Dados e Análise

Detect syntenic blocks and structural rearrangements between genomes using MCScanX (Wang 2012), JCVI/MCScan (Tang 2008 Python), GENESPACE (Lovell 2022) for orthology-anchored riparian visualization, SyRI for structural variation, AnchorWave for sequence-level synteny, i-ADHoRe 3.0 for highly diverged species, SynNet for synteny networks, and ntSynt for multi-genome macrosynteny. Use when identifyi

Optimize for search engine visibility and ranking. Use when asked to "improve SEO", "optimize for search", "fix meta tags", "add structured data", "sitemap optimization", or "search engine optimization".

Scaffold contigs into chromosome-level assemblies using Hi-C data with YaHS, 3D-DNA, SALSA2, and validate with BUSCO and contact maps. Use when scaffolding contigs to chromosome-level assemblies.

Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

Utilize para configurar clientes de API, como TanStack Query, Axios, gerenciamento de tokens JWT, tratamento de erros ou análise de respostas. Não use para chamadas fetch simples, manipulação de dados não-API ou lógica de UI não relacionada.

Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.

Comprehensive patient stratification for precision medicine by integrating genomic, clinical, and therapeutic data. Given a disease/condition, genomic data (germline variants, somatic mutations, expression), and optional clinical parameters, performs multi-phase analysis across 9 phases covering disease disambiguation, genetic risk assessment, disease-specific molecular stratification, pharmacogen

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

O SDK de Gerenciamento do Azure API Center para Python é usado para gerenciar o inventário de APIs, metadados e governança em toda a sua organização.

Add, remove, and manage page-level and visual-level filters on Power BI PBIR reports using pbi-cli. Invoke this skill whenever the user mentions "filter", "TopN filter", "top 10", "bottom 5", "relative date filter", "last 30 days", "categorical filter", "include values", "exclude values", "clear filters", "slicer filter", "page filter", "visual filter", or wants to restrict which data appears on a

Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

Verifies and corrects model probability outputs so predicted win percentages match actual win rates. Use when user asks about calibration, reliability diagrams, Brier score, Platt scaling, isotonic regression, probability quality, or whether model probabilities are accurate. Also use when user has a trained model and wants to know if outputs can be trusted for betting. Do not use for odds math or