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「integration」の検索結果

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概要と使いどころ

SDK installation and setup patterns for Agent-to-Agent Protocol across Python, TypeScript, Java, C#, and Go. Use when implementing A2A protocol, setting up SDKs, configuring authentication, or when user mentions SDK installation, language-specific setup, or A2A integration.

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。

aibot88/sec_skill_store42026年5月27日 更新

Implement security best practices for TwinMind integrations. Use when securing API keys, configuring privacy settings, or implementing data protection for meeting recordings. Trigger with phrases like "twinmind security", "secure twinmind", "twinmind privacy", "protect twinmind data", "twinmind api key security".

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。

aibot88/sec_skill_store42026年5月27日 更新

1password

無料

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.

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。

aibot88/sec_skill_store42026年5月27日 更新

Generates RESTful API Controllers with proper routing, versioning, authorization, and MediatR integration. Follows REST conventions and Clean Architecture patterns.

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。

aibot88/sec_skill_store42026年5月27日 更新

1password

無料

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.

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。

aibot88/sec_skill_store42026年5月27日 更新

windows-platform-integration

無料日本語概要

Windows アプリ開発 (Windows App SDK / WinRT) の OS 統合 API リファレンス。 DeviceInformation, DeviceWatcher, センサー (Accelerometer, Gyrometer, Compass, OrientationSensor, Pedometer, ActivitySensor), Bluetooth LE, USB, Serial, HID, Battery, HttpClient, StreamSocket, WebSocket, BackgroundDownloader/Uploader, NetworkInformation, PointerInput, KeyboardInput, FocusManager, DragAndDrop, IME/TextInput, Calendar, DateTimeFormatter, CurrencyFormatter, ResourceLoader (多言語化・地域化), PasswordVault, CryptographicBuffer, WindowsHello/Passkeys, WebAuthenticationBroker, Clipboard, DataTransferManager, Launcher, JumpList, TaskbarManager, SecondaryTile, StartupTask, ProtocolActivation。

Fandhe-AI/agent-reference-skills42026年10月13日 更新

Philosophy-first writing partner for Medium with tactical depth. Combines human storytelling values with production-ready technical content tools. Six content modes based on staff pick analysis, mode-specific quality gates, evidence requirements, annotated examples, and comprehensive scripts integration. Designed for sustainable practice, not algorithm gaming.

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。

alirezarezvani/medium-content42026年4月11日 更新

Orders and orients assembled contigs into chromosome-scale scaffolds from long-range linking data, inserting N-gap spacers (adds no sequence). Covers Hi-C/Omni-C scaffolding (YaHS, SALSA2, 3D-DNA/Juicer), Hi-C read-mapping prerequisites (map each end separately, no mate rescue, dedup, enzyme-aware), reading the contact map for misjoins/inversions/false-duplications, manual curation in Juicebox/PretextView (the VGP/DToL standard), reference-guided scaffolding (RagTag) and its karyotype-erasure hazard, genetic-map (ALLMAPS) and Bionano optical-map integration, chimera-breaking before scaffolding, gap-filling, and telomere/contig-vs-scaffold-N50 QC (tidk). Use when turning contigs into chromosomes with Hi-C, integrating a linkage map or optical map, choosing a scaffolder by available linking data, or judging whether a chromosome-scale assembly is trustworthy.

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。

peacezha/TRACE32026年10月13日 更新

Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small gotchas that distinguish reproducible matplotlib from notebook scratch. Use when producing publication figures in Python — RNA-seq scatter, single-cell embeddings, generic biological plotting.

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。

peacezha/TRACE32026年10月13日 更新

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.

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。

peacezha/TRACE32026年10月13日 更新

Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Li & Hart 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving 2-3x sensitivity over MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

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。

peacezha/TRACE32026年10月13日 更新

Calculates tumor mutational burden from WES/WGS/panel data with Friends of Cancer Research harmonization equations, per-assay calibration (FDA 10/Mb = 7.8 TSO500 = 8.4 OncomineTML), synonymous/indel/germline filtering, hypermutator tiering, blood TMB, and integration with HLA-LOH and neoantigen quality (Luksza 2017 fitness). Use when assessing ICI eligibility under tumor-specific cutoffs (McGrail 2021), comparing tissue vs bTMB, or auditing TMB-H reporting against ESMO 2024 and FDA pembrolizumab pan-tumor 2020.

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。

peacezha/TRACE32026年10月13日 更新

Call copy number variants with the GATK best-practices workflows — the somatic CNV pipeline (CollectReadCounts, DenoiseReadCounts with tangent normalization, ModelSegments, CallCopyRatioSegments) and the germline GATK-gCNV pipeline (DetermineGermlineContigPloidy, GermlineCNVCaller cohort/case mode, PostprocessGermlineCNVCalls). Covers panel-of-normals construction, AnnotateIntervals/FilterIntervals, allelic-count integration, and QS-based filtering. Use when integrating CNV calling into a GATK variant pipeline, calling rare germline CNVs from an exome cohort, deciding between the somatic and germline GATK workflows, or diagnosing why tangent normalization removed a real event or why gCNV output has low precision.

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。

peacezha/TRACE32026年10月13日 更新

Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.

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。

peacezha/TRACE32026年10月13日 更新

Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.

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。

peacezha/TRACE32026年10月13日 更新

Provider account and authenticator setup through Matrx Vault. Use when creating a service account, saving its login, enrolling 2FA, or verifying agent sign-in with Vault credentials.

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。

armanisadeghi/ai-matrx32026年10月14日 更新

Provides JWT authentication and authorization patterns for Spring Boot 3.5.x covering token generation with JJWT, Bearer/cookie authentication, database/OAuth2 integration, and RBAC/permission-based access control using Spring Security 6.x. Use when implementing authentication or authorization in Spring Boot applications.

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。

lgzarturo/springboot-course32026年10月12日 更新

Provides expert knowledge of the testing pyramid, test design principles, MockK patterns, and integration testing conventions for Spring Boot + Kotlin projects.

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。

lgzarturo/springboot-course32026年10月12日 更新

Generate a structured test plan for a feature or module — covers unit, integration, contract, and edge cases without writing implementation code.

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。

lgzarturo/springboot-course32026年10月12日 更新

Provides Spring Data Neo4j integration patterns for Spring Boot applications. Use when you need to work with a graph database, Neo4j nodes and relationships, Cypher queries, or Spring Data Neo4j. Creates node entities with @Node annotation, defines relationships with @Relationship, writes Cypher queries using @Query, configures imperative and reactive Neo4j repositories, implements graph traversal patterns, and sets up testing with embedded databases.

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。

lgzarturo/springboot-course32026年10月12日 更新

Provides expert knowledge of the testing pyramid, test design principles, MockK patterns, and integration testing conventions for Spring Boot + Kotlin projects.

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。

lgzarturo/springboot-course32026年10月12日 更新

Provides comprehensive testing patterns for Spring Boot applications covering unit, integration, slice, and container-based testing with JUnit 5, Mockito, Testcontainers, and performance optimization. Use when writing tests, @Test methods, @MockBean mocks, or implementing test suites for Spring Boot applications.

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。

lgzarturo/springboot-course32026年10月12日 更新

Harden LLM and agent integrations you operate: prompt injection, tool allowlists, secret leakage, and supply-chain of models. Defensive only.

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。

lgzarturo/springboot-course32026年10月12日 更新

Generates Spring Boot 3.x configurations, creates REST controllers, implements Spring Security 6 authentication flows, sets up Spring Data JPA repositories, and configures reactive WebFlux endpoints. Use when building Spring Boot 3.x applications, microservices, or reactive Java applications; invoke for Spring Data JPA, Spring Security 6, WebFlux, Spring Cloud integration, Java REST API design, or Microservices Java architecture.

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。

lgzarturo/springboot-course32026年10月12日 更新