Education Profile

  • BSc, Computer Science, Royal Holloway University of London, 2012
  • MSc, Advanced Computing, Imperial College London, 2013
  • Ph.D., Computer Science, KAUST, Thuwal, Saudi Arabia, 2014

Honors & Awards

​Following awards were received at Royal Holloway.

  • The Lilian F Heather Prize – This is given to students that carried out excellent work in the year 1.
  • Annual Driver Prize – This is given to the best first year student.
  • Martin-Holloway prize – This is given to best single honours finalist in each faculty.

Received at KAUST:

  • CEMSE Dean Award

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, Chechen State University, Grozny, Russia

Selected Publications

Umarov, R. K., & Solovyev, V. V. (2017). Recognition of prokaryotic and eukaryotic promoters using convolutional deep learning neural networks. PLOS ONE, 12(2), e0171410. doi:10.1371/journal.pone.0171410
Shahmuradov, I. A., Umarov, R. K., & Solovyev, V. V. (2017). TSSPlant: a new tool for prediction of plant Pol II promoters. Nucleic Acids Research, gkw1353. doi:10.1093/nar/gkw1353
Dai, H., Umarov, R., Kuwahara, H., Li, Y., Song, L., & Gao, X. (2017). Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape. Bioinformatics, 33(22), 3575–3583. doi:10.1093/bioinformatics/btx480
Li, Y., Wang, S., Umarov, R., Xie, B., Fan, M., Li, L., & Gao, X. (2017). DEEPre: sequence-based enzyme EC number prediction by deep learning. Bioinformatics, 34(5), 760–769. doi:10.1093/bioinformatics/btx680
Kuwahara, H., Umarov, R., Almasri, I., & Gao, X. (2017). ACRE: Absolute concentration robustness exploration in module-based combinatorial networks. Synthetic Biology, 2(1). doi:10.1093/synbio/ysx001