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Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
中文简介正在准备中。当前显示原文说明。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
中文简介正在准备中。当前显示原文说明。
Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
中文简介正在准备中。当前显示原文说明。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
中文简介正在准备中。当前显示原文说明。
Total-loss determination and settlement pricing. Triggers: "total loss valuation", "claims value", "settlement offer", "salvage estimate", "insurance claim pricing", "total loss threshold", "what's the claim worth", "settlement range", "pre-loss value", "diminished value", "total loss determination", insurance claim vehicle valuation, total-loss determination, settlement pricing, or salvage value estimation.
中文简介正在准备中。当前显示原文说明。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
中文简介正在准备中。当前显示原文说明。
Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
中文简介正在准备中。当前显示原文说明。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
中文简介正在准备中。当前显示原文说明。
Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
中文简介正在准备中。当前显示原文说明。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
中文简介正在准备中。当前显示原文说明。
Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
中文简介正在准备中。当前显示原文说明。
Review cross-origin isolation, a browser security mode required by features such as SharedArrayBuffer. Check response headers and external resources, identify integrations that could break, and verify that isolation actually works in the browser.
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Review quarterly updates and financials across portfolio companies to identify practical AI opportunities. Rank them by estimated profit impact, speed, and feasibility, then outline first steps and approaches that other companies can reuse.
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Screen dependency names on npm, PyPI, and crates.io before installation to find lookalikes of legitimate packages. This skill compares spelling patterns and registry metadata, helping review AI-generated lists, lockfile changes, and new dependencies in CI/CD.
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Connect security incidents across organizations by comparing attack indicators, techniques, and timelines. Build relationship graphs and campaign reports that document shared evidence, attribution confidence, and indicators useful for detection.
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Configure Google Cloud logs across multiple projects, either by storing them centrally or querying them together where they already reside. The skill guides routing, access permissions, and log views, and helps diagnose missing logs and permission failures.
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Monitor model training through WandB metrics to detect invalid numbers, worsening loss, and declining evaluation results. Ambiguous trends receive a Codex review, while stopped runs retain key metrics and the reason for stopping.
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Build holaOS apps for connecting external services or managing work through a dashboard. The skill uses shared SDK building blocks for stored records, actions, and synchronization, with the dashboard and agent tools working on the same data.
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Run independent development tasks in parallel, each with a separate git worktree and implementation agent. Each agent opens its own pull request, which receives cross-review before being handed to a human for review and merging.
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Build stablecoin transfers where the amount sent equals the amount received using LI.FI Intents. The skill covers quotes, token approval, escrow deposits, and order tracking for transfers within or across supported blockchains.
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Search for social media profiles associated with a person, brand, or business across platforms including Facebook, Twitter, Instagram, LinkedIn, and TikTok. Receive a downloadable CSV with profile links, follower counts, page titles, and description snippets.
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Find social media profiles through Google using a person’s name, brand name, or username. Collect platform names, profile links, usernames, description snippets, and follower counts where they appear in search results.
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Coordinate work across independent Squad installations by discovering their capabilities and delegating tasks across repositories. It guides context sharing, acceptance criteria, and progress tracking, while distinguishing persistent Squad teams from temporary groups of agents.
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Coordinate independent Squad AI teams across repositories using procedures for questions, review requests, and task delegation. Choose between direct CLI sessions, reading team metadata, and asynchronous requests based on repository access and task needs.
中文简介正在准备中。当前显示英语简介。