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Bioinformatics

Tools for computational analysis of biological data, including genomics, proteomics, and other molecular biology data. Enables access to bioinformatics pipelines, algorithms, and databases.

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    Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.
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    Apache 2.0
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    Enables editing and querying of Gene Ontology Causal Activity Models (GO-CAMs) through the Barista API. Supports model creation, individual and fact management, evidence addition, and causal pathway construction for biological knowledge representation.
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    BSD 3-Clause
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    Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.
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    MIT
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    ▎ Provides 32 tools for plant-genomics locus lookup across 11 free public backends (Ensembl Plants, Phytozome, UniProtKB, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, BAR). Takes a TAIR-style locus plus optional organism and returns gene metadata, functional/pathway annotation, interactions, co-expression, and literature — in single-locus, batch, and cross-source synthesis.
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    MIT
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    Enables AI-assisted molecular biology experiment design with tools for qPCR primer design, cloning strategy optimization, TaqMan probe design, and multiplex compatibility analysis.
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    Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.
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    Enables molecular design and simulation through 45 chemistry tools including pKa calculations, geometry optimization, conformer searches, docking, protein cofolding, and ADMET predictions powered by Rowan's computational chemistry platform.
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    MIT
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    Enables LLM agents to query the CZ CELLxGENE Census single-cell atlas with ontology-aware filters, cost caps, and full provenance, allowing natural language questions about cell types, tissues, and gene expression.
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    MIT
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    Enables bioinformatics analysis through natural language conversations with Claude Desktop, automatically generating and executing Python scripts to produce HTML reports and visualizations.
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    MIT
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    Enables searching and downloading Gene Expression Omnibus (GEO) data from NCBI, including datasets, series, samples, platforms, and profiles, through natural language queries.
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    Provides LLMs with structured access to critical biomedical databases including PubTator3 (PubMed/PMC), ClinicalTrials.gov, and MyVariant.info through the Model Context Protocol.
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    A Model Context Protocol server that provides tools for interacting with the STRING database to analyze protein-protein interaction networks and functional enrichment. It enables users to map protein identifiers, retrieve interaction data, and generate biological network visualizations through natural language interfaces.
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    Enables AI agents and applications to search, retrieve, and analyze chemical compounds, substances, and bioassays from PubChem's vast chemical information database through comprehensive tools for chemical research and discovery.
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    Provides comprehensive BioPython capabilities for biological sequence analysis, alignment, database access (GenBank, UniProt, PubMed), protein structure analysis, and phylogenetics through a Model Context Protocol interface for AI-assisted bioinformatics workflows.
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    MIT
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    Provides a programmatic interface to the Genome Aggregation Database (gnomAD) API across versions v2.1.1, v3.1.2, and v4.1.0. It enables users to query gene metadata, variant information, population frequencies, and ClinVar data through a unified schema.
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    Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.
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