BindSpace decodes transcription factor binding signals by large-scale sequence embedding.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 31406384.
- Also identified by DOI 10.1038/s41592-019-0511-y and PMC identifier 6717532.
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Abstract
The decoding of transcription factor (TF) binding signals in genomic DNA is a fundamental problem. Here we present a prediction model called BindSpace that learns to embed DNA sequences and TF labels into the same space. By training on binding data from hundreds of TFs and embedding over 1 M DNA sequences, BindSpace achieves state-of-the-art multiclass binding prediction performance, in vitro and in vivo, and can distinguish between signals of closely related TFs.
Medical subject headings
- Algorithms
- Computational Biology
- DNA
- Machine Learning
- Transcription Factors