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Alisa Kumbara on Muck Rack

Alisa Kumbara

As seen in: BioRxiv
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Articles

Benchmarking PWM and SVM-based Models for Transcription Factor Binding Site Prediction: A Comparative Analysis on Synthetic and Biological Data

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By Manuel Tognon, Andrea Betti, Lorenzo Ruggeri Verified, Alisa Kumbara
| BioRxiv
Abstract Transcription Factors (TFs) are essential regulatory proteins that control the cellular transcriptional states by binding to specific DNA sequences known as Transcription Factor Binding Sites (TFBSs) or motifs. Accurate TFBS identification is crucial for unraveling regulatory mechanisms driving cellular dynamics. Over the years, various computational approaches have been developed to model TFBSs, with Position Weight Matrices (PWMs) being one of the most widely adopted methods.
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