bioservices-multi-database
BioServices Multi-Database Access
Overview
BioServices provides a unified Python interface to 40+ bioinformatics web services including UniProt, KEGG, ChEMBL, ChEBI, PubChem, UniChem, PSICQUIC, QuickGO, and BLAST. Each service is accessed through a consistent object-oriented API with built-in caching, rate limiting, and output format handling.
When to Use
- Querying protein information from UniProt (search, retrieve, ID mapping)
- Discovering KEGG pathways and extracting gene/interaction networks
- Cross-referencing compounds across ChEMBL, ChEBI, PubChem, and KEGG
- Running BLAST sequence similarity searches against UniProtKB
- Mapping identifiers between biological databases (UniProt, Ensembl, KEGG, RefSeq, PDB)
- Retrieving Gene Ontology annotations via QuickGO
- Finding protein-protein interactions via PSICQUIC (IntAct, MINT, BioGRID)
- Batch converting thousands of biological identifiers with error handling
- For single-database deep queries → use gget (Ensembl), pubchempy (PubChem), or chembl-database skill
- For pathway visualization → use pathway analysis tools (Cytoscape, NetworkX) after retrieving data with bioservices
More from jaechang-hits/sciagent-skills
scientific-brainstorming
Structured ideation methods: SCAMPER, Six Thinking Hats, Morphological Analysis, TRIZ, Biomimicry, plus more. Decision framework for picking methods by challenge type (stuck, improving, systematic exploration, contradiction). Use when generating research ideas or exploring interdisciplinary connections.
12snakemake-workflow-engine
Python-based workflow management system for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake automatically determines the execution order and parallelism. Supports local, SLURM, LSF, AWS, and Google Cloud execution via profiles; per-rule conda/Singularity environments. Use for bioinformatics NGS pipelines, ML training workflows, and any multi-step file-processing analysis. Use Nextflow instead for Groovy-based dataflow pipelines or when nf-core ecosystem integration is required.
11esm-protein-language-model
Protein language models (ESM3, ESM C) for sequence generation, structure prediction, inverse folding, and protein embeddings. Use when designing novel proteins, extracting sequence representations for downstream ML, or predicting structure from sequence. Local GPU or EvolutionaryScale Forge cloud API. For traditional structure prediction use AlphaFold; for small-molecule cheminformatics use RDKit.
11biopython-sequence-analysis
Biopython sequence analysis: parse FASTA/FASTQ/GenBank/GFF (SeqIO), NCBI Entrez (esearch/efetch/elink), remote/local BLAST, pairwise/MSA alignment (PairwiseAligner, MUSCLE/ClustalW), phylogenetic trees (Phylo). Use for gene family studies, phylogenomics, comparative genomics, NCBI pipelines. For PCR/restriction/cloning use biopython-molecular-biology; for SAM/BAM use pysam.
11shap-model-explainability
>-
11archs4-database
Query ARCHS4 REST API for uniformly processed RNA-seq expression, tissue patterns, co-expression across 1M+ human/mouse samples. Retrieve z-scores, co-expressed genes, samples by metadata, HDF5 matrices. For variant population genetics use gnomad-database; for pathway enrichment use gget-genomic-databases (Enrichr).
11