Dados e Análise

Pesquisa e recupera contexto de sessões de desenvolvimento anteriores usando dados do Chronicle, funcionando com MCP (rápido, estruturado) ou comandos CLI (portátil). Utilize para relembrar trabalhos anteriores, entender o histórico do código ou evitar repetir abordagens passadas.

TimescaleDB - PostgreSQL extension for high-performance time-series and event data analytics, hypertables, continuous aggregates, compression, and real-time analytics

AI-driven pharmacogenomic analysis for precision dosing and adverse event prediction using multi-omics data.

Download large datasets from NCBI efficiently using history server, batching, and rate limiting. Use when performing bulk sequence downloads, handling large query results, or production-scale data retrieval.

NHGRI-EBI GWAS Catalog REST API for SNP-trait associations from published GWAS. Query studies, associations, variants, traits, genes, summary stats. Build PRS candidates, analyze pleiotropy, fetch stats for Manhattan plots. No auth.

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

Build UpSet plots to visualize set intersections beyond 4 sets (where Venn fails) using ComplexUpset (modern, ggplot2-grammar) or the unmaintained UpSetR, with explicit cardinality vs degree sorting, attribute panels, and query highlighting. Use when comparing overlap across many gene sets, peak sets, variant lists, or any set membership matrix where Venn diagrams become illegible.

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachte

ML molecular com diversos featurizers e conjuntos de dados pré-construídos para previsão de propriedades (ADMET, toxicidade) usando ML tradicional ou GNNs. Ideal para experimentos rápidos com modelos pré-treinados, diversas representações moleculares e benchmarks MoleculeNet, oferecendo amplas opções de featurização.

Full slate analysis for tonight's games with edge rankings, odds across books, and recommended stakes. Use when user asks about tonight's slate, best bets tonight, daily card, full slate, tonight's games, which games are worth betting, or wants all games ranked by edge. Do not use for a single game breakdown -- see game-preview. Do not use for historical backtesting -- see backtesting. Do not use

Python library for genomic interval ML. Train/apply region2vec embeddings turning BED regions into vectors, index interval datasets for ML, search embedding space with BEDSpace, and evaluate embedding quality. Use for chromatin accessibility clustering, regulatory element classification, and cross-sample region comparison.

Use when setting up Alembic migrations or making database schema changes. Triggers for: initializing Alembic, generating migrations, applying upgrades, rolling back changes, or creating data migrations. NOT for: raw SQL execution outside migration context or non-database schema updates.