Results for “scembed”

3 skills

Alterlab Geniml

Machine learning on genomic interval data (BED files) with the geniml Python package — region embeddings (Region2Vec), joint region+metadata embeddings (BEDspace/StarSpace), single-cell ATAC-seq embeddings (scEmbed), consensus peak sets / universes (build-universe), tokenization, BEDshift randomization, and BBClient/BEDbase caching. Use when training or using region/cell embeddings, clustering scATAC-seq, building a tokenization universe from BED collections, or any ML/feature-learning task over genomic regions. NOT for plain interval arithmetic (overlap/intersect/merge counts) — that is gtars, not geniml. Part of the AlterLab Academic Skills suite.

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brycewang-stanford

Synthetic Control

Econometrics skill for Synthetic Control Method (SCM). Activates when the user asks about: "synthetic control", "SCM", "synthetic counterfactual", "donor pool", "placebo test", "in-space placebo", "in-time placebo", "MSPE ratio", "Abadie Diamond Hainmueller", "augmented synthetic control", "penalized SCM", "synthetic DID", "合成控制", "合成控制法", "捐助池", "安慰剂检验", "合成反事实", "合成DID", "政策评估"

Cadence Builder

Turn a segment into a multi-touch, multi-channel cadence that holds together. Steps, timing, channel, and the intent of each touch, tuned to who you are chasing. No 12 identical emails. Built for B2B SDRs and sales teams, customizable to your segment, channels, and sequencer. Trigger on "build an outbound cadence", "design a sequence", "how many touches over how many days", "multi-channel cadence for this segment", or any sequence design task.