Discover Agent Skills for data science & ml. Browse 53skills for Claude, ChatGPT & Codex.
Streamlines high-throughput sequencing data analysis by providing tools for BAM processing, quality control, and publication-quality genomic visualizations.
Performs complex biological computation, sequence analysis, and bioinformatics workflows using the Biopython library.
Processes and analyzes high-performance genomic interval data for computational biology and machine learning applications.
Simulates and analyzes quantum mechanical systems using the QuTiP toolbox for both closed and open system dynamics.
Access and analyze comprehensive FDA regulatory data, including drug safety, medical device clearances, and food recalls through the openFDA API.
Streamlines access to over 40 bioinformatics web services and databases for biological data retrieval and cross-database analysis.
Enables parallel and distributed computing in Python to scale data processing beyond memory limits.
Builds, optimizes, and executes quantum circuits and algorithms on simulators or real hardware using the Qiskit framework.
Generates publication-quality statistical graphics and complex data visualizations using the Seaborn Python library.
Builds, analyzes, and visualizes complex networks and graph data structures using the comprehensive NetworkX library for Python.
Runs Python code in the cloud with serverless containers, autoscaling GPUs, and minimal infrastructure management.
Empowers Claude with expert capabilities for manipulating, analyzing, and visualizing geospatial vector data using Python.
Accesses AI-ready Therapeutics Data Commons (TDC) datasets and benchmarks for drug discovery and pharmaceutical machine learning.
Provides unified, rapid access to over 20 genomic databases and bioinformatics analysis tools for DNA and protein research.
Parses and manipulates Flow Cytometry Standard (FCS) files, converting biological data into NumPy arrays and CSV formats for scientific analysis.
Solves complex single and multi-objective optimization problems using evolutionary algorithms and Pareto front analysis.
Optimizes data processing workflows with high-performance Polars expressions, lazy evaluation, and efficient DataFrame manipulations.
Facilitates advanced mass spectrometry data analysis using the Python interface to the OpenMS library for proteomics and metabolomics.
Applies medicinal chemistry rules and structural filters to prioritize drug-like compounds in molecular discovery workflows.
Manipulates genomic datasets including SAM, BAM, VCF, and FASTA files through a Pythonic interface to htslib.
Manages large-scale N-dimensional arrays with chunked storage, compression, and cloud-native parallel I/O.
Implements comprehensive machine learning workflows using scikit-learn for classification, regression, clustering, and data preprocessing.
Accesses the Human Metabolome Database (HMDB) to retrieve comprehensive data on small molecule metabolites, clinical biomarkers, and biochemical pathways.
Facilitates direct REST API access to the KEGG database for biological pathway analysis, gene mapping, and molecular interaction research.
Facilitates collaborative research ideation to generate hypotheses, challenge assumptions, and explore interdisciplinary connections for creative scientific problem-solving.
Accesses and manages NCBI Gene Expression Omnibus (GEO) data for transcriptomics and functional genomics research.
Access and retrieve comprehensive nucleotide sequence data and metadata from the European Nucleotide Archive (ENA) for bioinformatics pipelines.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variant associations, study metadata, and genomic summary statistics.
Accesses over 230 million purchasable chemical compounds for virtual screening, drug discovery, and molecular docking studies.
Queries the NCBI ClinVar database to interpret genetic variant pathogenicity and annotate genomic data for research and medicine.
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