3,410 件 ・ 関連度順
概要と使いどころ
CLI toolkit for SAM/BAM/CRAM: sort, index, convert, filter, QC alignments. Core commands: view, sort, index, flagstat, stats, depth, markdup, merge. Required between alignment and variant/peak calling. Use pysam for Python-native BAM access; deeptools for normalized coverage tracks.
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。
Open-source FAIR biology data framework. Version artifacts (AnnData, DataFrame, Zarr), track lineage, validate via ontologies (Bionty), query datasets. Integrates with Nextflow, Snakemake, W&B, scVI. For scRNA-seq use scanpy; for ontology lookups use bionty.
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。
Access USPTO patent data via PatentsView REST API and Google Patents Public Data (BigQuery). Search by inventor, assignee, CPC, or keywords; download metadata and claims; analyze portfolios; track tech trends. For IP landscape analysis, competitor monitoring, prior art search, and tech forecasting in life sciences and biotech.
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。
Selecting a reference manager and applying citation styles. Compares Zotero, Mendeley, EndNote, Paperpile; covers APA/Vancouver/ACS/Nature styles, DOI management, citation tracking, and Word/Google Docs/LaTeX integration. Use when setting up a reference workflow or fixing citation formatting.
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。
API + Python SDK for ordering cell-free protein expression and binding assays. Submit sequences for expression (10–100 µg), measure binding affinity (KD) against targets, track status, and retrieve results programmatically — no wet-lab setup. Built for ML-guided directed evolution and antibody/nanobody optimization. Requires Adaptyv account and API key.
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。
Python bridge to ImageJ2/Fiji for macros, plugins (Bio-Formats, TrackMate, Analyze Particles), NumPy↔ImagePlus/ImgLib2 exchange, and ImageJ Ops. Automates Fiji headlessly from Python. Use scikit-image for pure Python without Fiji plugins; napari for visualization.
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。
DL cell/nucleus segmentation for fluorescence and brightfield microscopy. Pre-trained models (cyto3, nuclei, tissuenet) and a generalist flow-based algorithm segment cells without retraining. Outputs label masks for morphology and tracking. Use scikit-image watershed for rule-based; Cellpose when DL generalization across staining 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。
Interactive viewer for microscopy. Displays 2D/3D/4D arrays as Image, Labels, Points, Shapes, Tracks layers; supports annotation, plugin analysis, headless screenshots. Core visualization for Python bioimage workflows. Use ImageJ/FIJI for macro processing; napari for Python-native interactive visualization and DL segmentation review.
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 ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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。
Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface: 6 tools with --full (adds check_action); 13 tools with AR_EXTRAS=1 --full. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.
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。
Remove the discourse-level (structural) signs of AI writing that survive surface editing: stated lessons and moral-of-the-story closers, tidy single-track arcs, embodied-emotion performance ("chest tightened"), vague allusions instead of named references, unbroken linear structure, and shape convergence across pieces. Grounded in the StoryScope study (Russell et al. 2026): narrative structure alone detects AI text at 93.2% F1, and professional stylistic rewriting moved detection only 1.6 points. Use as the SECOND pass after the humanizer skill (which handles words and phrasing) whenever writing or revising LinkedIn posts, course lessons, blog posts, essays, newsletters, or emails that must read as human. Triggers: "humanize", "de-slop", "AI tells", "make this sound human", "structural pass", "deep humanize".
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 monitor reviews, mentions, and community sentiment about their own product. Also use when the user mentions "track our reviews", "what are people saying about us", "brand monitoring", "reputation management", or "review alerts".
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 a founder needs demo scripts, discovery call frameworks, objection handling, RFP/RFI responses, competitive feature matrices, POC planning, or closing playbooks. Activate for sales calls, demo prep, talk tracks, bid responses, competitor comparisons, or pre-sales engineering.
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。
Construction safety incident reporting and analysis. Capture incidents, conduct investigations, track corrective actions, and analyze trends for prevention.
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。
Compress construction schedules using crashing and fast-tracking techniques. Analyze cost-time tradeoffs and find optimal acceleration 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。
Excel/spreadsheet processing for construction: estimates, schedules, tracking logs, quantity takeoffs. Formulas, formatting, 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。
Process construction payment applications. Validate schedule of values, calculate retainage, track billing status, and generate G702/G703 forms.
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。
Document construction claims for disputes and recovery. Compile evidence, calculate damages, track notice requirements, and prepare claim packages.
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。
Construction quality control workflow automation. Manage QC inspections, track defects, generate NCRs, and ensure specification compliance throughout the project.
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。
Digital safety inspection checklists for construction sites. Generate, conduct, and track safety inspections with automated reporting and compliance monitoring.
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 Telegram bots for construction field workers. Real-time reporting, photo uploads, task assignments, progress tracking. Integrate with n8n for automated 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。
Manage construction change orders from request to approval. Track costs, schedule impacts, and maintain audit trail for dispute prevention.
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 Gantt charts for construction scheduling. Create visual project timelines with dependencies and progress tracking.
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。
Manage construction unit price databases: update prices, track vendors, apply location factors, maintain historical records. Essential for accurate estimating.
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。