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Serdar Bozdag

Title: Associate Professor

Department: Computer Science and Engineering

College: College of Engineering

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of California, Riverside, 2008
    Major: Computer Science
    Dissertation: Combinatorial Approaches to the Physical Mapping Problem
  • BS, Marmara University, 2002
    Major: Computer Engineering

Current Scheduled Teaching

CSCE 6950.806Doctoral DissertationFall 2024
CSCE 6940.806Individual ResearchFall 2024
CSCE 5900.806Special ProblemsFall 2024

Previous Scheduled Teaching

BIOL 6810.001Advanced Topics in Computational Life ScienceSpring 2024 SPOT
CSCE 6810.001Advanced Topics in Computational Life ScienceSpring 2024 SPOT
CSCE 6950.906Doctoral DissertationSpring 2024
CSCE 6940.906Individual ResearchSpring 2024
MATH 6710.001Topics in Applied MathematicsSpring 2024 SPOT
BIOL 5810.001BioComputingFall 2023 SPOT
CSCE 5810.001BioComputingFall 2023 SPOT
BIOL 4810.001Bioinformatics AlgorithmsFall 2023 Syllabus SPOT
CSCE 4810.001Bioinformatics AlgorithmsFall 2023 Syllabus SPOT
CSCE 4810.401Bioinformatics AlgorithmsFall 2023
MATH 4810.001Bioinformatics AlgorithmsFall 2023 Syllabus SPOT
CSCE 6950.806Doctoral DissertationFall 2023
CSCE 6940.806Individual ResearchFall 2023
CSCE 4820.001Computational EpidemiologySpring 2023 Syllabus SPOT
CSCE 5820.001Computational EpidemiologySpring 2023 SPOT
CSCE 5934.824Directed StudySpring 2023
CSCE 6950.924Doctoral DissertationSpring 2023
CSCE 6940.706Individual ResearchSpring 2023
CSCE 4110.070AlgorithmsFall 2022 Syllabus SPOT
BIOL 4810.001BioComputingFall 2022 Syllabus SPOT
BIOL 5810.001BioComputingFall 2022 SPOT
CSCE 5810.001BioComputingFall 2022 SPOT
MATH 4810.001BiocomputingFall 2022 Syllabus SPOT
CSCE 6950.806Doctoral DissertationFall 2022
CSCE 6940.806Individual ResearchFall 2022
CSCE 5900.806Special ProblemsFall 2022
CSCE 6950.924Doctoral DissertationSpring 2022
CSCE 6940.706Individual ResearchSpring 2022
BIOL 6810.002Advanced Topics in Computational Life ScienceFall 2021 SPOT
CSCE 6810.002Advanced Topics in Computational Life ScienceFall 2021 SPOT
BIOL 4810.001BioComputingFall 2021 Syllabus SPOT
BIOL 5810.001BioComputingFall 2021 SPOT
CSCE 4810.001BioComputingFall 2021 Syllabus SPOT
CSCE 5810.001BioComputingFall 2021 SPOT
MATH 4810.001BiocomputingFall 2021 Syllabus SPOT
CSCE 6950.706Doctoral DissertationFall 2021
CSCE 6940.706Individual ResearchFall 2021
CSCE 4110.002AlgorithmsSpring 2021 Syllabus SPOT
CSCE 4110.005AlgorithmsSpring 2021 Syllabus SPOT
CSCE 6940.706Individual ResearchSpring 2021
BIOL 4810.001BioComputingFall 2020 Syllabus SPOT
BIOL 5810.001BioComputingFall 2020 SPOT
CSCE 4810.001BioComputingFall 2020 Syllabus SPOT
CSCE 4810.004BioComputingFall 2020
CSCE 4810.281BioComputingFall 2020 Syllabus SPOT
CSCE 5810.001BioComputingFall 2020 SPOT
CSCE 5810.600BioComputingFall 2020 SPOT
MATH 4810.001BiocomputingFall 2020 Syllabus SPOT
CSCE 6940.706Individual ResearchFall 2020

Published Intellectual Contributions

    Abstracts and Proceedings

  • Vashishath, Y., Bozdag, S. (2021). GWAS Analysis to Compute Genetic Markers of Progression to Alzheimer's Disease. Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. 1. New York, NY, USA, Association for Computing Machinery. https://doi.org/10.1145/3459930.3470854
  • Kesimoglu, Z.N., Bozdag, S. (2021). SUPREME: A Cancer Subtype Prediction Methodology Integrating Multiple Biological Datatypes Using Graph Convolutional Neural Networks. Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. New York, NY, USA, Association for Computing Machinery. https://doi.org/10.1145/3459930.3470853
  • Conference Proceeding

  • Yang, T., Al-Duailij, M.A., Bozdag, S., Saeed, F. (2022). Classification of Autism Spectrum Disorder Using rs-fMRI data and Graph Convolutional Networks. 2022 IEEE International Conference on Big Data (Big Data). 3131--3138.
  • Dursun, C., Smith, J.R., Hayman, G.T., Kwitek, A.E., Bozdag, S. (2020). NECo: A node embedding algorithm for multiplex heterogeneous networks. 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 146--149.
  • Do, D., Bozdag, S. (2020). 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. (117) 1--10. New York, NY, USA, Association for Computing Machinery. https://doi.org/10.1145/3388440.3415586
  • Bose, B., Bozdag, S. (2020). CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer. Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. (7) 1--10. New York, NY, USA, Association for Computing Machinery. https://doi.org/10.1145/3388440.3412456
  • Bose, B., Bozdag, S. (2019). miRDriver: A Tool to Infer Copy Number Derived miRNA-Gene Networks in Cancer. Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. 366--375. New York, NY, USA, ACM. http://doi.acm.org/10.1145/3307339.3342172
  • Dursun, C., Shimoyama, N., Shimoyama, M., Schläppi, M., Bozdag, S. (2019). PhenoGeneRanker: A Tool for Gene Prioritization Using Complete Multiplex Heterogeneous Networks. Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. 279--288. New York, NY, USA, ACM. http://doi.acm.org/10.1145/3307339.3342155
  • Bozdag, S., Close, T.J., Lonardi, S. (2007). A Compartmentalized Approach to the Assembly of Physical Maps. IEEE International Conference on Bioinformatics and Bioengineering. 218--225.
  • Journal Article

  • Aghdam, M., Bozdag, S., Saeed, F. (2023). PVTAD: Alzheimer’s Disease Diagnosis Using Pyramid Vision Transformer Applied To White Matter Of T1-Weighted Structural MRI Data. https://www.biorxiv.org/content/10.1101/2023.11.17.567617v1
  • Zitnik, M., Li, M.M., Wells, A., Glass, K., Gysi, D.M., Krishnan, A., Murali, T.M., Radivojac, P., Roy, S., Baudot, A., Bozdag, S., Chen, D.Z., Cowen, L., Devkota, K., Gitter, A., Gosline, S., Gu, P., Guzzi, P.H., Huang, H., Jiang, M., Kesimoglu, Z.N., Koyuturk, M., Ma, J., Pico, A.R., Pržulj, N., Przytycka, T.M., Raphael, B.J., Ritz, A., Sharan, R., Shen, Y., Singh, M., Slonim, D.K., Tong, H., Yang, X.H., Yoon, B., Yu, H., Milenković, T. (2023). Current and future directions in network biology. arXiv. http://arxiv.org/abs/2309.08478
  • Al Olaimat, M., Martinez, J., Saeed, F., Bozdag, S., Initiative, A.D. (2023). PPAD: a deep learning architecture to predict progression of Alzheimer's disease. Other. 39 (39 Suppl 1) i149--i157.
  • Kesimoglu, Z.N., Bozdag, S. (2023). SUPREME: multiomics data integration using graph convolutional networks. Other. 5 (2) lqad063.
  • Madugula, S.S., Pandey, S., Amalapurapu, S., Bozdag, S. (2023). NRPreTo: A Machine Learning-Based Nuclear Receptor and Subfamily Prediction Tool. ACS Omega. 8 (23) 20379--20388. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10268018/
  • Kesimoglu, Z.N., Bozdag, S. (2023). GRAF: Graph Attention-aware Fusion Networks. arXiv. http://arxiv.org/abs/2303.16781
  • Bose, B., Bozdag, S. (2022). 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. https://www.biorxiv.org/content/10.1101/2022.12.18.520831v1
  • Bose, B., Moravec, M., Bozdag, S. (2022). Computing microRNA-gene interaction networks in pan-cancer using miRDriver. Scientific Reports. 12 (1) 3717. https://www.nature.com/articles/s41598-022-07628-z
  • 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?. Other. https://api.elsevier.com/content/abstract/scopus_id/85122795806
  • 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.. Other.
  • Dursun, C., Kwitek, A., Bozdag, S. (2021). PhenoGeneRanker: Gene and Phenotype Prioritization Using Multiplex Heterogeneous Networks. Other. IEEE.
  • 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
  • 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.
  • Stamm, K., Tomita-Mitchell, A., Bozdag, S. (2019). GSEPD: a Bioconductor package for RNA-seq gene set enrichment and projection display. BMC Bioinformatics. 20 (1) 115. https://doi.org/10.1186/s12859-019-2697-5
  • Jain, N., Ahamed, S.I., Bozdag, S., Dolan, B.K., McVey, A.J., Willar, K.S., Pleiss, S.S., Murphy, C.C., Casnar, C.L., Potts, S., Cibich, D., Nelsen-Freund, K., Fernandez, D., Hernandez, I., Hecke, A.V. (2019). Have It, Know It, but Don’t Show It: Examining Physiological Arousal, Anxiety, and Facial Expressions over the Course of a Social Skills Intervention for Autistic Adolescents. Other. 582676. https://www.biorxiv.org/content/10.1101/582676v2
  • Do, D., Bozdag, S. (2018). Cancerin: A computational pipeline to infer cancer-associated ceRNA interaction networks. PLOS Computational Biology. 14 (7) e1006318.
  • Muñoz-Amatriaín, M., Mirebrahim, H., Xu, P., Wanamaker, S.I., Luo, M., Alhakami, H., Alpert, M., Atokple, I., Batieno, B.J., Boukar, O., Bozdag, S., Cisse, N., Drabo, I., Ehlers, J.D., Farmer, A., Fatokun, C., Gu, Y.Q., Guo, Y.N., Huynh, B.L., Jackson, S.A., Kusi, F., Lawley, C.T., Lucas, M.R., Ma, Y., Timko, M.P., Wu, J., You, F., Barkley, N.A., Roberts, P.A., Lonardi, S., Close, T.J. (2017). Genome resources for climate-resilient cowpea, an essential crop for food security.. Other. 89 (5) 1042--1054.
  • Baur, B., Bozdag, S. (2017). ProcessDriver: A computational pipeline to identify copy number drivers and associated disrupted biological processes in cancer. Other. 109 (3-4) 233--240.
  • Ready, D., Yagiz, K., Amin, P., Yildiz, Y., Funari, V., Bozdag, S., Cinar, B. (2017). Mapping the STK4/Hippo signaling network in prostate cancer cell. PLOS One. 12 (9) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5589252/
  • Baur, B., Bozdag, S. (2016). A Feature Selection Algorithm to Compute Gene Centric Methylation from Probe Level Methylation Data. PLOS One. 11 (2) e0148977.
  • Pradeep, P., Povinelli, R.J., Merrill, S.J., Bozdag, S., Sem, D.S. (2015). Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction. Molecular Informatics. 34 (4) 236--245.
  • Muñoz-Amatriaín, M., Lonardi, S., Luo, M., Madishetty, K., Svensson, J.T., Moscou, M.J., Wanamaker, S., Jiang, T., Kleinhofs, A., Muehlbauer, G.J., Wise, R.P., Stein, N., Ma, Y., Rodriguez, E., Kudrna, D., Bhat, P.R., Chao, S., Condamine, P., Heinen, S., Resnik, J., Wing, R., Witt, H.N., Alpert, M., Beccuti, M., Bozdag, S., Cordero, F., Mirebrahim, H., Ounit, R., Wu, Y., You, F., Zheng, J., \textbackslashu Simková, Hana, Doleel, J., Grimwood, J., Schmutz, J., Duma, D., Altschmied, L., Blake, T., Bregitzer, P., Cooper, L., Dilbirligi, M., Falk, A., Feiz, L., Graner, A., Gustafson, P., Hayes, P.M., Lemaux, P., Mammadov, J., Close, T.J. (2015). Sequencing of 15,622 gene-bearing BACs clarifies the gene-dense regions of the barley genome. Other. n/a--n/a.
  • LaDisa, J.F., Bozdag, S., Olson, J., Ramchandran, R., Kersten, J.R., Eddinger, T.J. (2015). Gene Expression in Experimental Aortic Coarctation and Repair: Candidate Genes for Therapeutic Intervention?. PLOS One. 10 (7) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4514739/
  • Baur, B., Bozdag, S. (2015). A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data. Other. 22 (4) 289--299.
  • Bozdag, S., Li, A., Baysan, M., Fine, H.A. (2014). Master regulators, regulatory networks, and pathways of glioblastoma subtypes.. Other. 13 (Suppl 3) 33--44.
  • Baysan, M., Woolard, K., Bozdag, S., Riddick, G., Kotliarova, S., Cam, M.C., Belova, G.I., Ahn, S., Zhang, W., Song, H., Walling, J., Stevenson, H., Meltzer, P., Fine, H.A. (2014). Micro-Environment Causes Reversible Changes in DNA Methylation and mRNA Expression Profiles in Patient-Derived Glioma Stem Cells. PLOS One. 9 (4) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984100/
  • Bozdag, S., Close, T.J., Lonardi, S. (2013). A Graph-Theoretical Approach to the Selection of the Minimum Tiling Path from a Physical Map.. Other.
  • Lonardi, S., Duma, D., Alpert, M., Cordero, F., Beccuti, M., Bhat, P.R., Wu, Y., Ciardo, G., Alsaihati, B., Ma, Y., Wanamaker, S., Resnik, J., Bozdag, S., Luo, M.C., Close, T.J. (2013). Combinatorial pooling enables selective sequencing of the barley gene space.. Other. 9 (4) e1003010.
  • Sahu, S.N., Lewis, J., Patel, I., Bozdag, S., Lee, J.H., Sprando, R., Cinar, H.N. (2013). Genomic analysis of stress response against arsenic in Caenorhabditis elegans.. PLOS One. 8 (7) e66431.
  • Bozdag, S., Li, A., Riddick, G., Kotliarov, Y., Baysan, M., Iwamoto, F.M., Cam, M.C., Kotliarova, S., Fine, H.A. (2013). Age-Specific Signatures of Glioblastoma at the Genomic, Genetic, and Epigenetic Levels. PLOS One. 8 (4) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3639162/
  • Wuchty, S., Vazquez, A., Bozdag, S. (2013). Genome-wide associations of signaling pathways in glioblastoma multiforme. Other. 6 11. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3616958/
  • Baysan, M., Bozdag, S., Cam, M.C., Kotliarova, S., Ahn, S., Walling, J., Killian, J.K., Stevenson, H., Meltzer, P., Fine, H.A. (2012). G-cimp status prediction of glioblastoma samples using mRNA expression data.. PLOS One. 7 (11) e47839.
  • Sahu, S.N., Lewis, J., Patel, I., Bozdag, S., Lee, J.H., LeClerc, J.E., Cinar, H.N. (2012). Genomic analysis of immune response against Vibrio cholerae hemolysin in Caenorhabditis elegans.. PLOS One. 7 (5) e38200.
  • Wuchty, S., Arjona, D., Bozdag, S., Bauer, P.O. (2012). Involvement of microRNA families in cancer.. Other. 40 (17) 8219--26.
  • Bozdag, S., Li, A., Wuchty, S., Fine, H.A. (2010). FastMEDUSA: a parallelized tool to infer gene regulatory networks.. Other. 26 (14) 1792--3.
  • Li, A., Bozdag, S., Kotliarov, Y., Fine, H.A. (2010). GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes.. Other. 10 38.
  • Kotliarov, Y., Bozdag, S., Cheng, H., Wuchty, S., Zenklusen, J., Fine, H.A. (2010). CNAReporter: a GenePattern pipeline for the generation of clinical reports of genomic alterations. Other. 3 11. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2872651/
  • Bozdag, S., Close, T.J., Lonardi, S. (2009). A compartmentalized approach to the assembly of physical maps.. BMC Bioinformatics. 10 217.
  • Close, T.J., Bhat, P.R., Lonardi, S., Wu, Y., Rostoks, N., Ramsay, L., Druka, A., Stein, N., Svensson, J.T., Wanamaker, S., Bozdag, S., Roose, M.L., Moscou, M.J., Chao, S., Varshney, R.K., Szucs, P., Sato, K., Hayes, P.M., Matthews, D.E., Kleinhofs, A., Muehlbauer, G.J., DeYoung, J., Marshall, D.F., Madishetty, K., Fenton, R.D., Condamine, P., Graner, A., Waugh, R. (2009). Development and implementation of high-throughput SNP genotyping in barley.. BMC Genomics. 10 582.
  • Bozdag, S., Close, T., Lonardi, S. (2008). Computing the minimal tiling path from a physical map by integer linear programming. Other. 148--161.

Contracts, Grants and Sponsored Research

    Grant - Research

  • Bozdag, S. (Principal), "Integrating multiple biomedical data modalities to predict disease diagnosis," sponsored by NIH, Federal, $111375 Funded. (2022 - 2024).
  • Bozdag, S., "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," sponsored by National Institutes of Health, Federal, $1191286 Funded. (2020 - 2024).
  • Bozdag, S. (Principal), "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," sponsored by NIH, Federal, $320473 Funded. (2023 - 2024).
  • Bozdag, S. (Principal), "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," sponsored by NIH, Federal, $8825 Funded. (2023 - 2024).
  • Antunes, M.S. (Principal), Bozdag, S. (Co-Principal), "Identification of early-response small-RNA signatures of biotic stress in plants," sponsored by UNT CENG, COS and VPRI, University of North Texas, $10000 Funded. (2023 - 2024).
  • Bozdag, S. (Principal), "Travel: NSF Student Travel Grant for 2023 Great Lakes Bioinformatics Conference (GLBIO)," sponsored by NSF, Federal, $10000 Funded. (2023 - 2024).
  • Bozdag, S. (Principal), "TACC Computer Server Allocation (Project Name: "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response")," University of North Texas, $10000 Funded. (2022 - 2023).
  • Bozdag, S., "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," sponsored by National Institutes of Health, Federal, Funded. (2020 - 2024).
  • Bozdag, S. (Principal), "Integrating multi-omcs datasets to infer phenotype-specific driver genes, regulatory interactions and drug response," sponsored by National Institutes of Health, FED, Funded. (2020 - 2022).
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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