React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
Skill 디렉토리
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모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
검색 결과: gene-expression
영문 디렉토리A comprehensive collection of ready-to-use scientific and research skills for AI agents.
AI Agent Skill for Prompting Video Models
Glisp is a Lisp-based design tool that combines generative approaches with traditional design methods, empowering artists to discover new forms of expression.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
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.
Real time WebGL and JavaScript library for face tracking, expression detection and animated emoticons in the browser, with both SVG and Three.js demos included 😄
Compile-time dependency injection in Golang using google/wire — wire.NewSet, wire.Build, wire.Bind (interface→concrete), wire.Struct, wire.Value, wire.InterfaceValue, wire.FieldsOf, cleanup functions, //go:build wireinject injector files, and generated wire_gen.go. Apply when using or adopting google/wire, when the codebase imports `github.com/google/wire`, or when wiring an application graph at compile time via `wire.Build`. For runtime DI with reflection, see `samber/cc-skills-golang@golang-uber-dig` skill.
System.Linq.Expression expressions optimizer. http://thorium.github.io/Linq.Expression.Optimizer
Gene cluster comparison figure generator