30 件 ・ 関連度順
概要と使いどころ
Use when a task needs the judgment of a Biomass Power Plant Manager — running a biomass-fired power generation facility, managing fuel supply logistics and quality variability, evaluating combustion/efficiency problems, or balancing generation output against fuel cost and emissions constraints.
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 material forecasting and requirements planning systems including MRP/MRP II logic evaluation, BOM explosion accuracy, supplier lead time variability tracking, seasonal demand pattern detection, fabric yield and marker efficiency optimization, MOQ aggregation strategies.
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 TF motif accessibility variability across samples or single cells using chromVAR. Use when identifying TF motifs whose accessibility correlates with conditions, computing per-sample motif z-scores after matched background correction, comparing to ArchR / Signac equivalents, or distinguishing motif-accessibility signal from per-site footprinting.
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 CGM blood glucose data from Nightscout. Use this skill when asked about current glucose levels, blood sugar trends, A1C estimates, time-in-range statistics, glucose variability, or diabetes management insights.
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。
Interactive cell annotation and image QC for IMC/MIBI using napari, napari-imc, Mantis Viewer, and cytomapper, covering the pixels-to-cell-table bridge, overlaying masks to catch segmentation/spillover artifacts, inter-annotator variability as the accuracy ceiling, contrast-as-threshold, and building class-balanced ground-truth label sets. Use when manually labeling cells, generating training data for a classifier, QC-ing segmentation on the image, confirming clusters are spatially real, or choosing an annotation viewer.
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 TF motif accessibility variability across samples or single cells using chromVAR. Use when identifying TF motifs whose accessibility correlates with conditions, computing per-sample motif z-scores after matched background correction, comparing to ArchR / Signac equivalents, or distinguishing motif-accessibility signal from per-site footprinting.
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。