'fish' 검색 결과

Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2G), accessibility-only (Cicero), and orthogonal (HiChIP H3K27ac, EpiMap) approaches, validating predictions against CRISPRi-FlowFISH gold-standard, or building cell-type-specific regulatory maps for fine-mapping or therapeutic target discovery.

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CAPA system management for medical device QMS, covering root cause analysis, corrective action planning, and effectiveness verification. Use for CAPA investigations, 5-Why and fishbone analysis, and corrective action tracking.

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April Dunford's 10-step positioning methodology for B2B tech products. Use when customers don't understand the product, sales cycles are long because reps must "explain it," prospects compare you to wrong competitors, or you face price pressure despite a good product. Covers competitive alternatives, unique attributes, value themes, target market characteristics, market category (Head to Head / Big Fish Small Pond / New Game), and trend layering.

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Create animated, explorable editorial diagrams in 45 types (architecture, flowchart, sequence, state, ER, DB schema, UML class, swimlane, timeline, gantt, journey, tree, org chart, nested, venn, quadrant, fishbone, wardley, bar, line, scatter, sankey, treemap, heatmap, 3D isometric objects, floor plans and exploded views) as standalone HTML from a short JSON spec. Use when the user asks to draw, diagram, chart or visualize a system, codebase, flow, process, API call sequence, hierarchy, data or a physical object (a chair); to convert Mermaid, Graphviz/DOT, PlantUML, D2, draw.io, Excalidraw, SQL or CSV into a clean diagram; or to export a diagram as PNG, JPEG, SVG, GIF or MP4. Also for everyday plans: trips, moves, job hunts, approvals, budgets, where money goes.

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Structured peer review for analytical work. Use when reviewing teammates' analysis, providing constructive feedback, or establishing analysis quality standards.

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Create standardized metadata for data assets. Use when documenting new datasets, building data catalogs, improving data discoverability, or creating data dictionaries for teams.

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Transform data findings into compelling insights. Use when converting analysis results into actionable insights, connecting findings to business impact, or preparing insights for stakeholder communication.

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Design specifications for effective dashboards. Use when planning new dashboards, improving existing ones, or documenting dashboard requirements before development starts.

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Standard business metric calculation with industry benchmarks. Use when calculating SaaS metrics (MRR, churn, LTV, CAC), e-commerce KPIs, or product analytics metrics with proper definitions.

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Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.

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Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.

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Build compelling data-driven narratives. Use when presenting analysis results, creating stakeholder reports, or transforming a set of findings into a story that drives a specific decision or action.

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Pre-delivery quality assurance for analysis work. Use when reviewing analysis before sharing with stakeholders, checking for completeness, validating assumptions, or ensuring clarity of recommendations.

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Efficiently package context for AI-assisted analysis. Use when preparing to work with Claude on analysis, organizing context documents, or structuring prompts for complex analytical tasks.

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Customer/user segmentation with actionable insights. Use when identifying distinct customer groups, analyzing segment-specific behavior, profiling high-value segments, or testing segmentation hypotheses.

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Estimate and communicate business impact of insights. Use when sizing opportunities discovered in analysis, calculating ROI of recommended actions, or prioritizing initiatives by potential impact.

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Create concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats for senior audiences.

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Create effective, publication-ready data visualizations. Use when choosing chart types, designing presentation visuals, building dashboard charts, or applying visual design best practices to data output.

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Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, comparing segments through a funnel, or optimizing user journeys.

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Translate SQL queries into plain language business logic. Use when documenting queries, explaining analysis to non-technical stakeholders, code reviewing for correctness, or building a query catalog.

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Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.

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Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models for planning.

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Trace and resolve discrepancies when the same metric shows different values in two or more sources. Use before reporting, after pipeline changes, or when stakeholders question a number.

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SQL query review for correctness, performance, and best practices. Activate when a query needs review before production use, shows unexpected results, or runs too slowly.

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