
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# Biopython: Computational Molecular Biology in Python
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# Biopython: Computational Molecular Biology in Python
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name: bioservices
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name: bioservices
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description: "Access 40+ bio web services (UniProt, KEGG, ChEMBL, PubChem, BLAST, QuickGO, Reactome). Retrieve data, map IDs, pathway analysis, for multi-database integration workflows."
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description: "Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database)."
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# BioServices
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# BioServices
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name: datamol
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name: datamol
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description: "Pythonic RDKit wrapper for cheminformatics. SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing, for drug discovery workflows."
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description: "Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly."
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# Datamol Cheminformatics Skill
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# Datamol Cheminformatics Skill
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name: gget
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name: gget
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description: "Bioinformatics query toolkit. Gene info (Ensembl/UniProt), BLAST, AlphaFold, ARCHS4 expression, Enrichr, OpenTargets, COSMIC, genome downloads, CLI/Python, for rapid database queries."
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description: "CLI/Python toolkit for rapid bioinformatics queries. Preferred for quick BLAST searches. Access to 20+ databases: gene info (Ensembl/UniProt), AlphaFold, ARCHS4, Enrichr, OpenTargets, COSMIC, genome downloads. For advanced BLAST/batch processing, use biopython. For multi-database integration, use bioservices."
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# gget
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# gget
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name: rdkit
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name: rdkit
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description: "Cheminformatics toolkit for molecules. Parse SMILES/SDF, calculate descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, for drug discovery."
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description: "Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms."
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# RDKit Cheminformatics Toolkit
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# RDKit Cheminformatics Toolkit
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