'workflows' 검색 결과

End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding. Use when running the full Yeo lab eCLIP / iCLIP / iCLIP2 / iCLIP3 / irCLIP / PAR-CLIP analysis with SMInput control, protocol-specific UMI extraction, ENCODE STAR parameters, CLIPper or Skipper peak calling with stringent log2 FC and -log10 p thresholds, IDR rescue and self-consistency QC, and downstream motif registration with mCross or PEKA.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

End-to-end multi-omics integration workflow. Orchestrates data harmonization, MOFA/mixOmics integration, factor interpretation, and downstream analysis across transcriptomics, proteomics, metabolomics, and other modalities. Use when integrating multiple omics datasets.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze metabolomics data end-to-end — metabolite identification, quantification (TIC normalization, batch correction), differential analysis, and pathway interpretation. Use for processing mass-spec metabolomics output, normalization choice, untargeted metabolomics workflows, and integrating with other omics layers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs PROTACs, molecular glues, and bivalent degraders with explicit handling of E3 ligase choice (VHL, CRBN, IAP, MDM2, KEAP1), linker design (length, composition, rigidity), ternary complex prediction (PRosettaC, DeepTernary, AlphaFold3 with constraints), cooperativity (alpha), DC50 / Dmax characterization, hook effect, and prediction-experiment reconciliation. Use when designing targeted protein degraders, planning linker SAR, predicting ternary complex stability, or building generative degrader workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling of when ML beats classical docking, when classical beats ML, the PB-invalid pose problem, and rescoring as the standard production hybrid. Use when modern docking is needed: foundation-model ligand-pose prediction, AI rescoring of classical poses, or scaffold-hopping in cross-docking scenarios.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design AI-assisted content creation workflows. TRIGGERS - Use when user needs help with ai-content-workflow related tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build AI prompt chains and multi-step workflows for complex tasks. TRIGGERS - Use when user needs help with ai-chain-builder related tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design multi-step AI agent architectures with tools, memory, and orchestration. TRIGGERS - Use when user wants to design AI agents, multi-agent systems, or autonomous AI workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design data annotation workflows for AI. TRIGGERS - Use when user needs help with ai-annotation-workflow related tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build autonomous AI workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design ad operations workflows. TRIGGERS - Use when user needs help with ad-ops-workflow related tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design automation for accounting workflows. TRIGGERS - Use when user needs help with accounting-workflow-automation related tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Integrate Iteration Layer APIs for document, website, image, and sheet processing. Composable APIs — Document Extraction, Website Extraction, Document to Markdown, Image Transformation, Image Generation, Document Generation, and Sheet Generation — share one credit pool and chain together into workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract product name, SKU, price, and specifications from a catalog document into structured JSON for e-commerce workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract parties, dates, and clauses from a contract into structured JSON for legal review workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Claude Code (code.claude.com) の拡張機能リファレンス。 Agent Skills (SKILL.md), slash commands, output styles, subagents (cross-session messaging), agent teams, agent view, workflows, routines, scheduled tasks, hooks (PreToolUse / PostToolUse), mods (Claude Code mods), plugins, plugin eval, plugin marketplace (marketplace.json), MCP 設定 (.mcp.json / claude mcp add), managed MCP, channels (--channels / claude/channel push events, webhook / telegram / discord / imessage), tools-reference, advisor, ultrareview。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Claude Managed Agents (platform.claude.com) リファレンス。Agents / Sessions / Environments API, SSE event streaming, event deltas, session threads, session budgets, multiagent orchestration (subagents, dynamic workflows, workflow runs, advisor), deployments (cron), dreams, vaults, memory stores, self-hosted sandboxes, webhooks, web search / fetch ドメイン制限, secure deployment, permission policies, Agent Skills, MCP connector, user profiles。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

App Store Connect API 4.5.1 (REST) アプリ配布リファレンス。JWT 認証、API キー作成・失効、 Apps, Builds, Bundle IDs, Bundle ID Capabilities, Certificates, Devices, Provisioning Profiles, Users, User Invitations, Merchant IDs, Pass Type IDs、TestFlight (Beta Groups / Testers)、 Sandbox Testers、App Review, Review Submissions, Customer Reviews, Custom Product Pages, Phased Release、In-App Purchases, Subscriptions, Subscription Groups, App Price Points, Promotional Offers, Win-back Offers, Sales Reports、App Asset Library (screenshots / app previews)、 Webhooks / Webhook Events / Deliveries、Xcode Cloud (Workflows, Build Runs, Artifacts)、 Alternative Distribution (EU マーケットプレイス / Web Distribution)、 Game Center (Achievements, Leaderboards, Challenges)、Analytics / 診断レポート。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Bulk mode — maximum development speed by spending tokens aggressively on massive parallel sub-agents and multi-agent workflows, while the orchestrator context stays lean (pairs with /slim). Invoking /bulk is the user's explicit opt-in to Workflow/ultracode-style orchestration for this session. Use when the user types /bulk, asks for "爆速", "並列で大量に", "ultracode", "多エージェント", or hands over a big task where wall-clock speed matters more than token cost.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.