Journal Articles:

Y.Renaudineau, …, K.Mizgalska, WC.Guida, A.Karolak, …, CM.Hedrich. Ultra-rare truncating Toll-Like Receptor 7 variants associate with juvenile-onset systemic lupus erythematosus and pathological cytokine expression. Annals of the Rheumatic Diseases, just accepted (2026)

K.Mizgalska, K.Urbaniak, DJ.Imbody, EB.Haura, WC.Guida, S.Branciamore, A.Karolak. Integrating Molecular Dynamics and Machine Learning to Identify Potential Apo-State Conformational and Solvent-Exposure Signatures Associated with Resistant KRAS Mutants, Frontiers in Chemical Biology, just accepted (2026)

EW. Davis, MA.Park, …, A.Karolak, …, G.Rasool, …, JB.Permuth. CT-Derived Radiomic Signature of MUC6 Expression Improves Guideline-Based Risk Stratification in Intraductal Papillary Mucinous Neoplasms. Cancers 18, 14 (2026)

T. Dyrda-Terniuk, …, K.Mizgalska, WC.Guida, A.Karolak, …, P.Pomastowski. Lactoferrin as an Active Coordination Scaffold for Ruthenium(III).Inorganic Chemistry Frontiers 13, 11 (2026)

RC.Rockne, M.Andersen, ARA.Anderson, D.Basanta, A.Bentivegna, S.Benzekry, S.Branciamore, SC.Brüningk, M.Conte, F.Farahpour, A.Karolak, A.Köhn-Luque, G.Lorenzo, B.Manookian, AS.Rodin, L.Schmalenstroer, J.Soler, C.Tomasetti, K.Urbaniak. The Future of Mathematical Oncology in the Age of AI. NPJ Systems Biology and Applications, 12, 2 (2026)

RE.Noor, S.Islam, T.Smalley, K.Mizgalska, M.Eschenfelder, D.Keramisanou, A.Joshua Astalos, JW.Leahy, WC.Guida, A.Karolak, I.Gelis, M.Acevedo-Duncan. Biophysical Insights into the Binding Interactions of Inhibitors (ICA-1S/1T) Targeting Protein Kinase C-ι, Biophysica 5, 3 (2025)

EW.Davis, ..., A.Karolak, ..., J.Permuth. The Impact of Edema on Skeletal Muscle Changes among Patients with Pancreatic Ductal Adenocarcinoma. Cancer Epidemiology, Biomarkers & Prevention https://doi.org/10.1158/1055-9965.EPI-25-0237 (2025)

T.Nguyen, A.Karolak. Transformer Graph Variational Autoencoder for Generative Molecular Design, Biophysical Journal 124, 1–9; PMID: 39885689  https://doi.org/10.1016/j.bpj.2025.01.022 (2025)

A.Wojtulewski, A.Sikora, S.Dineen, M.Raoof, A.Karolak. Using artificial intelligence and statistics for managing peritoneal metastases from gastrointestinal cancers. Briefings in Functional Genomics 24 (elae049), https://doi.org/10.1093/bfgp/elae049 (2025)

MA.Park, K.Gumpper-Fedus, SG.Krishna,., A.Karolak,., J.Permuth. Molecular Pathway and Immune Profile Analysis of IPMN-Derived Versus PanIN-Derived Pancreatic Ductal Adenocarcinomas. International Journal of Molecular Sciences 25 (23), 13164; https://doi.org/10.3390/ijms252313164 (2024)

E.Mohanan, G.Shen, S.Ren, HH.Fan, KT.Ying Moua, A.Karolak, RC.Rockne, R.Nakamur, DA.Horne, CG.Kanakry, DE.Mager, J.McCune. Challenges with sirolimus experimental data to inform QSP model of post-transplantation cyclophosphamide regimens. Clinical and Translational Science. DOI: 10.1111/cts.70014 (2024)

M.Gubanov, A.Pyayt, A.Karolak. CancerKG.ORG - a Web-scale, Interactive, Verifiable Knowledge Graph-LLM Hybrid for Assisting with Optimal Cancer Treatment and Care. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM, 2024)

A.Mukund, MA.Afridi, A.Karolak, MA.Park, JB.Permuth, G.Rasool. Pancreatic Ductal Adenocarcinoma (PDAC): A Review of Recent Advancements Enabled by Artificial Intelligence. Cancers (2024)

A.Karolak, K.Urbaniak, A.Monastryrskyi, D.Duckett, S.Branciamore, P. Stewart. Structure-independent machine learning predictions of the CDK12 interactome. Biophysical Journal (2024)

A.Sikora, K.Sullivan, S.Dineen, M.Raoof and A.Karolak. Emerging therapeutic approaches for peritoneal metastases from gastrointestinal cancers. Molecular Therapy Oncolytics Volume 32, Issue 1 (2024)

M.Stitou, J.Koomen, D.Imbody, Y.Liao, A.Monastryskyi, U.Rix, D.Duckett, E.Haura, A.Karolak. Opinion: Does AI need companionship to assist drug discovery? The KRAS study. BJR AI, Volume 1, Issue 1 (2024)

N.Nguyen, JK.Teer, MA.Park, P.McDonald, JB.Fleming, JB.Permuth, KC.Chen, A.Karolak. Reinforcing risk prediction for intraductal papillary mucinous neoplasms of the pancreas with AI-optimized nucleotide-to-amino acid analyses. Cancer Res. 84 (2 Suppl.) B109 (2024)

A.Karolak, V.Schoning, A.Khurana. Editorial: Spotlight on AI in Experimental Pharmacology and Drug Discovery. Front. Pharmacology. 14 (2023) PMID: 37711179

D. Rollison, A.Karolak, Y.Luo, L.Folio, T.Dilling, M.Bui, A.Tarhini, I.ElNaqa. Translation of AI into clinical practice. Oncogene (2023)

T.Shaw, B.Zhao, Y.Li, H.Wang, L.Wang, B.Manley, PA.Stewart, A.Karolak, Multi-omics approach to identifying isoform variants as therapeutic targets in cancer patients, Front. Oncol. 12 (2022). PMID: 36505834

A.Matache, A.Karolak, S.Branciamore, A.Rodin, PP.Lee, RC.Rockne, A communication theory framework for modeling cytokine-mediated signaling in healthy and breast cancer derived peripheral blood immune cells, Cancer Res. 82 (12 Supplement), 2741 (2022)

JS.McCune, R.Nakamura, D.O'Meally, TW.Randolph, BM.Sandmaier, A.Karolak, D.Hockenbery, SL.Navarro. Pharmacometabonomic Association of Cyclophosphamide 4-hydroxylation in Hematopoietic Cell Transplant Recipients. Clin Transl Sci. PMID: 35106927 (2022)

A.Karolak, J. Levatic, F. Supek. A framework for mutational signature analysis based on DNA shape parameters. PLoS ONE 17(1): e0262495 (2022)

A.Karolak, S. Branciamore, JS. McCune, PP. Lee, AS. Rodin, RC. Rockne. Concepts and applications of information theory to immuno-oncology Trends in Cancer, Special Issue: Quantitative Cancer Biology 7(4) (2021)

A.Karolak, S.Poonja, DA.Markov, LJ.McCawley, KA.Rejniak Morphophenotypic classification of tumor organoids as an indicator of drug exposure and penetration potential Plos.Comp.Biol. 15(7): e1007214 (2019)

A.Khabibullin, A.Karolak, M.Budzevich, M.Mclaughlin, D.Morse, L.Woods Structure and properties of DOTA-chelated radiopharmaceuticals within the ²²⁵Ac decay pathway, Med.Chem.Comm.,6;9(7), p155 (2018)

A.Karolak, DA.Markov, LJ.McCawley, KA.Rejniak, Toward personalized computational oncology: from spatial models of tumor spheroids to organoids to tissues, J.R.Soc Interface, 15:20170703 (2018)

A.Karolak, KA.Rejniak Micropharmacology: an in silico approach for assessing drug efficacy within a tumor tissue, Bull. Math. Biol. p1 (2018)

A.Karolak, V.Estrella, T.Chen, AS.Huynh, DL.Morse, KA.Rejniak Targeting imaging agents efficacy linked to tumor tissue topological heterogeneity via single-cell micro-pharmacological modelling, Scientific Reports, 8 (1), p3638 (2018)

S.Mukherjee, A.Karolak, Y.Renaudineau, M.Debant, P.Buscaglia, O.Mignen, WC.Guida, WH.Brooks Molecular dynamics simulations of membrane bound STIM1 to investigate conformational changes during STIM1 activation upon calcium release, J. Chem. Inf. Model. 57 (2), p335 (2017)

TA.Word, A.Karolak, C.Cioce, A.van der Vaart, RW.Larsen, Using photoacoustic calorimetry to study the cis to trans photo isomerization of the [Ru(II)(2,2’-bipyridine)₂(H₂O)₂]²⁺ complex in aqueous solution, Comment. Inorg. Chem. 36, p343 (2016)

A.Karolak, A.van der Vaart Molecular dynamics simulations of 5-hydroxycytosine damaged DNA J. Phys. Chem. B, 120, p42 (2016)

A.Karolak, A.van der Vaart BII stability and base step flexibility of N6-adenine methylated GATC motifs Biophys. Chem. 203, p22 (2015)

TA.Word, CL.Whittington, A.Karolak, MT.Kemp, HL.Woodcock, A.van der Vaart, RW. Larsen Photoacoustic calorimetry study of ligand photorelease from the Ru(II)bis(2,2'-bipyridine)(6,6'-dimethyl-2,2'-bipyridine) complex in aqueous solution Chem. Phys. Lett. 619, p214 (2015)

A.Karolak, A.van der Vaart Enhanced sampling simulations of DNA step parameters J. Comp. Chem. 35, 2297-2304 (2014)

A.Karolak, A.van der Vaart Importance of local interactions for the ETS1 stability of inhibitory helix 1 Biophys. Chem. 165, p74 (2012)

H.Maciejewski, B.Marciniec, J.Gulinski, A.Karolak, NK.Skvortsov From isothiocyanato- to silyl-nickel complexes Inorg. Chem. Comm. 5, p464 (2002)

Preprints:

T.Nguyen, M.Gavrilovskaia, K.Mizgalska, S.Xiang, KC.Craig, M.Tantak, KC.Chen, WC.Guida, TH.Tran, NJ.Lawrence, HR.Lawrence, MG.Alexandrow, A.Karolak. Docking-Informed and Multi-Objective Generative AI for Ligand Optimization: Comparison with Combinatorial Design. ChemRxiv (2026)

K.Mizgalska, TH.Tran, NJ.Lawrence, HR.Lawrence, WC.Guida, MG.Alexandrow, A.Karolak. Building Missing Regions in cryo-EM Structure of Human CMG Helicase (PDB ID: 9E2Z) Model Archive (2026)

K.Mizgalska, K.Urbaniak, DJ.Imbody, EB.Haura, WC.Guida, S.Branciamore, A.Karolak. Integrating Computational Chemistry and Machine Learning to Predict KRAS Mutation-Induced Resistance. bioRxiv (2026)

KD.Olumoyin, AM.Aydin, S.Bazargan, B.Bunch, I.Chamseddine, A.Karolak, M.Beatty, S.Pilon-Thomas, MA.Poch, KA.Rejniak. PETIL: Predicting Expansion of Tumor Infiltrating Lymphocytes for the Adoptive Cell Immunotherapy in Bladder Cancers. bioRxiv (2026)

KD.Olumoyin, ..., A.Karolak, ..., K.Rejniak. A Machine Learning Model Optimized for Local Data Stratifies Patients for the Adoptive Cell Therapy with Tumor Infiltrating Lympohocytes in Bladder Tumors. bioRxiv (2025) 

MA.Park, K.Gumpper-Fedus, SG.Krishna, MC.Genilo-Delgado, S.Brantley, PA.Hart, ME.Dillhoff, MF.Gomez, TL.Basinski, SR.Mok, AK.Luthra, JB.Fleming, A.Mohammadi, BA.Centeno, K.Jiang, A.Karolak, D.Jeong, DT.Chen, P.Stewart, JK.Teer, Z.Cruz-Monserrate, JB.Permuth. Molecular Pathway and Immune Profile Analysis of IPMN-Derived versus PanIN-Derived Pancreatic Ductal Adenocarcinomas. Preprints https://doi.org/10.20944/preprints202409.2045.v1 (2024) 

T.Nguyen, A.Karolak. Transformer Graph Variational Autoencoder for Generative Molecular Design, bioRxiv https://doi.org/10.1101/2024.07.22.604603 (2024)

N.Nguyen, MA.Park, JK.Teer, P.McDonald, JB.Fleming, JB.Permuth, KC.Chen, A.Karolak. Text-based Integration of Mutational Profiles for Risk Predictions and Biomarker Identification of Intraductal Papillary Mucinous Neoplasms of the Pancreas, medRxiv (2023)

A.Karolak, J. Levatic, F. Supek A framework for mutational signature analysis based on DNA shape parameters, BioRXiv doi: https://doi.org/10.1101/2020.09.28.316794 (2020)

M.Damaghi, S.Byrne, L.Xu, N.Tafreshi, B.Fang, JM. Koomen, A.Karolak, T.Chen, J.Johnson, ND. Gallant, A.Marusyk, RJ.Gillies Collagen production and niche engineering: a novel strategy for cancer cells to survive acidosis and evolve. BioRXiv 711978; doi: https://doi.org/10.1101/711978 (2019)

S.Nizzero, JC. Alfonso, A.Alvarez-Arenas, I.Mirzaev, I. Zervantonakis, T.Lewin, A.Rishi, E.Piretto, T. Joshi, DN. Santiago, A.Karolak, R.Howard, H.Enderling, FA.Karreth, J.Torres-Roca Overcoming non-small cell lung cancer radiation resistance by modulating the tumor-immune ecosystem BioRXiv https://doi.org/10.1101/458372 (2018)

A.Karolak, B.Huffstutler, Z.Khan, KA.Rejniak Assessment of patient-specific efficacy of chemo- and targeted-therapies: a micro pharmacology approach NIH/NCI Handbook of Mathematical Methods in Cancer Biology, BioRxiv, doi.org/10.1101/236653 (2017)

R.Walker, PE.Navas, SH.Friedman, S.Galliani, A.Karolak, F.Macfarlane, R.Noble, J.Poleszczuk, S.Russell,  KA.Rejniak, A.Shahmoradi, F.Ziebell, J.Brayer, D.Abate-Daga, H.Enderling Enhancing synergy of CAR T cell therapy and oncolytic virus therapy for pancreatic cancer BioRXiv doi: 10.1101/055988 (2016)

Research monographs, chapters in collective volumes:

M.Gavrilovskaia, K.Mizgalska, E.Behrens, Y.Luo, WC.Guida, KC.Chen, A.Karolak. Artificial Intelligence and Machine Learning in Drug Resistance Research. Chapter in "Molecular Mechanisms of Cancer Resistance" - invited and submitted to Elsevier (2026)

A.Karolak, S.Agrawal, S.Lee, KA.Rejniak Dissecting tumor heterogeneity with single-cell-based in silico models, Chapter in “Encyclopedia of Biomedical Engineering: Single Cell Mathematical Models”, Wiley (2019)

A.Karolak, KA.Rejniak Mathematical modeling of tumor organoids: toward personalized medicine, Chapter in “Tumor Organoids: Cancer Drug Delivery and Development”, Springer (2017)

J.Pérez-Velázquez, JL.Gevertz, A.Karolak, KA.Rejniak Microenvironmental niches and sanctuaries: A route to acquired resistance, Chapter in “Advances in Experimental Medicine and Biology”, Springer (2016)