发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Analyzes complex dynamical systems and strange attractors with sensitive dependence on initial conditions.
Calculates time averages of observables along trajectories to analyze qualitative behavior and stability in dynamical systems.
Systematically evaluates research papers and scholarly work using the peer-reviewed ScholarEval framework for soundness and contribution.
Accesses the NIH Metabolomics Workbench to query metabolite structures, study metadata, and standardized chemical nomenclature for biomarker discovery.
Facilitates collaborative research ideation through hypothesis generation, interdisciplinary exploration, and systematic challenge of scientific assumptions.
Accesses and analyzes over 240 million scholarly works, authors, and institutions through the OpenAlex API for comprehensive academic research.
Automates genomics pipeline development and data management on the DNAnexus cloud platform using the dxpy Python SDK.
Automates laboratory workflows by generating and optimizing Python protocols for Opentrons Flex and OT-2 liquid handling robots.
Infers large-scale gene regulatory networks from transcriptomics data using scalable machine learning algorithms like GRNBoost2 and GENIE3.
Conducts rigorous statistical hypothesis tests, regression models, and Bayesian analyses with APA-style reporting.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank, including drug properties, interactions, and chemical structures.
Evaluates research rigor, methodology, and statistical validity to critically analyze scientific claims and evidence quality.
Simplifies mass spectrometry data processing and analysis within Python-based proteomics and metabolomics workflows.
Develops and deploys specialized machine learning models for healthcare using clinical data and medical coding systems.
Queries the Reactome REST API for pathway analysis, gene enrichment, and molecular interaction mapping in systems biology studies.
Simulates complex fluid dynamics using high-performance Python-based pseudospectral methods for scientific research.
Processes mass spectrometry data to calculate spectral similarities, harmonize metadata, and identify chemical compounds.
Facilitates advanced materials analysis, crystal structure manipulation, and Materials Project database integration for computational science workflows.
Accesses and analyzes comprehensive vertebrate genomic data from the Ensembl REST API for over 250 species.
Accesses and analyzes over 200 million AI-predicted protein structures from the AlphaFold DB for drug discovery and structural biology research.
Builds, fits, and validates Bayesian statistical models using PyMC and ArviZ for probabilistic programming.
Processes medical imaging data in the DICOM standard format for healthcare applications and radiology workflows.
Searches and retrieves metadata and full-text PDFs from the bioRxiv preprint server for life sciences research discovery.
Analyzes and processes high-performance genomic interval data for computational biology and machine learning workflows.
Simplifies complex time series machine learning tasks including forecasting, classification, and anomaly detection using a scikit-learn compatible toolkit.
Generates publication-quality statistical graphics and exploratory data visualizations using the Seaborn Python library.
Accesses and queries the world's largest chemical database for compound information, molecular properties, and bioactivity data.
Automates electronic lab notebook workflows by managing entries, attachments, and backups through the LabArchives REST API.
Implements Darwin Gödel Machine patterns to enable AI agents to autonomously improve their code and capabilities through open-ended evolution.
Provides programmatic access to standardized single-cell genomics data for large-scale analysis and machine learning.
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