2025

M. Talo and S. Bozdag, “Top-DTI: Integrating Topological Deep Learning and Large Language Models for Drug Target Interaction Prediction,” ISMB/ECCB 2025 (Bioinformatics) 2025 Jul 1;41(Supplement_1):i133–i141. https://doi.org/10.1093/bioinformatics/btaf183.

C. Ozdemir, Y. Vashishath, S. Bozdag, and Alzheimer’s Disease Neuroimaging Initiative, “IGCN: integrative graph convolution networks for patient level insights and biomarker discovery in multi-omics integration,” Bioinformatics, vol. 41, no. 6, p. btaf313, 2025, https://doi.org/10.1093/bioinformatics/btaf313.

B. Bose, B. Stranger, and S. Bozdag, “A network model for patient-derived drug response in breast cancer integrating multi-omics datasets,” Jun. 12, 2025, bioRxiv. https://doi.org/10.1101/2025.06.09.658757.

M. Talo and S. Bozdag, “ProtFun: A Protein Function Prediction Model Using Graph Attention Networks with a Protein Large Language Model,” May 17, 2025, GLBIO 2025, (Preprint: https://doi.org/10.1101/2025.05.13.653854)

M. A. Aghdam, S. Bozdag, F. Saeed, and Alzheimer’s Disease Neuroimaging Initiative, “Machine-learning models for Alzheimer’s disease diagnosis using neuroimaging data: survey, reproducibility, and generalizability evaluation,” Brain Inf., vol. 12, no. 1, p. 8, Mar. 2025, https://doi.org/10.1186/s40708-025-00252-3.

B. A. Pijan and S. Bozdag, “DyGSSM: Multi-view Dynamic Graph Embeddings with State Space Model Gradient Update,” May 13, 2025, arXiv: arXiv:2505.09017. https://doi.org/10.48550/arXiv.2505.09017.

Ma Y, Ayadhury S, Singh S, Vashishath Y, Ozdemir C, McKee T, Nguyen N, Basi A, Mak D, Gomez J, Huse J, Noor S, Winkowski D, Baird R, Weinberg J, Lang F, Burks J, Bozdag S, Seeley E, Ene C. Integrated single cell spatial multi-omics landscape of WHO grades 2-4 diffuse gliomas identifies locoregional metabolomic regulators of glioma growth. bioRxiv; 2025. p. 2025.04.30.651361. https://www.biorxiv.org/content/10.1101/2025.04.30.651361v1

Z. N. Kesimoglu, J. I. M. Rifat, and S. Bozdag, “Computational inference of co-regulatory modules from transcription factors, MicroRNAs, and their targets using CanMod2,” Sci Rep, vol. 15, no. 1, p. 12521, Apr. 2025, https://doi.org/10.1038/s41598-025-97476-4.

C. Ozdemir, M. A. Olaimat, and S. Bozdag, “A Dynamic Model for Early Prediction of Alzheimer’s Disease by Leveraging Graph Convolutional Networks and Tensor Algebra,” Pac Symp Biocomput (PSB 2025), vol. 30, pp. 675–689, 2025. https://doi.org/10.1142/9789819807024_0048

M. A. Olaimat and S. Bozdag, “CAAT-EHR: Cross-Attentional Autoregressive Transformer for Multimodal Electronic Health Record Embeddings,” Jan. 31, 2025, arXiv: arXiv:2501.18891. https://doi.org/10.48550/arXiv.2501.18891.

S. S. Ferreira, S. Pandey, J. Hemminger, S. Bozdag, and M. S. Antunes, “Early changes in microRNA expression in Arabidopsis plants infected with the fungal pathogen Fusarium graminearum,” PLoS One, vol. 20, no. 2, p. e0318532, Feb. 2025, https://doi.org/10.1371/journal.pone.0318532.

2024

M. T. Rahman, F. Saeed, S. Bozdag, and Alzheimer’s Disease Neuroimaging Initiative, “Identifying Alzheimer’s disease-associated genes using PhenoGeneRanker,” bioRxiv, p. 2024.11.12.623269, Nov. 2024, https://doi.org/10.1101/2024.11.12.623269.

Z. N. Kesimoglu and S. Bozdag, “Fusing multiplex heterogeneous networks using graph attention-aware fusion networks,” Sci Rep, vol. 14, no. 1, p. 29119, Nov. 2024, https://doi.org/10.1038/s41598-024-78555-4

Susman A, Krishnamurthy R, Li YC, Olaimat M, Bozdag S, Varghese B, Sheikh-Bahei N, Pandey G. Longitudinal Ensemble Integration for sequential classification with multimodal data. arXiv; 2024. http://arxiv.org/abs/2411.05983

Al Olaimat M, Bozdag S, & Alzheimer’s Disease Neuroimaging Initiative. TA-RNN: an attention-based time-aware recurrent neural network architecture for electronic health records. ISMB 2024 (Bioinformatics). 2024 Jun 28; 40(Supplement_1):i169–i179. https://doi.org/10.1093/bioinformatics/btae264

M. A. Aghdam, S. Bozdag and F. Saeed, "Pvtad: Alzheimer’s Disease Diagnosis Using Pyramid Vision Transformer Applied to White Matter of T1-Weighted Structural Mri Data," 2024 IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024, pp. 1-4, doi: 10.1109/ISBI56570.2024.10635541.

Marinka Zitnik, Michelle M Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T M Murali, Predrag Radivojac, Sushmita Roy, Anaïs Baudot, Serdar Bozdag, Danny Z Chen, Lenore Cowen, Kapil Devkota, Anthony Gitter, Sara J C Gosline, Pengfei Gu, Pietro H Guzzi, Heng Huang, Meng Jiang, Ziynet Nesibe Kesimoglu, Mehmet Koyuturk, Jian Ma, Alexander R Pico, Nataša Pržulj, Teresa M Przytycka, Benjamin J Raphael, Anna Ritz, Roded Sharan, Yang Shen, Mona Singh, Donna K Slonim, Hanghang Tong, Xinan Holly Yang, Byung-Jun Yoon, Haiyuan Yu, Tijana Milenković, Current and future directions in network biology, Bioinformatics Advances, Volume 4, Issue 1, 2024, vbae099, https://doi.org/10.1093/bioadv/vbae099

Bose, B., Bozdag, S. Identifying cell lines across pan-cancer to be used in preclinical research as a proxy for patient tumor samples. Commun Biol 7, 1101 (2024). https://doi.org/10.1038/s42003-024-06812-3

2023

Z. N. Kesimoglu and S. Bozdag, “SUPREME: multiomics data integration using graph convolutional networks,” NAR Genomics and Bioinformatics, vol. 5, no. 2, p. lqad063, Mar. 2023, doi: 10.1093/nargab/lqad063.

S. S. Madugula, S. Pandey, S. Amalapurapu, and S. Bozdag, “NRPreTo: A Machine Learning-Based Nuclear Receptor and Subfamily Prediction Tool,” ACS Omega, May 2023, https://doi.org/10.1021/acsomega.3c00286.

M. Al Olaimat, J. Martinez, F. Saeed, S. Bozdag, and Alzheimer's Disease Neuroimaging Initiative, “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.

2022

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

Kleven AD, Middleton AH, Kesimoglu ZN, Slagel IC, Creager AE, Hanson R, Bozdag S, Edelstein AI (2022). Do In-Hospital Rothman Index Scores Predict Postdischarge Adverse Events and Discharge Location After Total Knee Arthroplasty?. The Journal of Arthroplasty, 37(4), 668-673. https://doi.org/10.1016/j.arth.2021.12.022

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. https://doi.org/10.1038/s41598-022-07628-z

Creager, A. E., Kleven, A. D., Kesimoglu, Z. N., Middleton, A. H., Holub, M. N., Bozdag, S., & Edelstein, A. I. (2022). The Impact of Pre-Operative Healthcare Utilization on Complications, Readmissions, and Post-Operative Healthcare Utilization Following Total Joint Arthroplasty. The Journal of Arthroplasty, 37(3), 414-418. https://doi.org/10.1016/j.arth.2021.11.018

2021

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. PMID: 34283720 https://doi.org/10.1109/TCBB.2021.3098278

Kesimoglu ZN, Bozdag S. Crinet: A computational tool to infer genome-wide competing endogenous RNA (ceRNA) interactions. PLoS One. 2021;16(5):e0251399. PMCID: PMC8118266 https://doi.org/10.1371/journal.pone.0251399

2020

Milali, M. P., Kiware, S. S., Govella, N. J., Okumu, F., Bansal, N., Bozdag, S., … 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. https://doi.org/10.1371/journal.pone.0234557

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. https://doi.org/10.1109/BIBM49941.2020.9313595

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 . New York, NY, USA: Association for Computing Machinery; 2020. p. 1-10. https://doi.org/10.1145/3388440.3415586

Bose B, Bozdag S. 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. New York, NY, USA: Association for Computing Machinery; 2020. p. 1-10.  https://doi.org/10.1145/3388440.3412456

2019

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., … Hecke, A. V. 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. BioRxiv, 582676. https://doi.org/10.1101/582676

Bose, B., & Bozdag, S. (2019). 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 (pp. 366-375). New York, NY, USA: ACM. https://doi.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. In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (pp. 279-288). New York, NY, USA: ACM. https://doi.org/10.1145/3307339.3342155

2018

Do, D., & Bozdag, S. (2018). Cancerin: A computational pipeline to infer cancer-associated ceRNA interaction networks. PLoS Computational Biology, 14(7), e1006318. https://doi.org/10.1371/journal.pcbi.1006318

2017

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://doi.org/10.1371/journal.pone.0184590

Baur, B., & Bozdag, S. (2017). ProcessDriver: A computational pipeline to identify copy number drivers and associated disrupted biological processes in cancer. Genomics, 109(3-4), 233-240. https://doi.org/10.1016/j.ygeno.2017.04.004

Muñoz-Amatriaín, M., Mirebrahim, H., Xu, P., Wanamaker, S. I., Luo, M., Alhakami, H., … Close, T. J. (2017). Genome resources for climate-resilient cowpea, an essential crop for food security. Plant J, 89(5), 1042-1054. https://doi.org/10.1111/tpj.13404

2016

Baur, B., & Bozdag, S. (2016). A Feature Selection Algorithm to Compute Gene Centric Methylation from Probe Level Methylation Data. PloS One, 11(2), e0148977. https://doi.org/10.1371/journal.pone.0148977

2015

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. Journal of Computational Biology: A Journal of Computational Molecular Cell Biology, 22(4), 289-299. https://doi.org/10.1089/cmb.2014.0296

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://doi.org/10.1371/journal.pone.0133356

Muñoz-Amatriaín, M., Lonardi, S., Luo, M., Madishetty, K., Svensson, J. T., Moscou, M. J., … Close, T. J. (2015). Sequencing of 15,622 gene-bearing BACs clarifies the gene-dense regions of the barley genome. The Plant Journal, 84.1: 216-227.. https://doi.org/10.1111/tpj.12959

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. https://doi.org/10.1002/minf.201400168

2014

Baysan, M., Woolard, K., Bozdag, S., Riddick, G., Kotliarova, S., Cam, M. C., … 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://doi.org/10.1371/journal.pone.0094045

Bozdag, S., Li, A., Baysan, M., & Fine, H. A. (2014). Master regulators, regulatory networks, and pathways of glioblastoma subtypes. Cancer Inform, 13(Suppl 3), 33-44. https://doi.org/10.4137/CIN.S14027

2013

Wuchty, S., Vazquez, A., & Bozdag, S. (2013). Genome-wide associations of signaling pathways in glioblastoma multiforme. BMC Medical Genomics, 6, 11. https://doi.org/10.1186/1755-8794-6-11

Bozdag, S., Li, A., Riddick, G., Kotliarov, Y., Baysan, M., Iwamoto, F. M., … Fine, H. A. (2013). Age-Specific Signatures of Glioblastoma at the Genomic, Genetic, and Epigenetic Levels. PLoS ONE, 8(4). https://doi.org/10.1371/journal.pone.0062982

Bozdag, S., Close, T. J., & Lonardi, S. (2013). A Graph-Theoretical Approach to the Selection of the Minimum Tiling Path from a Physical Map. IEEE/ACM Trans Comput Biol Bioinform. https://doi.org/B886D413-EA51-4D69-9095-CC2D5FEF04AB

Lonardi, S., Duma, D., Alpert, M., Cordero, F., Beccuti, M., Bhat, P. R., … Close, T. J. (2013). Combinatorial pooling enables selective sequencing of the barley gene space. PLoS Comput Biol, 9(4), e1003010. https://doi.org/10.1371/journal.pcbi.1003010

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. https://doi.org/10.1371/journal.pone.0066431

2012

Baysan, M., Bozdag, S., Cam, M. C., Kotliarova, S., Ahn, S., Walling, J., … Fine, H. A. (2012). G-cimp status prediction of glioblastoma samples using mRNA expression data. PLoS One, 7(11), e47839. https://doi.org/10.1371/journal.pone.0047839

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. https://doi.org/10.1371/journal.pone.0038200

Wuchty, S., Arjona, D., Bozdag, S., & Bauer, P. O. (2012). Involvement of microRNA families in cancer. Nucleic Acids Res, 40(17), 8219-8226. https://doi.org/10.1093/nar/gks627

2010

Kotliarov, Y., Bozdag, S., Cheng, H., Wuchty, S., Zenklusen, J.-C., & Fine, H. A. (2010). CNAReporter: a GenePattern pipeline for the generation of clinical reports of genomic alterations. BMC Medical Genomics, 3, 11. https://doi.org/10.1186/1755-8794-3-11

Bozdag, S., Li, A., Wuchty, S., & Fine, H. A. (2010). FastMEDUSA: a parallelized tool to infer gene regulatory networks. Bioinformatics, 26(14), 1792-1793. https://doi.org/10.1093/bioinformatics/btq275

Li, A., Bozdag, S., Kotliarov, Y., & Fine, H. A. (2010). GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes. BMC Med Inform Decis Mak, 10, 38. https://doi.org/10.1186/1472-6947-10-38

2009

Bozdag, S., Close, T. J., & Lonardi, S. (2009). A compartmentalized approach to the assembly of physical maps. BMC Bioinformatics, 10, 217. https://doi.org/10.1186/1471-2105-10-217

Close, T. J., Bhat, P. R., Lonardi, S., Wu, Y., Rostoks, N., Ramsay, L., … Waugh, R. (2009). Development and implementation of high-throughput SNP genotyping in barley. BMC Genomics, 10, 582. https://doi.org/10.1186/1471-2164-10-582

2008

Bozdag, S., Close, T., & Lonardi, S. (2008). Computing the minimal tiling path from a physical map by integer linear programming. Algorithms in Bioinformatics, 148-161.

2007

Bozdag, S., Close, T. J., & Lonardi, S. (2007). A Compartmentalized Approach to the Assembly of Physical Maps. In IEEE International Conference on Bioinformatics and Bioengineering (pp. 218-225). https://doi.org/10.1109/BIBE.2007.4375568