「traction」の検索結果

Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and Reaction templates, with explicit handling of atom mapping, template extraction (RDKit reaction mining), product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction data.

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Turns untargeted LC-MS/MS features (m/z, RT, MS/MS) into confidence-stratified metabolite annotations using spectral-library matching (matchms), in-silico tools (SIRIUS/CSI:FingerID, MetFrag) and molecular networking, and assigns a defensible MSI/Schymanski confidence level to each. Use when naming detected features, scoring MS/MS against a reference library, running SIRIUS, or deciding what confidence level an evidence set actually supports. For upstream feature extraction see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for downstream enrichment that must respect these levels see metabolomics/pathway-mapping; for lipid-specific structural annotation see metabolomics/lipidomics.

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Review Stellar Community Fund (SCF) Build Award applications. Use when evaluating SCF submissions, covering project fit assessment, technical architecture evaluation, team readiness, traction validation, budget analysis, and funding recommendations.

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Draft Stellar Community Fund Build Award applications interactively. Use when helping teams write their SCF submission — walks through project description, Stellar integration rationale, technical architecture, team section, deliverables, budget, and traction evidence. Produces a complete draft aligned with what funded projects look like.

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Build entity extraction systems for structured data from text. TRIGGERS - Use when user needs help with ai-entity-extractor related tasks.

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Design document processing pipelines for extraction and routing. TRIGGERS - Use when user needs help with ai-document-processor related tasks.

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Extract typed JSON from public website pages using a schema.

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Convert a contract PDF to clean markdown for clause extraction or LLM analysis.

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Download and transcribe videos from YouTube, Bilibili, TikTok and 1000+ platforms. Use when user requests video download, transcription (转录/字幕提取), or converting video to text/markdown. Supports quality selection, audio extraction, playlist downloads, cookie-based authentication, and AI-powered transcription via SiliconFlow API (免费转录).

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Advanced file management tools. Includes batch folder creation, batch file moving, file listing, and HTML author extraction.

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Configures JWT Bearer authentication for .NET APIs. Includes token generation, validation, refresh tokens, and user context extraction from claims.

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Keep GPT-5.6 and other coding-agent work proportional to the request by locking scope, choosing the smallest sufficient implementation, matching verification to risk, and stopping when success is proven. Use for implementations, bug fixes, refactors, reviews, or maintenance where scope creep, speculative abstractions, unrelated cleanup, repeated test runs, unnecessary dependencies, or polishing beyond the request are risks.

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Preprocess CLIP-seq reads (eCLIP, iCLIP, iCLIP2, iCLIP3, irCLIP, PAR-CLIP, FLASH) with protocol-specific UMI extraction, adapter trimming, length filtering, and post-alignment PCR-duplicate collapse. Use when raw CLIP FASTQ must be turned into deduplicated, crosslink-preserving BAM input for peak calling; choosing between two-pass and single-pass adapter trimming; deciding minimum read length; or mapping UMI patterns to specific eCLIP/iCLIP/iCLIP2/iCLIP3 library preps.

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Extracts and assigns COSMIC v3.4 mutational signatures (84 SBS / 11 DBS / 18 ID / 24 CN / 16 SV) from somatic VCFs using SigProfilerSuite, MutationalPatterns, MuSiCal mvNMF, SigNet, or HRDetect. Use when characterizing DNA-damage etiology (BRCA1/2 HRD, MMR-D, POLE, APOBEC3A, UV, tobacco, aflatoxin, 5-FU/SBS17b, platinum, colibactin SBS88), routing PARP inhibitor decisions, or auditing de novo extraction vs refit choice for cohort size.

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Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.

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Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.

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Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and Reaction templates, with explicit handling of atom mapping, template extraction (RDKit reaction mining), product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction data.

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Build image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.

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Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.

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AI-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your task.

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Provide comprehensive techniques for penetration testing AWS cloud enprojectnments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.

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Build natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.

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Run the combined AmeriFlux to EcoSIM extraction workflow for site metadata, NADP or tDEP atmospheric chemistry, gSSURGO soil data, and optional climate or grid NetCDF forcing. Use when building a complete site-specific EcoSIM input package.

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Download NASA GES DISC NLDAS_FORA0125_H version 2.0 primary hourly forcing data for a point location. Use when Codex needs to retrieve NLDAS File A meteorological forcing from the GES DISC API or HTTPS archive for a longitude/latitude pair, including Earthdata username/password authentication, hourly URL generation, nearest-grid-point extraction, CSV output, or EcoSIM climate-forcing preprocessing.

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