peer-reviewed publications
D. Thirumalaisamy, S.K. Joshi, S.E. Kurtz, T.Q. Vu, J.W. Tyner, M. Gönen, O. Nikolova. Drug-centric prior improves drug response modeling in partially overlapping pharmacogenomic screens. (2025) Jan 14. Proc. of the 13th Intl. Conf. on Computational Advances in Bio and Medical Sciences.
M. Mohammadhosseini, T. Enright, A. Duvall, A. Chitsazan, H.Y. Hsin-Yun, A. Ors, B.A. Davis, O. Nikolova, E. Bresciani, J. Diemer, K. Craft, A.C. Menezes, M. Merguerian, S. Chong, K.R. Calvo, N.T. Deuitch, S. Glushakow-Smith, K. Gritsman, L.A. Godley, M.S. Horwitz, S. Keel, L.H. Castilla, E. Demir, H. Mohammed, P. Liu, A. Agarwal. Targeting the CD74 signaling axis suppresses inflammation and rescues defective hematopoiesis in RUNX1-familial platelet disorder. Science Translational Medicine (2025) Jan 8. Vol 17, Issue 780. doi:10.1126/scitranslmed.adn9832
W.M. Yashar, J. Estabrook, H.D. Holly, J. Somers, O. Nikolova, Ö. Babur, T.P. Braun, E. Demir. Predicting transcription factor activity using prior biological information. iScience. (2024) Feb 5. https://doi.org/10.1016/j.isci.2024.109124
J. Somers, M. Fenner, G. Kong, D. Thirumalaisamy, W.M. Yashar, K. Thapa, M. Kinali, O. Nikolova, Ö. Babur, E. Demir. A framework for considering prior information in network-based approaches to omics data analysis. Proteomics. (2023) Nov 23(21-22) https://doi.org/10.1002/pmic.202200402
R. Moser, J. Annis, O. Nikolova, C. Whatcott, K. E. Gurley, E. Mendez, K. Moran-Jones, H. Han, A. Biankin, C. Grandori, D. Van Hoff, C. J. Kemp. Pharmacological targeting of TFIIH suppresses KRAS mutant pancreatic ductal adenocarcinoma and synergizes with TRAIL. Cancer Research (2022). https://doi.org/10.1158/0008-5472.CAN-21-4222
S. E. Kurtz, C. A. Eide, A. Kaempf, N. Long, D. Bottomly, O. Nikolova, B. J. Druker, S. McWeeney, B. H. Chang, J. W. Tyner and A. Agarwal. Associating Drug Sensitivity with Differentiation Status Identifies Effective Combinations for Acute Myeloid Leukemia. Blood Adv. (2022).
R. Moser, K. E. Gurley, O. Nikolova, G. Qin, R. Joshi, E. Mendez, I. Shmulevich, A. Ashley, C. Grandori, C. J. Kemp. Synthetic lethal kinases in Ras/p53 mutant squamous cell carcinoma. Oncogene (2022).
Hahn, W.C., et al., and the Cancer Target Discovery and Development Network. An expanded universe of cancer targets. Cell 184, 1142 — 1155 (2021).
T. Nechiporuk, S.E. Kurtz, O. Nikolova, T. Liu, C.L. Jones, A. D'Alessandro, R. Culp-Hill, A. d'Almeida, S.K. Joshi, M. Rosenberg, C.E. Tognon, A.V. Danilov, B.J. Druker, B.H. Chang, S.K. McWeeney, J.M. Tyner. The TP53 Apoptotic Network is a Primary Mediator of Resistance to BCL2 inhibition in AML Cells. Cancer Discovery (2019).
C. Xu*, O. Nikolova*, R. Basom, R.M. Mitchell, R. Moser, K.E. Gurley, R. Shaw, C.L. Green, I.S. Jang, J. Guinney, V.K. Gadi, A.A. Margolin, C. Grandori, C. Kemp and E. Mendez Ex vivo high throughput functional genomics and drug profiling identifies novel targets and therapeutic options in p53 mutant head and neck cancer. Clinical Cancer Research 24, 2828 — 2843 (2018).
V. Dan^ckz, J.N. Mazerikz, K. Smithz, Z. Ji, B.A. Aksoy, B. Gross, O. Nikolova, N. Jaber, C. Sander, A. Califano, S.L. Schreiber, D.S. Gerhard, L.C. Hermida, S. Jagu, A. Floratos, P.A. Clemons CTD2 Dashboard: A searchable web interface to connect validated results from the Cancer Target Discovery and Development Network. Database (2017).
O. Nikolova, R. Moser, C. Kemp, M. Gonen, A.A. Margolin Modeling Gene-Wise Dependencies Improves the Identification of Drug Response Biomarkers in Cancer Studies. Bioinformatics 33 1362{1369 (2017).
Cancer Target Discovery and Development Network. Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance. Molecular Cancer Research 814 675—682 (2016)
O. Nikolova, J. Zola, S. Aluru. Parallel Globally Optimal Structure Learning of Bayesian Networks. Journal of Parallel and Distributed Computing 73 1039—1048 (2013).
O. Nikolova and S. Aluru. Parallel Bayesian Network Structure Learning with Application to Gene Networks. Proc. ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis (SC), (2012) (acceptance rate: 21% 100/472).
O. Nikolova and S. Aluru. Parallel Discovery of Direct Causal Relations and Markov Boundaries with Applications to Gene Networks. Proc. IEEE International Conference on Parallel Processing (ICPP) 512{521 (2011) (acceptance rate: 22%, 81/363).
O. Nikolova and S. Aluru. Parallel Algorithms for Bayesian Networks Structure Learning with Applications to Systems Biology. Proc. IEEE International Symposium on Parallel and Distributed Processing (IPDPS), Ph.D. Forum 2045—2048 (2011).
O. Nikolova, J. Zola, S. Aluru. A Parallel Algorithm for Exact Structure Learning of Bayesian Networks. Neural
Information Processing Systems (NIPS) Workshop on Learning on Cores, Clusters and Clouds (2010).
O. Nikolova, J. Zola, S. Aluru. Parallel Algorithm for Exact Bayesian Network Inference. Proc. IEEE International Conference on High Performance Computing (HiPC) 342—349 (2009) (acceptance rate 18%, 49/261).
B. Buckner, J. Beck, K. F. Browning, A. E. Fritz, E. Hoxha, L. D. Grantham, Z. N. Kamvar, A. N. Lough, O. Nikolova, P. S. Schnable, M. J. Scanlon and D. Janick-Buckner. Involving Undergraduates in the Annotation and Analysis of Global Gene Expression Studies: Creation of a Maize Shoot Apical Meristem Expression Database. Genetics (2007).
J. Beck, B. Buckner, O. Nikolova, D. J. Buckner. Using interdisciplinary bioinformatics undergraduate research to recruit and retain computer science students. In ACM Proc. of the 38th SIGCSE Technical Symposium on Computer Science Education 358 — 361 (2007).
Pre-prints and Manuscripts in Preparation
Y. Chen, J. Tian, O. Nikolova, S. Aluru. A Parallel Algorithm for Exact Bayesian Structure Discovery in Bayesian Networks. arXiv:1408.1664 (2014).
C.N. de Leeuw, O. Nikolova, M. Toyoshima, T.A. Ince, C.J. Kemp, C. Grandori, et al. Genome scale arrayed siRNA screens reveal inter-patient heterogeneity in cisplatin response and identifies MASTL as a cisplatin sensitizer gene in ovarian carcinoma. In preparation. (In Preparation)
Peer-reviewed Extended Abstracts
D. Thirumalaisamy, S.K. Joshi, M. Gonen, O. Nikolova. Drug-centric prior improves drug response signature identification in partially overlapping, large-scale pharmacogenomic datasets. Accepted for presentation at the 2024 AACR Annual Meeting.
G. Kong, E. Traer, T. Vu, J. Tyner, E. Lind, O. Nikolova. Large-scale CyTOF data modeling of leukemia patient cohorts. Accepted for presentation at the 2024 AACR Annual Meeting.
G. Kong, E. Traer, T. Vu, J. Tyner, E. Lind, O. Nikolova. PyTOF: A Single-Cell CyTOF Pipeline Resolves Cellular Heterogeneity in Chronic Lymphocytic Leukemia. RECOMB/ISCB Conference on Regulatory and Systems Genomics with DREAM Challenges (2023)
F. Yan, O. Nikolova and V.K. Gadi. High-throughput epigenetic screening in hormone receptor positive (HR+) breast cancer cells. In Proc. of the San Antonio Breast Cancer Symposium, Cancer Research 80 Supp. (2020).
T. Nechiporuk, S.E. Kurtz, O. Nikolova, A. d’Almeida, K. Watanabe-Smith, M. Rosenberg, B.J. Druker, J.M. Tyner and S.K. McWeeney. A genome-wide CRISPR screen on AML cells reveals the TP53 apoptotic network is a primary mediator of resistance to BCL2 inhibition. In Proc. of the American Association for Cancer Research Annual Meeting, Cancer Research 79 Supp. (2019).
A. Damnernsawad, T. Nechiporuk, S.E. Kurtz, W.R. Horton, O. Nikolova, S.K. McWeeney, J.W. Tyner. Genome-wide CRISPR screening identifies TSC1 as a regulator of sorafenib resistance in acute myeloid leukemia. In Proc. of the American Association for Cancer Research Annual Meeting, Cancer Research 79 Supp. (2019).
O. Nikolova, L.Heiser, A.A. Margolin Genomic signatures for tumor-to-treatment stratification in pancreatic cancer. In Proc. of the American Association for Cancer Research Annual Meeting, Cancer Research 13 Supp. 5548 (2017).
H. Richards, O. Nikolova, K. Gurley, C. Grandori, C.J. Kemp, V.K. Gadi. A functional kinome screen to identify pathways of anthracycline resistance in patient-derived breast cancer cells. Journal of Clinical Oncology 33 Supp. 11092 (2015).
O. Nikolova, M. Gonen, R. Dienstmann, I. Jang, R. Moser, S. Cermelli, C. Xu, R. Mitchell, E. Mendez, C. Grandori, C. Kemp, S. Friend, J. Guinney, A. Margolin Integrated computational cell-line modeling of drug sensitivity and high-throughput siRNA screening reveals novel molecular biomarkers for conventional chemotherapy. In Proc. of the American Association for Cancer Research Annual Meeting, Cancer Research 74 Supp. 5323 (2014).
selected talks
O. Nikolova, N. Calistri, R. Chai, A. Nishida, V. Chung, M. Diaz, J. Albrecht, J.S. Rodriguez, E. Demir, A. Adey, L. Heiser. scRNA-seq and scATAC-seq Data Analysis DREAM Challenge. RECOMB/ISCB Conference on Regulatory and Systems Genomics with DREAM Challenges, Los Angeles, California (2023).
Predictive modeling to study drug response and improve efficacy of combination therapy in AML. Memorial Sloan Kettering Emerging Leaders in Computational Oncology Symposium, Virtual meeting (2021).
Single-Cell RNA-seq and ATAC-seq Data Analysis DREAM Challenge. Measuring, Modeling, and Controlling Heterogeneity - Center for Cancer Systems Biology (M2CH–CSBC) Outreach Workshop, OHSU (2021).
Differentiation-state plasticity and genetic diversity modeling to predict drug response in AML. Knight Cancer Research Group Seminar Series, OHSU (2021).
Graphical models for Big Data: methods and applications in systems biology and cancer pharmacogenomics. Computer Science Colloquium, Reed College (2020).
Drug signatures as part of the PRECEPTS framework: PREdictors of CEllular Phenotypes to guide Therapeutic Strategies. NIH CCSB Junior Investigator’s Meeting, Bethesda, Maryland (2019).
Modeling gene-wise dependencies improves the identification of drug response biomarkers in cancer. Fred Hutchinson Cancer Research Center ATME Affinity Group Seminar, Seattle (2017).
Parallel Bayesian Network Structure Learning with Application to Gene Networks. ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis, Austin (2012).
Parallel Algorithms for Bayesian Networks Structure Learning with Applications to Gene Networks. Doctoral Dissertation Showcase. ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis, Austin (2012).
Parallel algorithms for Bayesian networks learning: systems biology and biomedical applications. Truman State University, invited talk (2012).
Parallel Discovery of Direct Causal Relations and Markov Boundaries with Applications to Gene Networks. International Conference on Parallel Processing (ICPP), Taipei, Taiwan (2011)