「apa」の検索結果

Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.

日本語の概要は準備中です。原文の説明を表示しています。

Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a carrier or driver asks about winter trucking, snow chain requirements, hot-weather precautions, summer tire failures, fuel additive use (anti-gel), idle management in extreme temperatures, weight restrictions in spring thaw, or how seasonal demand patterns affect freight rates and capacity.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when the user asks how to build + manage direct shipper relationships — moving from spot market to dedicated lanes, customer scoring + credit assessment, contract terms, dedicated capacity agreements, KPI reporting, and how to handle customer disputes. Reference standard customer-carrier contract terms.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill to develop the capability to investigate crashes internally. Covers what to look for, when to escalate to outside experts, and documentation standards.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a dispatcher, operations manager, or owner asks how to plan loads to minimize empty (deadhead) miles, sequence freight efficiently, balance regional capacity, design dedicated loops, or build a load-pairing strategy across customers. Covers loaded-ratio math, lane balance, region-pair pricing, and software-supported optimization.

日本語の概要は準備中です。原文の説明を表示しています。

Runbook for creating or majorly growing an @ai-matrx TypeScript npm package. Use when invoked as /new-package <name or capability>, or for a new @ai-matrx/* package, extracting code into one, or a major growth wave. NOT for a routine fix inside an existing package (THE SAME-SESSION LAW).

日本語の概要は準備中です。原文の説明を表示しています。

Discovery batch that grows the Provider Access Launch queue. Use when asked to find more user-connected OAuth, API, API-key, remote MCP, marketplace, or partner-access campaigns for a capability, provider family, MCP/plugin catalog, or competitive gap. NOT for client Local Listings distribution.

日本語の概要は準備中です。原文の説明を表示しています。

Doctrine for adding a capability INTO a live, existing feature to a world-class bar. Use on 'add X to Y', 'extend Y to support X', a new option, button, setting, endpoint, or tool for Y, or a sub-feature spec to implement. NOT for whole-feature audits or overhauls (use feature-deep-dive).

日本語の概要は準備中です。原文の説明を表示しています。

Redux state for agent execution and firing agent shortcuts. Use when editing features/agents/redux/, building agent UI, creating a conversation, touching assembleRequest or NDJSON stream state, wiring agent-state selectors, adding a per-conversation capability, or triggering a shortcut from a button, menu, or code (useShortcutTrigger, launchAgentExecution).

日本語の概要は準備中です。原文の説明を表示しています。

Adding a file type or upgrading any of its capability slots in the files feature (preview, edit, thumbnail, grid card, info, share, versions, conversion, diff, rail panel). Use when supporting a new extension or MIME type, building a previewer, touching FILE_TYPES, PreviewKind, FilePreview.tsx, EDITABLE_KINDS, or surfaces/single-file/, or working the FILE_SURFACES.md wishlist.

日本語の概要は準備中です。原文の説明を表示しています。

Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user explicitly asks to threat model a codebase or path, enumerate abuse paths, or perform AppSec threat modeling.

日本語の概要は準備中です。原文の説明を表示しています。

Helps users discover and install agent skills. Use when they ask "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities with installable skills.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is needed.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

日本語の技術文書・書籍原稿の文章規範。整形（一文一行、引用ブロック、脚注、コラム記法）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

日本語の概要は準備中です。原文の説明を表示しています。

4claw — a moderated imageboard for AI agents. Boards, threads, replies, media uploads, bumping (bump=false to not bump), greentext, and automatic capacity purges. Post spicy hot takes (what you're REALLY thinking) — but no illegal content, doxxing, harassment, or minors.

日本語の概要は準備中です。原文の説明を表示しています。

ALWAYS use this skill when user needs ANY API functionality (AI models, image generation, video, audio, text processing, etc.). Automatically search 302.AI's 1400+ APIs and generate integration code. Use proactively whenever APIs or AI capabilities are mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

3D web graphics with Three.js (WebGL/WebGPU). Capabilities: scenes, cameras, geometries, materials, lights, animations, model loading (GLTF/FBX), PBR materials, shadows, post-processing (bloom, SSAO, SSR), custom shaders, instancing, LOD, physics, VR/XR. Actions: create, build, animate, render 3D scenes/models. Keywords: Three.js, WebGL, WebGPU, 3D graphics, scene, camera, geometry, material, light, animation, GLTF, FBX, OrbitControls, PBR, shadow mapping, post-processing, bloom, SSAO, shader, instancing, LOD, WebXR, VR, AR, product configurator, data visualization, architectural walkthrough, interactive 3D, canvas. Use when: creating 3D visualizations, building WebGL/WebGPU apps, loading 3D models, adding animations, implementing VR/XR, creating interactive graphics, building product configurators.

日本語の概要は準備中です。原文の説明を表示しています。

日本語の文章を、意味を変えずに自然で文脈に合う表現へ整えるスキル。Markdown、README、設計メモ、仕様書、説明文、報告文、コミットメッセージ、コードコメント、関数や型のドキュメント、UI 文言など、日本語を新規作成・編集・レビューするすべての場面で使う。明示的に「自然な日本語にして」と言われたときだけでなく、AI Agent が日本語を書くとき、英語由来の直訳語、文脈に合わない語、意味は通るが普通は使わない語を避けるために発火する。

Build search applications with vector, hybrid, and semantic search capabilities.

日本語の概要は準備中です。原文の説明を表示しています。

Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources.

日本語の概要は準備中です。原文の説明を表示しています。