Serdar Bozdag | BioDiscovery Institute
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Serdar Bozdag

Associate Professor
940-369-7581
Serdar.Bozdag@unt.edu
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. After a postdoctoral fellowship 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. In 2024, he established the Center for Computational Life Sciences and is currently the Founding Director.

Dr. Bozdag has served as a Program Committee member in several bioinformatics and machine learning conferences including ISMB, ACM-BCB, BIBM, KDD, and SDM. He is in the steering committee of the Great Lakes Bioinformatics Conference. He is an editorial board member of Scientific Reports, PLOS ONE, Frontiers in Bioinformatics, and Cancer Informatics journals. He has been co-organizing annual International Workshop on High Performance Computing, Big Data Analytics and Integration for Multi-Omics Biomedical Data since 2020. 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-modal biomedical 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

  • Bozdag, S. (PI), "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," Sponsored by NIH (3R35GM133657-06S1), Federal, $320,473. (August 1, 2023 - June 30, 2024)
  • Bozdag, S. (PI), "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response,", Sponsored by NIH (Supplement Award, Summer REU), Federal, $8,825. (May 2023 - June 2024).
  • Bozdag, S. (PI), "Integrating multiple biomedical data modalities to predict disease diagnosis," Sponsored by NIH, Federal, $111,375. (July 1, 2022 - June 30, 2024).
  • Bozdag, S (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. Akhavan Aghdam, M., Bozdag, S., Saeed, F., & Alzheimer's Disease Neuroimaging Initiative. (2023). PVTAD: Alzheimer's Disease Diagnosis Using Pyramid Vision Transformer Applied to White Matter of T1-Weighted Structural MRI Data. To appear 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024).
  2. Olaimat MA*, Bozdag S. TA-RNN: an Attention-based Time-aware Recurrent Neural Network Architecture for Electronic Health Records. arXiv; 2024 (Accepted at ISMB 2024). Available from: http://arxiv.org/abs/2401.14694 [* Graduate student]
  3. Ozdemir C, Olaimat MA*, Vashishath Y*, Bozdag S, Initiative ADN. IGCN: Integrative Graph Convolutional Networks for Multi-modal Data. arXiv; 2024. Available from: http://arxiv.org/abs/2401.17612 [* Graduate student]
  4. Zitnik M, Li MM, Wells A, Glass K, Gysi DM, Krishnan A, Murali TM, Radivojac P, Roy S, Baudot A, Bozdag S, Chen DZ, Cowen L, Devkota K, Gitter A, Gosline S, Gu P, Guzzi PH, Huang H, Jiang M, Kesimoglu ZN *, Koyuturk M, Ma J, Pico AR, Pržulj N, Przytycka TM, Raphael BJ, Ritz A, Sharan R, Shen Y, Singh M, Slonim DK, Tong H, Yang XH, Yoon BJ, Yu H, Milenković T. Current and future directions in network biology. arXiv; 2023. http://arxiv.org/abs/2309.08478. [* Graduate student]
  5. Kesimoglu Z.N.*, Bozdag S. SUPREME: A cancer subtype prediction methodology integrating multiomics data using Graph Convolutional Neural Network," NAR Genomics and Bioinformatics, vol. 5, no. 2, p. lqad063, Mar. 2023, doi: 10.1093/nargab/lqad063. Impact Factor: 4.6 [* Graduate student]
  6. Madugula, S. S., Pandey, S*., Amalapurapu, S#., & Bozdag, S. (2022). NRPreTo: A Machine Learning Based Nuclear Receptor and Subfamily Prediction Tool. ACS Omega, May 2023, https://doi: 10.1021/acsomega.3c00286 Impact factor: 4.132 [* Graduate student, # Undergraduate student]
  7. Z. N. Kesimoglu * & S. Bozdag (2023). GRAF: Graph Attention-aware Fusion Networks. arXiv preprint arXiv:2303.16781. https://doi.org/10.48550/arXiv.2303.16781 [* Graduate student]
  8. M Al Olaimat*, J Martinez#, F Saeed, S. Bozdag PPAD: A deep learning architecture to predict progression of Alzheimer's disease. (ISMB/ECCB 2023) Bioinformatics, vol. 39, no. Supplement_1, pp. i149-i157, Jun. 2023, doi: 10.1093/bioinformatics/btad249 (Acceptance rate 17%) [* Graduate student, # Undergraduate student]
  9. T. Yang, M. A. Al-Duailij, S. Bozdag and F. Saeed, Classification of Autism Spectrum Disorder Using rs-fMRI data and Graph Convolutional Networks, 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, 2022, pp. 3131-3138, https://doi.org/10.1109/BigData55660.2022.10021070
  10. 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 [* Graduate student]
  11. 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. Impact Factor: 4.996 [* Graduate student, # Undergraduate student]
  12. Kleven, A. D., Middleton, A. H., Kesimoglu, Z. N.*, Slagel, I. C., Creager, A. E., Hanson, R., Bozdag, S., Edelstein, A. I. (2021). Do In-Hospital Rothman Index Scores Predict Postdischarge Adverse Events and Discharge Location After Total Knee Arthroplasty? The Journal of Arthroplasty. https://api.elsevier.com/content/abstract/scopus_id/85122795806,Impact Factor is 4.757. [* Graduate student]
  13. Creager, A. E., Kleven, A. D., Kesimoglu, Z. N.*, Middleton, A. H., Holub, M. N., Bozdag, S., Edelstein, A. I. (2021). The Impact of Pre-Operative Healthcare Utilization on Complications, Readmissions, and Post-Operative Healthcare Utilization Following Total Joint Arthroplasty. The Journal of Arthroplasty. Impact Factor is 4.757. [* Graduate student]
  14. Dursun, C.*, Kwitek, A., Bozdag, S. (2021). PhenoGeneRanker: Gene and Phenotype Prioritization Using Multiplex Heterogeneous Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. Impact Factor is 3.71. [* Graduate student]
  15. Kesimoglu, Z. N.*, Bozdag, S. (2021). Crinet: A computational tool to infer genomewide competing endogenous RNA (ceRNA) interactions. PLOS One, 16(5 May). https://api.elsevier.com/content/abstract/scopus_id/85105825465, Impact Factor is 3.24. [* Graduate student]
  16. Milali, M. P., Kiware, S. S., Govella, N. J., Okumu, F., Bansal, N., Bozdag, S., Charlwood, J. D., Maia, M. F., Ogoma, S. B., Dowell, F. E., Corliss, G. F., Sikulu-Lord, M. T., Povinelli, R. J. (2020). An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra. PLOS One, 15(6), e0234557., Impact Factor is 3.24.
  17. Dursun C*, Smith JR, Hayman GT, Kwitek AE, Bozdag S. NECo: A node embedding algorithm for multiplex heterogeneous networks. 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2020. p. 146-149. [* Graduate student]
  18. Do D*, Bozdag S. CanMod: A computational model to identify co-regulatory modules in cancer. Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics [Internet]. New York, NY, USA: Association for Computing Machinery; 2020 [cited 2021 Feb 11]. p. 1-10. Available from: https://doi.org/10.1145/3388440.3415586 [* Graduate student]