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Query the ChEMBL database for bioactive molecules, targets, bioactivities, and approved drugs; use this when you need to filter by physicochemical properties (e.g., MW, LogP), chemical structure (SMILES), or retrieve drug mechanism information.
Automatically identify Western Blot gel bands, perform densitometric analysis, and calculate normalized values relative to loading controls.
Analyze data with `toxicity-structure-alert` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
Analyze data with `smiles-de-salter` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
Cloud-based quantum chemistry platform providing a Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformational search, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2). Suitable for tasks involving quantum chemistry calculations, molecular property prediction, DFT or semi-empirical methods, neural network potentials (AIMNet2), protein-ligand binding prediction, or automated computational chemistry pipelines. Provides cloud computing resources without local installation.
Automated bias assessment for diagnostic accuracy studies using QUADAS-C criteria. Requires full text input.
Automates Risk of Bias 2 (ROB2) assessment for RCT papers by analyzing text against specific domains and synthesizing a report. Use when you need to assess the quality of a clinical trial paper or evaluate risk of bias.
Use preclinical pkpd analyst for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
Clinical research outcome extraction for meta-analysis. Use when users need to extract outcome measures (binary, continuous, or survival data) from clinical research papers for systematic review and meta-analysis. Handles both database lookup by PMID and real-time LLM extraction.
Filter compound libraries based on Lipinski's Rule of Five for drug-likeness.
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking.
Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool. Use when Claude needs to assess the quality, risk of bias, or applicability of diagnostic accuracy studies (e.g., "Assess this paper using QUADAS-2").
Process CRISPR screening data to identify essential genes and hit candidates. Performs quality control, statistical analysis (RRA), and hit calling for pooled CRISPR screens including viability screens and drug resistance/sensitivity studies.
Unified Python access to 40+ bioinformatics web services; use when you need to query multiple databases (e.g., UniProt/KEGG/ChEMBL/Reactome) with one consistent API in a single workflow, especially for cross-database analysis and identifier mapping.
Analyze data with `adme-property-predictor` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
Generate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.
Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be explicitly marked as "To be supplemented/Not provided".
Generate ARRIVE 2.0 compliant animal research protocols with structured experimental design, sample size calculations, and reporting checklists. Ensures transparency, reproducibility, and ethical compliance in in vivo studies.
