「info」の検索結果

Predict TCR-epitope specificity using ERGO-II and deep learning models for T-cell receptor antigen recognition. Match TCRs to their cognate epitopes or predict TCR targets. Use when analyzing TCR repertoire specificity or identifying antigen-reactive T-cells.

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Predict peptide-MHC class I and II binding affinity using MHCflurry and NetMHCpan neural network models. Identify potential T-cell epitopes from protein sequences. Use when predicting MHC binding for vaccine design or neoantigen identification.

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Score and prioritize neoantigens and epitopes for immunogenicity using multi-factor models combining MHC binding, processing, expression, and sequence features. Rank candidates for vaccine design. Use when prioritizing epitopes for vaccine development or identifying the most immunogenic neoantigens.

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Identify tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient HLA and may elicit T-cell responses. Use when identifying vaccine targets or checkpoint inhibitor response biomarkers from tumor sequencing data.

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Predict B-cell and T-cell epitopes using BepiPred, IEDB tools, and structure-based methods for vaccine and antibody design. Identify immunogenic regions in antigens. Use when designing vaccines, mapping antibody binding sites, or predicting immunogenic peptides.

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Bisulfite sequencing read alignment using Bismark with bowtie2/hisat2. Handles genome preparation and produces BAM files with methylation information. Use when aligning WGBS, RRBS, or other bisulfite-converted sequencing reads to a reference genome.

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Query myvariant.info API for aggregated variant annotations from multiple databases (ClinVar, gnomAD, dbSNP, COSMIC, etc.) in a single request. Use when annotating variants with clinical and population data from multiple sources simultaneously.

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Query dbSNP for rsID lookups, variant annotations, and cross-references to other databases. Use when mapping between rsIDs and genomic coordinates or retrieving basic variant information.

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Researches a topic by breaking it into subtopics, gathering factual information with reasoning, and producing a structured summary with key findings and open questions. Use when the user asks to research, investigate, look up, summarize a topic, or says 'what is known about...' or 'learn about...'

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Advanced web search using Tavily API for current information retrieval

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Ingest a raw source document into the wiki. Reads the source, extracts key information, creates or updates wiki pages, maintains cross-references, and logs the operation. Use when the user adds a new source or says 'ingest this'.

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Use when the user asks to "personalize the email", "add merge tags / dynamic content", "set up conditional blocks per segment", or "make first-name and product-recommendation fields fall back safely"; produces a merge-tag map with per-tag fallbacks, conditional-block rules with per-segment variations, a fallback-safety audit, and a PII guard on what may render, informing the SEND E (Engagement/personalization) dimension. Not for building the segments — use list-segment-builder; not for writing the base copy — use email-creative-builder; not for scoring EQS or running vetoes — use email-quality-auditor. 邮件个性化/合并标签/条件内容块/兜底默认值

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Use when the user asks to "build audience segments from my customer list", "make value-based / lookalike seed lists", "set up exclusion / suppression segments", or "map audiences to funnel stages across platforms"; turns the user's OWN customer/CRM/GA4 export into seed audiences, value-based lookalike SEED lists, exclusion/suppression segments, and a cross-platform funnel-stage targeting map, informing the ROAS A (Audience) dimension. Not for building account structure or match types — use campaign-architect; not for organic SERP intent — use keyword-research. 付费广告受众分群/种子人群/排除人群/相似人群种子

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Use when the user asks to "build email segments from my list", "make engaged / lapsed / RFM segments", "set up cart-abandoner or lifecycle-stage audiences", or "build a suppression list of unsubscribes and bounces"; turns the user's OWN list/CRM/GA4/ecommerce export into behavioral, attribute, and lifecycle-stage segments plus a suppression list, with per-segment sizes labeled Measured/Estimated, informing the SEND E (Engagement/targeting) dimension. Not for scoring EQS or running vetoes — use email-quality-auditor; not for authentication or spam-content checks — use deliverability-qa. 邮件列表分群/生命周期分群/抑制名单/流失召回

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Use when the user asks to "optimize my Shopping feed", "fix product disapprovals", "improve product titles/attributes", or "build feed-driven PMax asset groups"; audits and rewrites the Shopping/Performance Max product feed — title/description patterns, required and recommended attributes, GTIN/availability/price hygiene, disapproval triage, and feed-driven asset-group / listing-group structure — informing the ROAS O (Offer) dimension. Not for text ad copy — use ad-creative-builder; not for scoring the account or the RQS — use ad-account-auditor. 商品Feed优化/购物广告Feed/商品标题优化/商品禁投修复

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Critique a rendered screen's density — cognitive load, content prioritisation, scanning patterns, and progressive disclosure. Use when a screen feels overwhelming. For the underlying choice-count principle, use `hicks-law` (interaction-design).

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Select and design a navigation pattern — tabs, drawer, hierarchy, or hub — matched to product structure and user tasks. Use when choosing how users move between sections. For the underlying content structure, use `information-architecture` (ux-strategy).

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Design content structure, hierarchy, labelling, and the navigation model. Use when organising what exists. For the UI that exposes it use `navigation-patterns` (interaction-design); for user-generated grouping evidence use `card-sort-analysis` (design-research).

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Apply Miller's Law — chunk information into groups of about four to fit working memory. Use when grouping fields, menu items, or steps. For reducing the number of choices offered, use `hicks-law`.

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Define what content a product needs, how it is structured, and who owns it. Use when content itself is the problem. For the words in the interface use `ux-writing` (designer-toolkit); for structural hierarchy use `information-architecture`.

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Analyse open or closed card sort results into a proposed grouping and label set. Use after running a sort study. For turning that evidence into a full structure, use `information-architecture` (ux-strategy).

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Render a self-contained HTML viewer for a pro-workflow wiki. Pages, sources, claims, seed queue, page-link graph and full-text search all in one file. No external dependencies, no JS framework, S3-uploadable. Use when the user wants to browse a wiki visually, share its current state with someone, audit research progress, or hand off a knowledge base. Inspired by Thariq Shihipar's "Unreasonable Effectiveness of HTML" — favors information density and shareability over markdown-only outputs.

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Builds, runs, debugs, and operates applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments running inside a container with up to 8 hr lifetimes. Applicable when workloads need strong isolation between tenants, isolated serverless compute, sandbox compute, or secure multi-tenant execution. Also suited for AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs, dev environments running user-supplied code), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, or isolated security scanners. Also applicable when the workload needs long-lived sessions, a real port-listening server (gRPC, WebSocket, custom TCP protocols), state preserved across periods of inactivity (suspend/resume), container-level access (FUSE, eBPF, custom syscalls), or session-affine routing.

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Audit a Python project's installed dependencies for known CVEs by wrapping pip-audit (PyPA's official vulnerability auditor) and emitting findings in the canonical penetration-tester schema. Detects vulnerable direct AND transitive packages, normalizes pip-audit's severity output via OSV severity bands, falls back to pip list --outdated when pip-audit isn't installed, and supports requirements.txt, pyproject.toml (PEP 621), Pipfile.lock, and poetry.lock as input sources. Use when: pre-merge gate on a Python project, post-incident sweep after a PyPI compromise (e.g. ctx, request-toolbelt typosquats, ultralytics 8.3.42 compromise), SOC2 evidence collection, or inheriting an unfamiliar Python codebase. Threshold: any HIGH or CRITICAL CVE in the resolved dependency tree. MODERATE / LOW reported informationally. Trigger with: "audit python deps", "pip vulnerability scan", "check pypi packages for CVEs", "pip-audit run".

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