Dr. Iman Dehzangi

Assistant Professor of Computer Science and Coordinator of the M.S. in Bioinformatics Program
Office Location: 
McMechen Hall 620
(443) 885-1730

Ph.D. Griffith University, Brisbane, Australia, 2015
M.S. MultiMedia University, Cyberjaya, Malaysia, 2011
B.S. Shiraz University, Shiraz, Iran, 2007


Ph.D. Griffith University, Brisbane, Australia, 2015
M.S. MultiMedia University, Cyberjaya, Malaysia, 2011
B.S. Shiraz University, Shiraz, Iran, 2007

Research Interests:

Dr. Abdollah Dehzangi joined as an Assistant Professor in the Computer Science Department at Morgan State University from Fall, 2017. He received his PhD in Bioinformatics and Computational biology from the Griffith University, Brisbane, Australia in 2015. During his PhD, he also served as Research Scholar at National ICT Australia (NICTA) from 2011 to 2014. After obtaining his PhD, he served as Research scholar at Griffith University (2014-2015) and later as a Post Doctoral Research Scholar at University of Iowa (2015-2017). He is also serving as the MS in bioinformatics program coordinator at MSU.

His research focus is on machine learning, artificial intelligence, and bioinformatics & computational biology in general. He would like to work on the challenges associated with the design and development of robust, general, and accurate systems for several important problems in bioinformatics and computational biology such as, protein local and global structure prediction, genome variants analysis, cancer subtype classification, and studying the impact of somatic mutations in cancer research, in specific. His main focus is on using machine learning techniques with emphasis on deep learning architecture, support vector machines, and ensemble classifiers (homogeneous and heterogeneous).

Dr. Dehzangi has published around 60 articles in refereed journals and conference proceedings, such as Bioinformatics, Scientific Report, PloS One, IEEE Transaction on Computational Biology and Bioinformatics, BMC Bioinformatics, BMC Genomics, Journal of Computational Chemistry, IEEE Transaction on NanoBioScience, Journal of Theoretical Biology etc. He also presented his works in several conferences and workshops, such as PRIB, ICONIP, IncoB, APBC, and ACIIDS over the years.

Additional Links:

Google Scholar:

Research Gate:

Selected Publications (Total: 65, h-Index = 23, I-index = 42, citations: 1503):

  • R. Muhammod, S. Ahmed, D. M. Farid, S. Shatabda, A. Sharma, A. Dehzangi. (2019), PyFeat: A Python-based Effective Features Generation Tool for DNA, RNA, and Protein Sequences. Bioinformatics, btz165
  • G. Taherzadeh, A. Dehzangi, M. Golchin, Y. Zhou, M. P. Campbell, (2019). SPRINT-Gly: Predicting N-and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties. Bioinformatics, btz215.
  • A. A. Chandra, A. Sharma, A. Dehzangi, T. Tsunoda. (2019). EvolStruct-Phogly: incorporating structural properties and evolutionary information from profile bigrams for the phosphoglycerylation prediction. BMC Genomics, 19(9), 984.
  • A. Sharma, A. Lysenko, Y. López, A. Dehzangi, R. Sharma, H. Reddy, A. Sattar, T. Tsunoda. (2019). HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acids residues. BMC Genomics, 19(9), 982.
  • H. M. Reddy, A. Sharma, A. Dehzangi, D. Shigemizu, A. Chandra, T. Tsunoda, T. (2019). GlyStruct: glycation prediction using structural properties of amino acid residues. BMC bioinformatics, 19(13), 547.
  • F. Rayhan, S. Ahmed, D. M. Farid, A. Dehzangi, S. Shatabda, (2019). CFSBoost: Cumulative feature subspace boosting for drug-target interaction prediction. Journal of theoretical biology, 464, 1-8.
  • A. Dehzangi, Y. López, G. Taherzadeh, A. Sharma, T. Tsunoda, (2018). “SumSec: Accurate Prediction of Sumoylation Sites Using Predicted Secondary Structure”. Molecules, 23(12), p.3260.
  • A. Chandra, A. Sharma, A. Dehzangi, S. Ranganathan, A. Jokhan, K.C. Chou, T. Tsunoda, (2018). “PhoglyStruct: Prediction of phosphoglycerylated lysine residues using structural properties of amino acids”. Scientific Reports, 8(1), p.17923.
  • A. Dehzangi, Y. López, S. P. Lal, G. Taherzadeh, A. Sattar, T. Tsunoda, A. Sharma, (2018). “Improving succinylation prediction accuracy by using secondary structure and evolutionary information”, PLOS One, Volume 13, number: 2, e0191900.
  • M. M. Islam, S. Saha, M. M. Rahman, S. Shatabda, D. M. Farid, A. Dehzangi, (2018). "iProtGly‐SS: Identifying Protein Glycation Sites Using Sequence and Structure Based Features." Proteins: Structure, Function, and Bioinformatics, 86 (7), p.: 777-789.