universal-single-cell-annotator
A unified interface for annotating single-cell RNA-seq data using Marker Genes, Deep Learning (CellTypist), or LLMs.
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A unified interface for annotating single-cell RNA-seq data using Marker Genes, Deep Learning (CellTypist), or LLMs.
Classifies genetic variants according to ACMG (American College of Medical Genetics) guidelines.
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...
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...
Toolkit for performing deep research on complex topics using multiple AI research providers (OpenAI, Falcon, Perplexity, Consensus). Emphasizes explicit speed vs depth trade-offs.
Perform gene set enrichment analysis using AI research providers. Analyzes lists of genes to identify biological themes, pathways, and functional associations.
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...
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...
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...
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...
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...
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...
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...
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal pro...
Automated hypothesis generation and testing using large language models. Use this skill when generating scientific hypotheses from datasets, combining literature insights with empirical data, testing hypotheses...
Multi-specialist collaborative analysis to understand how features, functions, or components work
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical rese...
Extract and process energy data from BSEE (Gulf of Mexico) and SODIR (Norway) regulatory databases
Diagnose research quality and guide systematic query expansion. Use when starting research on any topic, when stuck in research, or when unsure if research is complete.
MemberSim generates realistic synthetic claims and payer data for testing claims processing systems, payment integrity, and benefits administration.
Generate realistic clinical trial synthetic data including study definitions, sites, subjects, visits, adverse events, efficacy assessments, and disposition. Use when user requests: clinical trial data, CDISC/S...
Execute clustering algorithms (K-means, DBSCAN, hierarchical) to identify data groups. Use when requesting "run clustering", "cluster analysis", or "group data points".
Split datasets into training, validation, and testing sets for ML model development. Use when requesting "split dataset", "train-test split", or "data partitioning".
Detect potential memory leaks and analyze memory usage patterns in code. Use when troubleshooting performance issues related to memory growth or identifying leak sources. Trigger with phrases like "detect memor...
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