Results for “chromatin”
7 skills
levalencia Geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
3 · bundle
jackychenlu Geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
0 · bundle
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metinduraktr-44 Geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
0 · bundle
owl-listener Critique Color
Audits colour decisions on a screen for contrast ratios, palette coherence, semantic meaning, and accessibility, flagging deviations and recommending specific corrections.
1.7k
johnalbertini14-glitch Villain Mint
Mint a unique 1/1 villain NFT from CHUM's agent-only collection on Solana, with a 0.001 SOL mint fee plus network fees.
1 · bundle
kintsugi-programmer Clerk Custom UI
Custom authentication flows and component appearance - hooks (useSignIn, useSignUp), themes, colors, fonts, CSS. Use for custom sign-in/sign-up flows, appearance styling, visual customization, branding.
0 · bundle
chen-yu-hao Geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
5 · bundle