Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Streamlines computational molecular biology tasks including sequence analysis, NCBI database integration, and structural protein modeling.
Processes and analyzes comprehensive physiological signals including ECG, EEG, and EDA for psychophysiology and clinical research.
Calculates and interprets key financial ratios from corporate data to provide deep investment and performance insights.
Infers gene regulatory networks (GRNs) from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Generates interactive, publication-quality data visualizations and dashboards using the Plotly Python library.
Infers large-scale gene regulatory networks from transcriptomics data using scalable machine learning algorithms like GRNBoost2 and GENIE3.
Calculates and interprets comprehensive financial ratios from statement data to facilitate deep investment analysis and performance benchmarking.
Calculates and interprets key financial ratios from corporate statements to streamline investment analysis and performance benchmarking.
Searches the arXiv preprint repository for scholarly articles in computer science, physics, mathematics, and quantitative biology.
Calculates and interprets comprehensive financial ratios from balance sheets and income statements to provide actionable investment insights.
Infers gene regulatory networks from transcriptomics data using scalable machine learning algorithms like GRNBoost2 and GENIE3.
Access over 40 bioinformatics web services and databases including UniProt, KEGG, and ChEMBL through a unified Python interface.
Implements ultra-high-performance semantic vector search and document retrieval for Claude-powered RAG systems and intelligent knowledge bases.
Integrates high-performance semantic vector search and HNSW indexing for intelligent document retrieval and RAG systems.
Implement high-performance semantic search and vector storage for intelligent document retrieval and RAG systems.
Implement high-performance semantic vector search and intelligent document retrieval using AgentDB optimized HNSW indexing and quantization.
Infers gene regulatory networks from transcriptomics data using scalable gradient boosting and random forest algorithms.
Implements high-performance persistent memory and context management for AI agents using AgentDB.
Processes and generates audio, video, images, and complex documents using Google Gemini's advanced multimodal API capabilities.
Accesses and searches the bioRxiv preprint server to retrieve life sciences research metadata and download full-text PDFs.
Queries and interprets NCBI ClinVar data to evaluate human genetic variant pathogenicity and clinical significance for genomic medicine.
Automates protein sequence optimization and experimental validation through cloud-based laboratory testing.
Accesses and integrates data from over 40 bioinformatics web services and databases using a unified Python API.
Automates life sciences R&D workflows by integrating Benchling's registry, inventory, and electronic lab notebook via API and Python SDK.
Standardizes and automates molecular featurization to convert chemical structures into machine-learning-ready numerical representations.
Develops, deploys, and manages genomics pipelines and biomedical data on the DNAnexus cloud platform.
Automates laboratory data management and life sciences R&D workflows by integrating with the Benchling platform via Python SDK and REST API.
Generates sophisticated financial models including DCF analysis, Monte Carlo simulations, and sensitivity testing for investment decision-making.
Manages AI model configurations, pricing, and capabilities within backend registries for LLM-powered applications.
Queries the ClinicalTrials.gov API v2 to search for trials, analyze research trends, and extract detailed study data.
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