time-series-analysis
Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models.
Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models.
Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
Expert research analyst specializing in comprehensive information gathering, synthesis, and insight generation. Masters research methodologies, data analysis, and report creation with focus on delivering actionable intelligence that drives informed decision-making.
Cell type regulatory analysis using gcell. Use this skill when users ask about: - Loading pre-inferred cell types (GET model outputs) - Gene-by-motif matrices showing TF influence on genes - Gene Jacobian analysis for regulatory importance - Motif subnet visualization - Cell type-specific gene expression patterns Triggers: cell type, regulatory analysis, gene expression, Jacobian, motif subnet, GET model, TF influence
Pathway enrichment analysis using gcell. Use this skill when users ask about: - Gene set enrichment analysis - GO (Gene Ontology) enrichment - KEGG pathway analysis - Reactome pathway enrichment - Custom pathway/gene set analysis Triggers: pathway enrichment, GO enrichment, KEGG, Reactome, gene set analysis, functional enrichment, ontology
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 figures in high-energy physics publications.
Comprehensive research, analysis, and content extraction system. Multi-source parallel research using available researcher agents. Deep content analysis with extended thinking. Intelligent retrieval for difficult sites. Fabric pattern selection for 242+ specialized prompts. USE WHEN user says 'do research', 'extract wisdom', 'analyze content', 'find information about', or requests web/content research.
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 light curves", "work with astronomical catalogs", "perform astrometry", "process images from telescopes", or mentions astronomical instruments, surveys, or astrophysical phenomena. Provides guidance for scientific astrophysics workflows and best practices.
Protein structure and interaction analysis using gcell. Use this skill when users ask about: - Protein sequences from gene names - AlphaFold2 structure predictions and pLDDT scores - UniProt protein information - 3D protein structure visualization - Protein-protein interactions (STRING database) Triggers: protein structure, AlphaFold, pLDDT, UniProt, protein sequence, 3D structure, protein interaction, STRING
ChIP-Atlas epigenome data query using gcell. Use this skill when users ask about: - Finding ChIP-seq, ATAC-seq, or DNase-seq experiments - Searching for transcription factor binding data - Finding histone modification data (H3K27ac, H3K4me3, etc.) - Querying epigenome data by cell type or tissue - Downloading peak files or BigWig coverage data - Enrichment analysis for genomic regions or gene lists Triggers: ChIP-seq, ChIP-Atlas, ATAC-seq, DNase-seq, histone modification, H3K27ac, H3K4me3, transcription factor binding, epigenome, peak data, BigWig, enrichment analysis
Gene annotations and TSS analysis using gcell. Use this skill when users ask about: - GENCODE gene annotations - Transcription start sites (TSS) - Gene coordinates and metadata - Transcript information - Querying genes by genomic region Triggers: gene annotation, GENCODE, TSS, transcription start site, gene coordinates, transcript, GTF
Causal network analysis using gcell. Use this skill when users ask about: - Inferring causal relationships from expression data - LiNGAM causal discovery algorithm - Regulatory network construction - Visualizing causal/regulatory networks Triggers: causal network, LiNGAM, causal inference, regulatory network, causal discovery, gene regulatory network
Structural biology analysis including protein structure validation, AlphaFold interpretation, and structural comparisons
Metabolomics-specific analysis strategies and domain knowledge
The scientific method applied to computational research, data science, and experimental software engineering. Covers hypothesis formulation, experimental design, controls, reproducibility, and avoiding common methodological pitfalls like p-hacking, HARKing, and confirmation bias. Use when ", " mentioned.
Evaluates biosimilar products for therapeutic interchange with clinical evidence review. Use when evaluating biosimilars, planning therapeutic switches, or analyzing biosimilar evidence.
Structures molecular test interpretation including NGS panels, FISH, and PCR-based assays. Use when interpreting molecular results, reporting genetic variants, or documenting molecular findings.
Synthesizes surgical, medical, and radiation oncology inputs into coordinated treatment timelines. Use when coordinating multimodal treatment, scheduling sequential therapies, or managing treatment timelines.
Interprets flow cytometry panels for hematologic malignancy classification and minimal residual disease. Use when analyzing flow cytometry, classifying lymphomas/leukemias, or documenting immunophenotyping.
Electronic circuit simulation and SPICE analysis via ngspice MCP tool
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.