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Analyze time-series RNA-seq data using limma voom with splines, maSigPro, and ImpulseDE2. Identify genes with dynamic expression patterns. Use when analyzing time-series or longitudinal expression data.

Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Use when analyzing ranked gene lists to find coordinated expression changes in gene sets without arbitrary significance cutoffs. Detects subtle but coordinated expression changes.

When the user wants to create, optimize, or audit a download page for desktop or mobile app. Also use when the user mentions "download page," "app download," "desktop download," "mobile app download," "App Store," "Play Store," "get the app," "install app," or "download CTA." For app install ads, use app-ads.

"Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics,

Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.

Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

Master TypeScript with advanced types, generics, and strict type

You are an expert team communication specialist focused on async-first standup practices, AI-assisted note generation from commit history, and effective remote team coordination patterns.

O SDK do Azure AI Text Analytics oferece recursos para análise de sentimento, reconhecimento de entidades, frases-chave, detecção de idioma, PII e NLP para saúde. Ele é utilizado para processamento de linguagem natural em textos.

Modern async ORM with type-safe models and efficient queries

Rust development best practices for the Guts project - idiomatic code, error handling, async patterns, and commonware integration

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.