1,352 件 ・ 関連度順
概要と使いどころ
Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.
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。
Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.
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。
Build and analyze pangenomes for prokaryotes (Panaroo, PPanGGOLiN, PEPPAN, GET_HOMOLOGUES, anvi'o pangenomics) and eukaryotes (Minigraph-Cactus, PGGB, vg pangenome graphs). Implement Tettelin core/accessory/cloud genome decomposition (Tettelin 2005), Heap's law open/closed pangenome modeling, gene presence/absence GWAS (Scoary, pyseer), pangenome graph variant calling (vg, PanGenie), and structural-variation graph indexing. Use when assembling species- or genus-level pan-gene catalogs, separating core from accessory/shell/cloud genes, testing gene-content associations with phenotypes, building pangenome graphs from haplotype-resolved assemblies, calling SVs from pangenome graphs, or selecting between bacterial-pangenome and eukaryotic-pangenome workflows.
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。
Detect horizontal gene transfer (HGT / LGT) using compositional methods (GC%, codon usage, tetranucleotide z-scores via SIGI-HMM, AlienHunter, IslandViewer 4, IslandPath-DIMOB), phylogenetic-incongruence methods (AvP, HGTphyloDetect, ALE / GeneRax / AleRax reconciliation, RANGER-DTL), and BLAST-distribution methods (HGTector v2, DarkHorse, Alien Index). Use when screening prokaryote genomes for genomic islands and HGT events, distinguishing HGT from incomplete lineage sorting / differential gene loss / hybridization, mapping donor lineages via phylogenetic placement, separating eukaryotic HGT from contamination, ruling out gBGC as a false signal, or quantifying DTL rates with ALE/GeneRax on bacterial trees.
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。
Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.
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。
Select, document, download, and checksum-verify the most appropriate NCBI reference genome on an HPC cluster. Use whenever an analysis needs a reference genome, genome FASTA, genome annotation, assembly accession, or genome index and no exact approved assembly is already available; when a user asks to fetch a species genome from NCBI; or when a pipeline must resolve and cache a reproducible reference assembly on a remote cluster.
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。
Generate consensus sequences and manage reference files using samtools. Use when creating consensus from alignments, indexing references, or creating sequence dictionaries.
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。
Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.
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。
Sort alignment files by coordinate or read name using samtools and pysam. Use when preparing BAM files for indexing, variant calling, or paired-end analysis.
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。
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
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。
Generates strictly typed Drizzle ORM schemas for PostgreSQL with indexes, foreign keys, and Zod schema deduction.
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。
Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.
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。
Memory consolidation pass: orient on existing memories, gather signal from logs/transcripts, merge updates into topic files, prune index. Use on 'dream', 'consolidate memory', 'clean up memories', 'prune memories', 'memory maintenance', or when memories feel stale.
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 AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.
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 AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.
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 AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.
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。
Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning
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。
Generate a single-file industrial-archive product landing page (Nordic museum aesthetic, hash-routed detail pages). Takes a natural-language description of one or more "exhibit-style" products (objects, tools, hardware, watches, kitchenware, lighting, audio, instruments, anything with a designed/forged/restrained quality); outputs ONE working .html file. Visitors see a black-framed cover that flips between exhibits, sidebar index, side meta column (material/origin/year/dimension), and click any exhibit → full detail page (giant italic title, spec table, hero image, lead + 3 prose paragraphs, gallery, prev/next). Runs in BOTH Claude Code (writes to ~/Desktop) and GLM / online chat (outputs HTML inline). Trigger: "做个工业风产品落地页", "做克制之物风格的展品页", "industrial-archive-gen ...", or when user drags this skill folder into chat asking for a product page in the Nordic-industrial archive style.
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。
Canonical design token registry — colors, typography, spacing, sizing, border radius, shadows, z-index, breakpoints, motion, and focus tokens. Used by ui-best-practices rules and all agents that implement or review UI components. Includes CSS variable template for quick project setup.
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。
Create GitHub releases for this project or similar GitHub repositories. Use when the user asks to release the current master/main branch, create a version tag, publish a GitHub Release, write release notes, check release workflow status, or follow the repository's release process.
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。
Check an externally created PR for coding rule violations against memory/INDEX.md atoms and docs/architecture/code-review-rules.md.
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。
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup. For AI search optimization, see ai-seo.
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。
Execute AEM Edge Delivery Services admin operations - list admins, add/remove users, preview, publish, unpublish content, clear cache, sync code, reindex, generate sitemap, manage snapshots, view logs, manage jobs, list sites, configure org/site settings, manage secrets and API keys. Also supports Document Authoring (DA) operations via admin.da.live - list/get/put content, copy, move, delete, versioning, and DA-specific preview/publish. Use for any Edge Delivery Services administrative task.
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。
Audit and update metadata across multiple AEM Edge Delivery Services pages. Scans pages via the query index, identifies missing or inconsistent metadata (titles, descriptions, og tags, robots), and generates a corrected bulk metadata spreadsheet. Use when standardizing metadata across a site, preparing for launch, or fixing SEO issues at scale.
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。