「collection」の検索結果

Design accessible apps. TRIGGERS - Use when user needs help with accessible-app-design related tasks.

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。

Implement 5S workplace organization. TRIGGERS - Use when user needs help with 5s-implementation related tasks.

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 strategic account planning templates. TRIGGERS - Use when user needs help with account-planning-template related tasks.

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 academic publishing. TRIGGERS - Use when user needs help with academic-publishing-guide related tasks.

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。

Write clear acceptance criteria for features. TRIGGERS - Use when user needs help with acceptance-criteria related tasks.

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 accessibility checklists for web applications. TRIGGERS - Use when user needs help with accessibility-checklist related tasks.

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。

Implement A/B tests with code and analytics. TRIGGERS - Use when user needs help with ab-test-implementation related tasks.

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 ADA accessibility compliance checklists. TRIGGERS - Use when user needs help with accessibility-compliance related tasks.

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。

Write accessibility policies. TRIGGERS - Use when user needs help with accessibility-policy-writer related tasks.

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。

Analyze 5G use cases. TRIGGERS - Use when user needs help with 5g-use-case-analysis related tasks.

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。

Plan 5G network deployment with coverage. TRIGGERS - Use when user needs help with 5g-deployment-plan related tasks.

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 workplace accessibility for compliance. TRIGGERS - Use when user needs help with accessibility-audit related tasks.

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 accessibility training. TRIGGERS - Use when user needs help with accessibility-training-program related tasks.

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 409A valuation processes. TRIGGERS - Use when user needs help with 409a-valuation-guide related tasks.

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 acceptable use policies. TRIGGERS - Use when user needs help with acceptable-use-policy related tasks.

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。

Process accommodation requests with documentation. TRIGGERS - Use when user needs help with accommodation-request related tasks.

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。

Evaluate third-party logistics providers. TRIGGERS - Use when user needs help with 3pl-evaluation related tasks.

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。

Write accessibility requirements. TRIGGERS - Use when user needs help with accessibility-requirements related tasks.

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。

Answers "can CARLA do X here, and is there a vetted procedure for it" before you promise anything, and detects client/server/tree version skew — a support matrix over the whole collection (covered by a skill / works but undocumented / present but untested / broken or removed), an index of the features that are verified BROKEN on 0.10.0 (gbuffers crash the server, map layers do nothing, Landmark.waypoint is None, standalone asset packages are gone), and a probe that reports what this machine's build flags and running server actually offer. Use when the user asks whether CARLA supports something, when a feature has no skill, when a UE4 tutorial's steps do not exist, or before improvising a procedure.

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。

Annotates bacterial and archaeal genomes (isolates, MAGs, plasmids) with Bakta (active versioned databases, NCBI-compliant output) or Prokka (legacy), producing GFF3/GenBank/EMBL/FASTA with INSDC locus tags. Covers Bakta-vs-Prokka-vs-PGAP-vs-DFAST choice, light-vs-full database tiers, translation-table selection (11/4/25), archaeal and leaderless-gene caveats, the small-ORF blind spot, pseudogene-vs-phase-variation, the pangenome re-annotation trap, and submission compliance. Use when annotating a newly assembled prokaryotic genome, choosing an annotation tool, re-annotating a collection for pangenomics, or preparing annotations for NCBI/DDBJ submission.

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。

Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.

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。

Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME. Handles background selection (GC-matched, dinucleotide-shuffled, Markov order-2, peak-flanks), motif databases (JASPAR 2024 CORE PWMs, JASPAR 2026 deep-learning collection, HOCOMOCO v12, HOMER built-in), centrally-enriched motif testing, and differential motif analysis. Use when identifying TF binding motifs in peaks, testing for known TF enrichment, scanning for motif instances, comparing motif content between conditions, or interpreting motifs from deep learning models.

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。

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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。

Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping, neutralization, tautomer canonicalization, stereochemistry standardization, mixture handling, and isotope normalization. Explicitly compares ChEMBL pipeline, canSARchem, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.

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。