data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Builds complex discrete-event simulations in Python to model systems with processes, queues, and shared resources.
Builds process-based discrete-event simulations in Python to model complex systems, resource contention, and queue behaviors.
Performs constraint-based reconstruction and analysis of metabolic models for systems biology and metabolic engineering.
Applies machine learning to chemistry, biology, and materials science for drug discovery and molecular property prediction.
Applies advanced machine learning to chemistry, biology, and materials science for drug discovery and molecular property prediction.
Simulates complex fluid dynamics using high-performance Python pseudospectral solvers for Navier-Stokes and geophysical flows.
Simulates high-performance computational fluid dynamics using Python-based pseudospectral methods and MPI support.
Processes and analyzes complex physiological signals including ECG, EEG, and EDA for research and clinical applications.
Integrates Pinecone's serverless vector database to power production-grade RAG, semantic search, and recommendation systems.
Automates the creation, editing, and sophisticated analysis of Excel spreadsheets with a focus on financial modeling standards and formula integrity.
Analyzes single-cell omics data using deep generative models for transcriptomics, chromatin accessibility, and spatial analysis.
Streamlines the creation and management of large-scale Gemini batch prediction jobs on Google Cloud Vertex AI.
Predicts high-accuracy 3D protein-ligand binding poses using diffusion-based deep learning models.
Queries and analyzes SEC filings, XBRL financials, and company data for streamlined financial research and auditing.
Processes gigapixel whole slide images for digital pathology, automating tissue detection and tile extraction for deep learning pipelines.
Infers gene regulatory networks (GRNs) from gene expression data using scalable GRNBoost2 and GENIE3 algorithms.
Infers gene regulatory networks from expression data using scalable algorithms like GRNBoost2 and GENIE3.
Accesses and retrieves gene expression data from the NCBI Gene Expression Omnibus (GEO) for transcriptomics and functional genomics analysis.
Processes, analyzes, and generates multimedia content including audio, video, images, and complex documents using the Google Gemini API.
Accesses and integrates over 40 bioinformatics web services and databases including UniProt, KEGG, and ChEMBL through a unified Python interface.
Accesses and integrates data from over 40 major bioinformatics web services and databases using a unified Python API.
Accesses and analyzes NCBI Gene Expression Omnibus (GEO) datasets for transcriptomics and genomics research.
Analyzes Excel spreadsheets, generates pivot tables, and automates complex data reporting workflows.
Accesses and retrieves nucleotide sequence data, raw reads, and genome assemblies from the European Nucleotide Archive (ENA).
Automates the generation and testing of scientific hypotheses by integrating empirical data with existing literature insights.
Queries the NCBI Gene database to retrieve comprehensive genetic information, sequences, and functional annotations.
Queries the Ensembl REST API to retrieve genomic annotations, sequences, and variant data for over 250 vertebrate species.
Implements comprehensive evaluation strategies for Large Language Models using automated metrics, human feedback, and comparative benchmarking.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and financial modeling standards.
Automates the end-to-end scientific research pipeline from initial data analysis and hypothesis generation to publishing-ready LaTeX manuscripts.
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