GitHub
structural-biology
Structural biology analysis including protein structure validation, AlphaFold interpretation, and structural comparisons
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Skills IA tools scientific computing
Découvrez les skills tools scientific computing, comparez leurs dépôts et consultez leurs instructions.
Catégories: tools scientific computing
tools scientific computing Effacer les filtres
Explorer
GitHub
metabolomics
Metabolomics-specific analysis strategies and domain knowledge
☆ 10Voir le skill
GitHub
genomics
Genomics and transcriptomics analysis strategies
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GitHub
memory-documentary
Generate evidence-based documentary reports by searching across all 4 memory systems (Claude-Mem, Forgetful, Serena, DeepWiki), .agents/ artifacts, and GitHub issues. Produces investigative journalism-style ana...
GitHub
ngspice-circuit-simulator
Electronic circuit simulation and SPICE analysis via ngspice MCP tool
GitHub
research-web
Deep web research with parallel investigators, multi-wave exploration, and structured synthesis. Spawns multiple web-researcher agents to explore different facets of a topic simultaneously, launches additional...
GitHub
clinical-trial-matcher
Matches patient profiles to open clinical trials using vector similarity and inclusion/exclusion criteria. Use when a user provides patient data and asks for relevant trials.
GitHub
regulatory-drafter
Drafts regulatory documents (FDA, EMA) with audit trails and specific "Thinking Block" reasoning. Use for high-stakes compliance writing.
GitHub
protein-structure-prediction
Predicts 3D protein structures from amino acid sequences using ESMFold or AlphaFold3 (mock).
GitHub
crispr-designer
Designs guide RNA (gRNA) sequences for CRISPR-Cas9 editing, including off-target analysis. Use when a user needs to edit a gene or asks for gRNA sequences.
GitHub
chemcrow-tools
A production-grade cheminformatics toolkit for analyzing molecular properties, toxicity, and synthetic accessibility.
GitHub
universal-single-cell-annotator
A unified interface for annotating single-cell RNA-seq data using Marker Genes, Deep Learning (CellTypist), or LLMs.
GitHub
variant-interpretation-acmg
Classifies genetic variants according to ACMG (American College of Medical Genetics) guidelines.
GitHub
rd-management
R&D management expertise for R&D portfolio management, technology roadmapping, research methodology, patent strategy, lab management, academic partnerships, and regulatory pathways. Use when managing research p...
GitHub
research
Comprehensive research, analysis, and content extraction system. Multi-source parallel research using available researcher agents. Deep content analysis with extended thinking. Intelligent retrieval for difficu...
GitHub
run-deep-research
Toolkit for performing deep research on complex topics using multiple AI research providers (OpenAI, Falcon, Perplexity, Consensus). Emphasizes explicit speed vs depth trade-offs.
GitHub
gene-set-enrichment
Perform gene set enrichment analysis using AI research providers. Analyzes lists of genes to identify biological themes, pathways, and functional associations.
GitHub
data-analyzer
Analyzes datasets to extract insights, identify patterns, and create visualizations. This skill should be used when users want to explore data, perform statistical analysis, identify trends, or visualize patter...
GitHub
hepdata
Use when the user mentions 'HEPData' or asks to find experimental data, download data tables from HEP papers, get digitized plots, or retrieve cross-section measurements. HEPData contains data points behind fig...
GitHub
astrophysics-analysis
This skill should be used when the user asks to "analyze astronomical data", "process FITS files", "create sky maps", "work with cosmological simulations", "fit spectral data", "calculate redshifts", "analyze l...
GitHub
denario
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing re...
GitHub
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), buil...
GitHub
gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment...
GitHub
exploratory-data-analysis
Analyze datasets to discover patterns, anomalies, and relationships. Use when exploring data files, generating statistical summaries, checking data quality, or creating visualizations. Supports CSV, Excel, JSON...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.