「experiment」の検索結果

Use when a task needs the judgment of a Bioinformatics Scientist — designing a differential-expression or GWAS analysis with correct multiple-testing correction, calling and triaging variants from NGS data using genotype-likelihood confidence rather than raw allele counts, interpreting a BLAST/DIAMOND homology search, choosing or building a genomics pipeline (aligner, caller, normalization method) for a specific data-generating process, or judging whether a computational-biology analysis's statistical design actually supports the biological claim being made. Distinct from a bioinformatics-technician (executes and QC-gates an established pipeline someone else designed) and a data-scientist (general product/experimentation judgment, not genomics-specific statistics) — this role owns which method and statistical model a genomics question requires, and why.

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Use when a task needs the judgment of a Biologist — designing a study and identifying its true experimental unit before data collection starts, running a power analysis to size a sample, judging whether a published or preclinical finding warrants trust without independent replication, sequencing IACUC/IBC/field-permit approvals before biosafety or wildlife work begins, or scoping a grant-funded research plan against realistic funding odds.

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Build comprehensive chromatin accessibility maps by aggregating ATAC-seq and DNase-seq narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is chromatin accessible in my tissue?" by combining peak calls into a union peak set. Handles cross-lab variation, ATAC vs DNase platform differences, and ENCODE blocklist filtering.

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Find and work with ENCODE single-cell genomics data including scRNA-seq and scATAC-seq. Use when the user asks about single-cell experiments, cell type resolution, clustering from ENCODE data, deconvolution of bulk signals using single-cell references, or comparing single-cell vs bulk profiles. Covers platform differences (10X Chromium, Smart-seq2, Drop-seq), quality limitations of single-cell data, multimodal integration (RNA+ATAC), and cross-study reproducibility concerns. Also use for cell type annotation, gene detection limits, dropout artifacts, and single-cell data structure in ENCODE.

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Search and explore ENCODE Project genomics data. Use when the user wants to find experiments, files, or explore what data is available for specific assays, organs, cell lines, or targets.

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Compare ENCODE experiments across different biosamples, tissues, or cell lines to identify tissue-specific regulatory patterns. Use when the user wants cross-tissue comparison, cell-type comparison, tissue-specific elements, differential chromatin, biosample matching, disease vs normal comparison, developmental time course, constitutive vs variable regulation, or multi-tissue data availability mapping. Handles batch effect detection, biosample hierarchy, and comparison design.

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Download ENCODE genomics files (BED, FASTQ, BAM, bigWig, etc.) to the user's machine. Use when the user wants to download data files from ENCODE experiments.

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Build comprehensive chromatin contact maps by aggregating Hi-C loop calls (BEDPE) across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "what regions are in 3D contact in my tissue?" by creating a union catalog of chromatin loops. Handles resolution-aware anchor matching, cross-lab variation, and Hi-C-specific quality metrics.

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Build comprehensive histone mark maps by aggregating narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is this histone mark present in my tissue?" by combining peak calls from multiple studies into a union peak set with confidence annotations. Handles cross-lab batch effects, broad vs narrow marks, and ENCODE blocklist filtering.

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Guide for integrating CellxGene Census single-cell data with ENCODE bulk experiments. Use when users need cell-type-specific expression context for ENCODE regulatory data, want to deconvolve bulk ENCODE signals, or validate regulatory elements at single-cell resolution. Trigger on: CellxGene, single-cell atlas, cell type expression, Census, cell type specificity, single-cell context, scRNA-seq atlas.

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Build comprehensive DNA methylation maps by aggregating WGBS (Whole Genome Bisulfite Sequencing) data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is DNA methylated/unmethylated in my tissue?" by combining per-CpG methylation data into tissue-level methylation profiles. Handles coverage filtering, identifies hypomethylated regions (HMRs) and partially methylated domains (PMDs), and manages cross-lab variation.

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Cross-reference ENCODE data with PubMed, bioRxiv, ClinicalTrials.gov, Open Targets, GTEx, ClinVar, GWAS Catalog, gnomAD, Ensembl, and other scientific databases. Use when the user wants to find publications, preprints, or clinical trials related to ENCODE experiments, chain ENCODE data with other scientific MCP servers, or build translational pipelines from genomic data to clinical application.

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Archive a completed OpenSpec change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete. Also use when the user says "openspec archive" or "opsx archive".

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Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

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。

Flow cytometry experimental design and analysis — panel design, compensation, gating, and QC.

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Increase conversion rates — CRO audits, A/B testing, landing page optimization, and experimentation programs.

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Practical computational and experimental chemistry workflows — cheminformatics, quantum chemistry, kinetics, and analytical methods.

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Chaos engineering — designing safe failure-injection experiments to build resilience — use when proactively testing system robustness.

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Bulk RNA-seq differential expression — experimental design, count modeling with DESeq2/edgeR, and enrichment.

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Analyzing behavioral experiment data — RT/accuracy preprocessing, mixed-effects models, and robust inference.

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Create, write, or manage Meta ads and assets: ad copy, campaigns, spend, reports, audiences, catalogs, product feeds, feed refresh schedules, experiments, and policy. Always load for any request to create or write an ad, or to advertise a product or service, even when no platform is named; this includes sensitive or restricted categories. Always load for any question asking what a Meta, Facebook, or Instagram advertising policy means, allows, prohibits, or requires, including a standalone policy-definition question with no account context. Those questions must use ads_policy_tool, never browser search or memory. Load for a specifically named catalog or feed with an upload or refresh-schedule request; use Ads reads to resolve ownership before writing. Generic unnamed feeds need context. Whether an image, claim or piece of copy may be used in an ad is ALWAYS a Meta Ads task — 'can I use this in an ad', 'is it allowed', 'is this against policy', and any rights, likeness, celebrity, logo or trademark question about advertising with an image, including a follow-up about one just generated. Those are ads-policy questions, not general legal ones. An ad request uses the campaign workflow unless explicitly only an image or organic post.

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Evidence-first academic research workflow for topic ideation, scholarly search, paper reading, literature and systematic reviews, study and experiment design, statistics and data analysis, scientific figures, manuscript drafting and polishing, citation checks, peer review, rebuttals, submission packages, theses, and paper-to-presentation work. Use when an agent must plan, execute, audit, write, revise, or package research while keeping claims traceable to verified sources, data, analysis, or official requirements.

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Design a research study. Use when the user says "study design", "design my research", "what research method should I use", "how do I test this hypothesis", "research plan", "methodology section", "experimental design", "survey design", "qualitative study design", "how to structure my study", "sample size", "data collection plan", or needs to plan how to test a research question or hypothesis - even if they don't explicitly say "study design".

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Rate any product, feature, or experience on the 11-star scale (Brian Chesky's Airbnb thought experiment). Use when user says "rate this experience", "11-star", "star rating", "experience audit", "how good is this", "experience rating", "product audit", "quality assessment", or wants to evaluate product quality and identify improvement paths. Also trigger when user wants to benchmark a feature, assess where a product stands, or map out what "great" looks like - even if they don't explicitly say "11-star".

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。