Identifying transcription factor-dna interactions using machine learning

HIGHLIGHTS

• who: Harikrishnan k from the Institute of Bioinformatics, University of Georgia, Athens, GA, USA have published the research work: Identifying transcription factor-DNA interactions using machine learning, in the Journal: (JOURNAL)
• what: The authors use the well characterized Auxin Response Factor (ARF) family of TFs to build predictive models for detection of TF-DNA interactions. Considering maize is a monocot and soybean is a dicot, which have significant time since divergence (Chaw, et_al, 2004), if the model can successfully predict TF:DNA interactions in soybean it would provide strong evidence that this model can be . . .
  

   

  

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