data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Automates scientific hypothesis generation and testing from tabular datasets using LLMs and literature integration.
Queries and retrieves comprehensive gene information from NCBI databases for genomic research and functional analysis.
Accesses and analyzes functional genomics data from the NCBI Gene Expression Omnibus (GEO) repository.
Analyzes whole-slide pathology images and multiparametric imaging data using a comprehensive computational pathology toolkit.
Accelerates drug discovery and molecular research using graph neural networks and PyTorch-based machine learning.
Infers gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Performs differential gene expression analysis on bulk RNA-seq data using the DESeq2 framework within Python.
Automates computational molecular biology tasks including sequence manipulation, NCBI database queries, and structural analysis.
Analyzes single-cell omics data using deep generative models for batch correction, multimodal integration, and differential expression.
Automates the generation and testing of scientific hypotheses by synthesizing empirical data and existing research literature.
Processes and visualizes massive tabular datasets exceeding available RAM using high-performance out-of-core DataFrame operations.
Performs advanced astronomical data analysis, coordinate transformations, and cosmological calculations using the core Astropy Python library.
Processes and analyzes mass spectrometry data through spectral similarity, metadata harmonization, and automated workflows.
Accesses and manages somatic mutation data from the COSMIC database for cancer research and precision oncology.
Streamlines molecular machine learning and drug discovery by providing specialized featurizers, graph neural networks, and chemical benchmark datasets.
Queries and analyzes large-scale single-cell genomics data from the CZ CELLxGENE Census repository.
Creates publication-quality statistical graphics and complex multi-panel data visualizations with minimal Python code.
Create publication-quality static, animated, and interactive visualizations using Python's foundational plotting library.
Processes and manipulates DICOM medical imaging files for healthcare data analysis and clinical workflow integration.
Provides a unified interface for rapid bioinformatics queries, genomic sequence analysis, and protein structure prediction across 20+ scientific databases.
Accesses and queries the Human Metabolome Database (HMDB) for detailed metabolite information, chemical properties, and clinical biomarkers.
Queries the openFDA API to retrieve comprehensive data on drugs, medical devices, food safety, and regulatory submissions.
Implements and optimizes reinforcement learning workflows using the Stable Baselines3 PyTorch library.
Queries the Ensembl REST API for genomic data, sequence retrieval, variant analysis, and comparative genomics across 250+ species.
Builds process-based discrete-event simulations in Python to model complex systems like manufacturing, logistics, and network traffic.
Simplifies high-performance genomic interval analysis and machine learning preprocessing using Rust-powered toolsets.
Solves complex single and multi-objective optimization problems using evolutionary algorithms and Pareto front analysis.
Processes and analyzes high-throughput sequencing data including SAM, BAM, VCF, and FASTA files using a Pythonic interface to htslib.
Performs exact symbolic mathematical computations including algebra, calculus, and equation solving using the SymPy Python library.
Manages biological datasets with automated lineage tracking, ontology-based validation, and FAIR data principles through a unified Python API.
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