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。
Accesses the European Nucleotide Archive (ENA) to retrieve genomic sequences, raw reads, and metadata for bioinformatics pipelines.
Predicts high-accuracy 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug design.
Processes and analyzes high-throughput sequencing data to generate publication-quality visualizations and quality control metrics for genomics research.
Infers gene regulatory networks (GRNs) from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Automates complex scientific research workflows and tool discovery across bioinformatics, genomics, and drug discovery domains.
Builds end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.
Simplifies high-performance computational fluid dynamics (CFD) simulations and analysis using Python and pseudospectral methods.
Streamlines astronomical data analysis and astrophysical calculations using the core Astropy Python library.
Builds end-to-end MLOps pipelines for data preparation, model training, validation, and production deployment.
Builds robust Retrieval-Augmented Generation systems using vector databases and semantic search to ground LLM responses in proprietary data.
Accesses the Human Metabolome Database to retrieve metabolite properties, clinical biomarker data, and spectral information for metabolomics research.
Builds high-performance Retrieval-Augmented Generation systems using vector databases, semantic search, and advanced retrieval patterns.
Transforms, cleans, and reshapes complex datasets locally using industry-standard Python libraries like pandas and numpy.
Implements high-performance Retrieval-Augmented Generation systems for LLM applications using vector databases and semantic search.
Generates interactive, publication-quality scientific and statistical visualizations using the Plotly Python library.
Accesses and integrates data from over 40 bioinformatics web services and databases using a unified Python API.
Develops and deploys specialized machine learning models for healthcare using clinical datasets and medical coding systems.
Analyzes Excel spreadsheets, generates pivot tables, and creates data visualizations using Python libraries like pandas and openpyxl.
Automates Excel spreadsheet manipulation, data cleaning, and visualization using Python's Pandas and OpenPyXL libraries.
Retrieves genomic, transcriptomic, and proteomic data from 20+ bioinformatics databases using a unified interface.
Accesses and analyzes the Human Metabolome Database to retrieve detailed metabolite information, chemical properties, and clinical biomarkers.
Integrates the open-source embedding database to build AI-native applications with semantic search and retrieval-augmented generation (RAG) capabilities.
Simplifies PDF manipulation, data extraction, and document generation using industry-standard Python libraries and CLI tools.
Processes and analyzes high-performance genomic interval data using Rust-powered algorithms and Python bindings.
Queries the NCBI Gene database to retrieve comprehensive genetic information, metadata, and sequences for annotation and functional analysis.
Processes and generates multimedia content including audio, video, images, and documents using the Google Gemini API.
Queries NCBI Gene databases to retrieve comprehensive genomic data, including sequences, annotations, and functional pathways.
Automates Excel spreadsheet analysis, data manipulation, and visual reporting using Python-based data science libraries.
Accesses and analyzes the Human Metabolome Database to retrieve metabolite data, chemical properties, and clinical biomarkers.
Accesses and retrieves genomic data from the European Nucleotide Archive (ENA) via REST APIs and FTP for bioinformatics pipelines.
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