Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Performs comprehensive differential gene expression analysis from bulk RNA-seq count data using the Python implementation of DESeq2.
Queries the NCBI ClinVar database to interpret genetic variant pathogenicity and annotate genomic data for research and medicine.
Enables advanced materials science research through crystal structure manipulation, thermodynamic analysis, and Materials Project database integration.
Simulates high-performance computational fluid dynamics using pseudospectral methods and Python-based analysis.
Processes and analyzes high-performance genomic interval data for computational biology and machine learning applications.
Parses and manipulates Flow Cytometry Standard (FCS) files, converting biological data into NumPy arrays and CSV formats for scientific analysis.
Manipulates, analyzes, and visualizes phylogenetic and hierarchical trees for genomic research and evolutionary biology.
Performs advanced molecular analysis, manipulation, and chemical informatics tasks using the RDKit toolkit.
Builds, fits, and validates robust Bayesian models using PyMC's modern probabilistic programming interface.
Facilitates advanced mass spectrometry data analysis using the Python interface to the OpenMS library for proteomics and metabolomics.
Integrates the Reactome database to perform pathway enrichment, gene-pathway mapping, and molecular interaction analysis for systems biology.
Processes and analyzes mass spectrometry data using the Matchms library for spectral similarity and metadata harmonization.
Accesses AI-ready Therapeutics Data Commons (TDC) datasets and benchmarks for drug discovery and pharmaceutical machine learning.
Facilitates automated protein testing and validation through the Adaptyv cloud laboratory platform.
Converts complex documents, images, and multimedia files into clean, token-efficient Markdown for optimized LLM processing.
Integrates NCBI Gene data access into Claude for querying sequences, functional annotations, and genomic metadata.
Enables programmatic access to the RCSB Protein Data Bank for searching, retrieving, and analyzing 3D structures of biological macromolecules.
Builds, optimizes, and executes quantum circuits and algorithms on simulators or real hardware using the Qiskit framework.
Develops and trains Graph Neural Networks (GNNs) for node classification, link prediction, and geometric deep learning tasks.
Provides unified, rapid access to over 20 genomic databases and bioinformatics analysis tools for DNA and protein research.
Analyzes protein-protein interaction networks and performs functional enrichment using the STRING database's 20 billion interactions.
Formulates testable, evidence-based scientific hypotheses and experimental designs from observations or literature synthesis.
Solves complex single and multi-objective optimization problems using evolutionary algorithms and Pareto front analysis.
Builds and deploys serverless bioinformatics pipelines using the Latch SDK and cloud infrastructure.
Runs Python code in the cloud with serverless containers, autoscaling GPUs, and minimal infrastructure management.
Accesses the NIH Metabolomics Workbench to query over 4,200 studies, standardize metabolite nomenclature, and perform mass spectrometry searches.
Accesses and analyzes over 61 million standardized single-cell genomics records from the CZ CELLxGENE Census.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variant associations, study metadata, and genomic summary statistics.
Implements comprehensive machine learning workflows using scikit-learn for classification, regression, clustering, and data preprocessing.
Accesses over 230 million purchasable chemical compounds for virtual screening, drug discovery, and molecular docking studies.
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