About Ramzan Umarov Ramzan Umarov Ph.D. Student, Computer Science machine learning Deep learning Ramzan is a PhD candidate, working on solving biological problems by using applied machine learning with focus on deep learning. He has developed deep learning based methods to solve bioinformatics problems achieving state-of-the-art performance, focusing on various aspects of gene regulation. Umarov obtained his Master degree from Imperial College London, Advanced Computing course. Research Interests The main research interest of Ramzan Umarov is applied machine learning especially Deep Learning. Professional Profile 2011-2012, Programmer, Softberry, Mount Kisko, NY, USA 2013-2014, Programmer Articles Related News July 2017 Our work on developing deep learning method for binding affinity prediction accepted by Bioinformatics (Sequence2Vec) 1 min read · Mon, Jul 24 2017 News Deep learning Congratulates Ramzan, Hiro, and Yu on their work on developing a novel method that combines the strength of probabilistic graphical models, Hilbert space embedding, and deep learning to model binding affinity of transcription factors which was accepted by Bioinformatics.
Our work on developing deep learning method for binding affinity prediction accepted by Bioinformatics (Sequence2Vec) 1 min read · Mon, Jul 24 2017 News Deep learning Congratulates Ramzan, Hiro, and Yu on their work on developing a novel method that combines the strength of probabilistic graphical models, Hilbert space embedding, and deep learning to model binding affinity of transcription factors which was accepted by Bioinformatics.
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