Serdar Bozdag

Computer Science and Engineering, Mathematics
Associate Professor

SRB 131/DISC F294

940-369-7581

Serdar.Bozdag@unt.edu

Serdar Bozdag

Bozdag Lab

Dr. Serdar Bozdag received his BS degree in Computer Engineering at Marmara University and Ph.D. degree in Computer Science at the University of California, Riverside. Prior to joining Marquette University, Dr. Bozdag was a postdoctoral fellow in National Cancer Institute at the National Institutes of Health. In 2012, he joined Marquette University as an Assistant Professor in the Department of Mathematics, Statistics and Computer Science. In 2015, he received the Way Klingler Young Scholar Award. In 2019, he received the NIH's prestigious Maximizing Investigators' Research Award (MIRA), a 5-year single-PI research grant. In 2020, he joined UNT as an Associate Professor in the Department of Computer Science and Engineering and the Department of Mathematics with an affiliation with the BioDiscovery Institute. Dr. Bozdag has served as a Program Committee member in several bioinformatics conferences including ISMB, ACM-BCB, RECOMB/ISCB Conference on Regulatory & Systems Genomics and the Great Lakes Bioinformatics Conference. He is an editorial board member of PLOS ONE and Cancer Informatics journals. Dr. Bozdag's research goal is to develop open source integrative computational tools to analyze high dimensional biological, clinical and environmental exposure datasets to infer context-specific gene regulatory interactions and modules, and to predict disease associated genes and patient-specific drug response.

CURRENT RESEARCH INTERESTS

  • Developing machine learning and network science methods to integrate multi-omics data
  • Inferring gene regulatory interactions and modules
  • Prioritization of disease- and trait-specific genes
  • Precision medicine

FOR PROSPECTIVE GRADUATE STUDENTS

Apply to the Graduate Program in Computer Science & Engineering

Apply to the Graduate Program in Mathematics

CURRENT GRANT-FUNDED PROJECTS

  • S. Bozdag (PI), "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," Sponsored by NIH (NIGMS, MIRA R35), Total Amount Awarded: $1,787,536. (August 2019 - July 2024).

RECENT SIGNIFICANT PUBLICATIONS

  1. M Al Olaimat, J Martinez, F Saeed, S. Bozdag PPAD: A deep learning architecture to predict progression of Alzheimer's disease. bioRxiv; 2023. p. 2023.01.28.526045. https://doi.org/10.1101/2023.01.28.526045v1

  2. Bose B, Bozdag S. Finding the best cell lines across pan-cancer to use in pre-clinical research as a proxy for patient tumor samples considering immune cells, multi-omics, and cancer pathways. bioRxiv; 2022 https://doi.org/10.1101/2022.12.18.520831

  3. Madugula, S. S., Pandey, S., Amalapurapu, S., & Bozdag, S. (2022). NRPreTo: A Machine Learning Based Nuclear Receptor and Subfamily Prediction Tool. bioRxiv. https://doi.org/10.1101/2022.11.12.516270

  4. Kesimoglu ZN, Bozdag S. SUPREME: A cancer subtype prediction methodology integrating multiomics data using Graph Convolutional Neural Network. bioRxiv; 2022 https://doi.org/10.1101/2022.08.03.502682

  5. Bose B, Moravec M, Bozdag S. Computing microRNA-gene interaction networks in pan-cancer using miRDriver. Sci Rep. Nature Publishing Group; 2022 Mar 8;12(1):3717.

  6. Kesimoglu ZN, Bozdag S. Crinet: A computational tool to infer genome-wide competing endogenous RNA (ceRNA) interactions. PLoS One. 2021;16(5):e0251399.

  7. Dursun C, Kwitek A, Bozdag S. PhenoGeneRanker: Gene and Phenotype Prioritization Using Multiplex Heterogeneous Networks. IEEE/ACM Trans Comput Biol Bioinform. 2021 Jul 20;PP.

  8. Milali, Masabho P., Samson S. Kiware, Nicodem J. Govella, Fredros Okumu, Naveen Bansal, S. Bozdag, Jacques D. Charlwood, et al. "An Autoencoder and Artificial Neural Network-Based Method to Estimate Parity Status of Wild Mosquitoes from near-Infrared Spectra." PLOS ONE 15, no. 6 (June 18, 2020): e0234557. https://doi.org/10.1371/journal.pone.0234557.

  9. B. Bose and S. Bozdag, miRDriver: A Tool to Infer Copy Number Derived miRNA-Gene Networks in Cancer, In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB) (pp. 366-375). New York, NY, USA, 2019.

  10. C. Dursun, N. Shimoyama, M. Shimoyama, M. Schläppi, and S. Bozdag, PhenoGeneRanker: A Tool for Gene Prioritization Using Complete Multiplex Heterogeneous Networks, In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB) (pp. 279-288). New York, NY, USA, 2019.

  11. K. Stamm, A. Tomita-Mitchell, and S. Bozdag, GSEPD: A Bioconductor package for RNA-seq gene set enrichment and novel projection display, BMC Bioinformatics, 2019, 20(1), 115.

  12. D. Do and S. Bozdag, Cancerin: A computational pipeline to infer cancer-associated ceRNA interaction networks, PLOS Computational Biology, 2018 14(7): e1006318.

  13. B. Baur, S. Bozdag, ProcessDriver: A computational pipeline to identify copy number drivers and associated disrupted biological processes in cancer, Genomics, 2017, 109(3-4): 233-240.

  14. M. Muñoz-Amatriaín, H. Mirebrahim, P. Xu, S. Wanamaker, M. C. Luo, H. Alhakami, M. Alpert, I. Atokple, B. Batieno, O. Boukar, S. Bozdag, N. Cisse, I. Drabo, J. Ehlers, A. Farmer, C. Fatokun, Y. Gu, Y.N. Guo, B. L. Huynh, S. Jackson, F. Kusi, C. Lawley, M. Lucas, Y. Ma, M. Timko, J. Wu, F. You, P. Roberts, S. Lonardi, T. J. Close, Genome resources for climate-resilient cowpea, an essential crop for food security, The Plant Journal, 89.5 (2017): 1042-1054.

  15. M. Muñoz-Amatriaín, S. Lonardi, M. C. Luo, K. Madishetty, J. T. Svensson, M. J. Moscou, S. Wanamaker, T. Jiang, A. Kleinhofs, G. J. Muehlbauer, R. P. Wise, N. Stein, Y. Ma, E. Rodriguez, D. Kudrna, P. R. Bhat, S. Chao, P. Condamine, S. Heinen, J. Resnik, R. Wing, H. N. Witt, M. Alpert, M. Beccuti, S. Bozdag, F. Cordero, H. M. R. Ounit, Y. Wu, F. You, J. Zheng, H. Simková, J. Dolezel, J. Grimwood, J. Schmutz, D. Duma, L. Altschmied, T. Blake, P. Bregitzer, L. Cooper, M. Dilbirligi, A. Falk, L. Feiz, A. Graner, P. Gustafson, P. M. Hayes, P. Lemaux, J. Mammadov, and T. J. Close, Sequencing of 15 622 gene-bearing BACs clarifies the gene-dense regions of the barley genome, The Plant Journal, 2015 84.1: 216-227. 10.1111/tpj.12959.

  16. B. Baur and S. Bozdag, A canonical correlation analysis-based dynamic Bayesian network prior to infer gene regulatory networks from multiple types of biological data, Journal of Computational Biology, 2015 22.4: 289-299. 10.1089/cmb.2014.0296.

  17. S. Bozdag, A. Li, G. Riddick, Y. Kotliarov, M. Baysan, F. M. Iwamoto, M. C. Cam, S. Kotliarova, H. A. Fine, Age-specific signatures of glioblastoma at the genomic, genetic, and epigenetic levels, PLOS ONE, 2013 8(4): e62982.

  18. S. Lonardi, D. Durma, M. Alpert, F. Cordero, M. Beccuti, P. R. Bhat, Y. Wu, G. Ciardo, B. Alsaihati, Y. Ma, S. Wanamaker, J. Resnik, S. Bozdag, M. C. Luo, T. J. Close, Combinatorial pooling enables selective sequencing of the barley gene space, PLOS Computational Biology, 2013 9(4): e1003010.

  19. S. Bozdag, A. Li, S. Wuchty, H. A. Fine, FastMEDUSA: A parallelized tool to infer gene regulatory networks, Bioinformatics, 2010, 26(14): 1792-1793.

  20. T. J. Close, P. R. Bhat, S. Lonardi, Y. Wu, N. Rostoks, L. Ramsay, A. Druka, N. Stein, J. T. Svensson, S. Wanamaker, S. Bozdag, M. L. Roose, M. J. Moscou, S. Chao, R. Varshney, P. Szucs, K. Sato, P. M. Hayes, D. E. Matthews, A. Kleinhofs, G. J. Muehlbauer, J. DeYoung, D. F. Marshall, K. Madishetty, R. D. Fenton, P. Condamine, A. Graner and R. Waugh, Development and implementation of high-throughput SNP genotyping in barley, BMC Genomics, 2009, 10:582.