Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Accesses over 600 scientific tools and databases for bioinformatics, drug discovery, and computational biology research.
Accesses over 40 bioinformatics web services and databases through a unified Python interface for biological data retrieval and analysis.
Infers gene regulatory networks from transcriptomics data using scalable GRNBoost2 and GENIE3 algorithms.
Simplifies complex molecular informatics workflows by providing a Pythonic interface for RDKit with sensible defaults and built-in parallelization.
Simplifies molecular cheminformatics and drug discovery workflows with a Pythonic abstraction layer over RDKit.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic interface for RDKit.
Builds discrete-event simulation models in Python to analyze complex systems involving queues, resources, and time-based processes.
Develops, tests, and deploys machine learning models for clinical healthcare data using standardized pipelines and specialized medical architectures.
Integrates managed vector databases into AI applications for production-grade RAG, semantic search, and recommendation systems.
Analyzes high-throughput sequencing data to perform quality control, normalization, and publication-quality visualization for NGS experiments.
Searches the arXiv repository to retrieve and summarize the latest scholarly articles in STEM fields.
Simulates and analyzes genome-scale metabolic models using constraint-based reconstruction and analysis (COBRA) techniques.
Searches the arXiv preprint repository for scholarly articles in computer science, physics, mathematics, and quantitative biology.
Builds process-based discrete-event simulations in Python for modeling complex systems like logistics, manufacturing, and networks.
Executes complex autonomous research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.
Accesses the European Nucleotide Archive (ENA) to retrieve genomic sequences, raw reads, and metadata for bioinformatics pipelines.
Builds, simulates, and executes quantum circuits using Google’s open-source framework for NISQ-era quantum computers.
Analyzes Excel spreadsheets, generates pivot tables, and creates data visualizations using Python libraries like pandas and openpyxl.
Implement high-performance semantic vector search and intelligent document retrieval using AgentDB optimized HNSW indexing and quantization.
Queries and analyzes clinical trial data from the official ClinicalTrials.gov API v2 for research and patient matching.
Calculates and interprets key financial ratios from company statements to facilitate investment analysis and performance benchmarking.
Processes and generates audio, video, images, and complex documents using Google Gemini's advanced multimodal API capabilities.
Automates high-throughput sequencing data analysis, from BAM file processing and quality control to publication-ready visualizations like heatmaps and profile plots.
Integrates high-performance semantic vector search and HNSW indexing for intelligent document retrieval and RAG systems.
Automates protein sequence optimization and experimental validation through cloud-based laboratory testing.
Implements high-performance persistent memory and context management for AI agents using AgentDB.
Implements ultra-high-performance semantic vector search and document retrieval for Claude-powered RAG systems and intelligent knowledge bases.
Infers gene regulatory networks from transcriptomics data using scalable machine learning algorithms like GRNBoost2 and GENIE3.
Implement high-performance semantic search and vector storage for intelligent document retrieval and RAG systems.
Performs constraint-based reconstruction and analysis of metabolic models for systems biology and metabolic engineering.
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