Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Detect introgression and admixture between species or populations using Dsuite (Malinsky 2021 fast D-statistics), Patterson's D / ABBA-BABA test (Green 2010; Durand 2011), f4-ratio and f-branch statistic (Malinsky 2018), TreeMix (Pickrell & Pritchard 2012), HyDe (Blischak 2018), QuIBL (Edelman 2019), sprime (Browning 2018), Twisst (Martin 2017), PhyloNet (Than 2008) for explicit phylogenetic networks, and qpAdm / qpGraph (Patterson 2012). Distinguish introgression from incomplete lineage sorting (ILS), ancestral structure, ghost-lineage admixture, and rate variation. Use when testing inter-species gene flow, dating admixture events, identifying introgressed segments, building phylogenetic networks for reticulate evolution, or applying the ABBAclustering (Koppetsch-Malinsky-Matschiner 2024) framework for divergent-species gene flow.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine claims.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Track complex, multi-session work with dependency graphs using bd (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
This skill recommends computed tomography (CT) as the initial imaging modality for primary aldosteronism (PA) evaluation in Japan, citing its accessibility and comparable performance to MRI. It is triggered when a clinician orders imaging for suspected PA and asks 'What imaging should I start with?' or seeks a cost-effective initial evaluation.
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。
dromlakhani/MD2SKILL☆ 142026年10月5日 更新
Work a primary-prevention patient through the 2026 ACC/AHA multisociety dyslipidaemia guideline CPR framework — Calculate (10-year and 30-year PREVENT-ASCVD), Classify (low / borderline / intermediate / high), Personalize (demographic, clinical, biomarker, and reproductive risk enhancers), and Reclassify (coronary artery calcium scoring where appropriate). Use when a clinician asks how to assess ASCVD risk for primary prevention, who needs a statin, borderline risk patient what to do, intermediate risk should I start a statin, risk enhancers to look for, premature family history of ASCVD how does it change risk, pregnancy-related risk factors, PCOS and cardiovascular risk. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.
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。
dromlakhani/MD2SKILL☆ 142026年10月5日 更新
Draft a Workflow Phase 4 technical spec from an intake (and optionally a BRD + scout + research memo). The spec defines how the system will change: design (C4 + UML + dependency graph in PlantUML), data, APIs, tests, rollout, rollback. Output lives at `docs/specs/<slug>.md`. Never self-approves — approval happens via `/approve-direction`.
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。
friedbotstudio/baseline☆ 142026年10月13日 更新
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
friedbotstudio/baseline☆ 142026年10月13日 更新
Propose the next dependency-ready sprint from the ALREADY-DECOMPOSED roadmap — standup's active sibling. Reads docs/roadmap-execution-plan.md + the memory backlog, computes per-task readiness from the roadmap's machine-readable status, orders with roadmap-planner's graph engine, and emits a proposed task-set (sprint-plan manifest shape) with per-feature done-criteria, excluding unready tasks and naming their unmet prerequisite. PROPOSES ONLY — the human confirms/edits before /triage routes it (typically to the `power` track). Distinct from `sprint-plan`, which decomposes a fresh vision.
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。
friedbotstudio/baseline☆ 142026年10月13日 更新
Azure Key Vault Keys SDK for Rust. Use for creating, managing, and using cryptographic keys. Triggers: "keyvault keys rust", "KeyClient rust", "create key rust", "encrypt rust", "sign rust".
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
API security testing workflow for REST and GraphQL APIs covering authentication, authorization, rate limiting, input validation, and security best practices.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Generate hand-drawn 16:9 article illustrations with the Grav character IP, sparse annotations, and absurd but clear visual metaphors.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers and stand the test of time.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Geracao de imagens humanizadas via Google AI Studio (Gemini). Fotos realistas estilo influencer ou educacional com iluminacao natural e imperfeicoes sutis.
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。
sinhoneyy/master-skills☆ 142026年9月5日 更新
Use when designing, reviewing, refactoring, or enforcing Angular application architecture with isolated lazy features, eager core/layout, reusable ui/pattern architecture building blocks, one-way dependency graphs, eslint-plugin-boundaries rules, or folder placement decisions. This skill takes precedence over angular-developer when architecture rules conflict with general Angular advice.
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。
angular-experts-io/ax-skills☆ 142026年5月21日 更新