「ner」の検索結果

Performs logistic regression for clinical trial outcomes (binary, ordinal, multinomial) with marginal-vs-conditional estimand reporting per FDA 2023 covariate adjustment guidance, g-computation/standardisation for marginal effects, modified Poisson for RR, Brant test for proportional odds, Firth penalty for separation, and Hauck-Donner detection. Use when modeling binary or ordinal endpoints in confirmatory or exploratory clinical trials.

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。

Calls ChIP-seq peaks with MACS3, MACS2, HOMER, or SPP across narrow (TF) and broad (histone) modes. Handles input control matching, fragment-size modeling vs --nomodel, effective genome size, ENCODE-style IDR vs naive overlap, hyper-ChIPable artifacts, and aligner-specific shifts. Use when calling peaks from ChIP-seq alignments, choosing between narrow vs broad mode for a histone mark, deciding model vs nomodel for low-depth data, applying ENCODE pseudoreplicate IDR, or reconciling MACS vs HOMER vs SPP results.

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 chemical libraries by scaffold using Bemis-Murcko scaffolds, generic frameworks, cyclic skeletons, matched molecular pair (MMP) analysis via mmpdb, R-group decomposition, Free-Wilson analysis, scaffold hopping, and chemotype-aware ML train/test splits. Use when identifying chemotype clusters in a library, deriving SAR transformation rules, decomposing series into R-groups, performing scaffold-balanced QSAR splits, or planning analog campaigns.

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 required bioinformatics command-line tools against Lmod or Environment Modules on Linux HPC clusters, resolve executable and version requirements, and reproducibly deploy missing software through a site-approved EasyBuild, Spack, Bioconda/micromamba, Apptainer, binary, or source-build workflow. Use when Codex must inspect module availability, diagnose a missing or wrong-version bioinformatics tool, install scientific software on Slurm/PBS clusters, publish or validate modulefiles, or produce an auditable and rollback-ready cluster software deployment.

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。

Map nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter. Use when characterizing nucleosome organization at promoters and enhancers, calling +1/-1 nucleosomes flanking NFRs, generating V-plots for chromatin structure visualization, or comparing nucleosome positioning between 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。

Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or EnFormer. Use when correcting Tn5 bias with neural networks beyond k-mer models, predicting per-base accessibility profiles, scoring in silico variant effects at GWAS or rare-variant SNPs, discovering motifs via DeepLIFT/TF-MoDISco from a trained model, or generating cell-type-specific accessibility predictions for unobserved cell states.

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 a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.

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。

Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA (LSV posteriors interactive HTML), leafviz (leafcutter clusters Shiny), Jutils (tool-agnostic heatmaps and sashimi for rMATS/leafcutter/SUPPA2/MAJIQ output), or pyGenomeTracks (multi-track publication figures). Tool choice depends on the upstream differential-splicing tool's output format and the publication vs interactive use case. Use when visualizing specific splicing events, validating differential splicing calls, or producing publication-quality figures.

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。

Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matches between DNA, RNA, or protein sequences.

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。

Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection 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。

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。

Add MAUI DevFlow to a .NET MAUI project with agent package references, MauiProgram.cs registration, Blazor WebView support, GTK variants, Central Package Management guidance, and verification commands. USE FOR: first-time DevFlow setup, reviewing what files to edit, choosing DevFlow packages, or continuing after `maui devflow init` installs skills. DO NOT USE FOR: troubleshooting an already-integrated app that cannot connect, iterative app debugging, UI inspection, or generic MAUI build failures (use maui-devflow-debug). INVOKES: maui devflow CLI and dotnet CLI.

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。

Run build, deploy, inspect, and fix loops for .NET MAUI apps that already have MAUI DevFlow integrated. USE FOR: launching MAUI apps, selecting devices or emulators, waiting for or recovering agent connections, broker/port/adb connectivity issues, visual tree inspection, screenshots, UI interaction, Blazor WebView CDP debugging, reading DevFlow logs, and iterative app debugging. DO NOT USE FOR: first-time DevFlow package setup (use maui-devflow-onboard), or generic desktop automation unrelated to MAUI. INVOKES: maui devflow CLI, dotnet CLI, Android adb/android tools, and Apple simctl tools.

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 about towing + recovery operations — separate FMCSA authority class, light-duty vs medium-duty vs heavy-duty wrecker rules, AAA + AAA-Plus contracts, Roadside-Assistance (RA) operations, "non-consensual tow" rules + state-by-state, and how towing operations differ from general freight. Reference state Public Utility Commission + 49 CFR 395 application.

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 recruit CDL drivers — sourcing channels (CDL schools, job boards, military, returning citizens, owner-operator pools), application + screening process, signing bonus structures, recruitment marketing, fleet ambassador programs, and what's working in the current driver market. Reference ATA Workforce Development.

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 about workers compensation for trucking — required by state law, classification of drivers, premium calculation (rate × experience modifier × payroll), Common Claim types in trucking, returning injured drivers to work, claims management, premium reduction strategies, and the difference between WC and Occupational Accident insurance for owner-operators. Reference state WC laws + IFTA / fleet insurance.

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 about trucking insurance — types of coverage (commercial auto, cargo, occupational accident, workers comp, bobtail/non-trucking, MCS-90 endorsement), federal minimums (49 CFR 387), what each covers, owner-operator vs company-driver implications, and how to read a Certificate of Insurance (COI). Cite 49 CFR 387.

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 safety director, operations manager, or fleet owner asks for templates, topics, or structure for recurring safety meetings — weekly driver meetings, monthly safety committee meetings, quarterly all-hands safety reviews, or post-incident safety stand-downs.

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 about Household Goods (HHG) movers — 49 CFR 375 + 376 consumer protection rules, FMCSA HHG-specific authority, mover certification, binding vs non-binding estimates, dispute resolution, weight ticket requirements, valuation coverage, and how HHG operations differ from general freight. Cite 49 CFR 375.

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 understand FMCSA cardiac certification standards. Covers what cardiac conditions disqualify, time-to-clearance, and what documentation is needed for examiner certification.

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。

Use this skill when the user asks about carrier-driver relationships — Independent Contractor (IC / 1099) vs Employee (W-2), Owner-Operator lease agreements, the AB5 California law, the DOL 2024 IC test, lease-purchase programs from the carrier side, settlement statements, deductions, and how to structure a compliant IC arrangement. Cite 49 CFR 376 + 1099 IRS rules.

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 owner, CFO, or controller asks how to build an annual budget, monthly P&L model, cash flow forecast, scenario plan, or break-even analysis for a trucking operation. Covers revenue modeling, cost structures, capital planning, and the discipline of tracking actuals vs budget.

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 buying another carrier and inheriting their drivers' DQF library. Covers the legal transfer of DQ records, what new owner must verify, and gaps that commonly require remediation.

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。