While at USC
Note: # indicates corresponding author; Research group members: * Postdoctoral Fellow, † Ph.D. student, ‡ undergraduate student
- Makaryan, S.Z.† and Finley, S.D.# (2018) “Modeling of CD16, 2B4 and NKG2D stimulation in natural killer cell activation”. Under review. [bioRxiv pre-print]
- Song, M.† and Finley, S.D.# (2018) “Fibroblast growth factor is predicted to dominate MAPK activation by pro-angiogenic factors”. Under review. [bioRxiv pre-print]
- Rohrs, J.A.†, Zheng, D., Graham, N.A., Wang, P. and Finley, S.D.# (2018) “Computational model of chimeric antigen receptors explains site-specific phosphorylation kinetics”. Biophysical Journal. In press. [bioRxiv pre-print]
- Wu, Q.†, Arnheim, A.D.‡, and Finley, S.D.# (2018) “In silico mouse study identifies tumor growth kinetics as biomarkers for the outcome of anti-angiogenic treatment”. Journal of the Royal Society Interface. In press. [bioRxiv pre-print]
- Rohrs, J.A.†, Makaryan, S.Z.†, and Finley, S.D.# (2018) “Constructing predictive cancer systems biology models”. bioRxiv Mathematical Oncology Channel. [bioRxiv]
- Li, D.† and Finley, S.D.# (2018) “The impact of tumor receptor heterogeneity on the response to anti-angiogenic cancer treatment”. Integrative Biology. 10: 253-269 [pubmed] [journal]
- Wu, Q.† and Finley, S.D.# (2017) “Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling”. Cell Communication and Signaling. 15: 53. [pubmed] [journal]
- Gaddy, T.D.‡, Wu, Q.†, Arnheim, A.D.‡ and Finley, S.D.# (2017) “Mechanistic modeling quantifies the influence of tumor growth kinetics on the response to anti-angiogenic treatment”. PLoS Computational Biology. 13(12): e1005874. [pubmed] [journal]
- Roy, M.* and Finley, S.D.# (2017) “Computational model predicts the effects of targeting cellular metabolism in pancreatic cancer”. Frontiers in Physiology. 8:217. [pubmed] [journal]
- Typpo, K.V., Wong, H.R., Finley, S.D., Daniels, R.C., Seely, J.E., and Lacroix, J. (2017) “Monitoring severity of multiple organ dysfunction syndrome: New technologies”. Pediatric Critical Care Medicine. 18(3 Suppl 1): S24-S31. [pubmed] [journal]
- Chu, L.H., Ganta, V.J., Choi, M., Chen, G., Finley, S.D., Annex, B., and Popel, A.S. (2016) “A multiscale computational model predicts distribution of anti-angiogenic isoform VEGF165b in peripheral arterial disease in human and mouse”. Scientific Reports. 6, 37030. [pubmed] [journal]
- Rohrs, J.A.†, Sulistio, C.D.‡, and Finley, S.D.# (2016) “Predictive model of thrombospondin-1 and vascular endothelial growth factor in breast tumor tissue”. npj Systems Biology and Applications (Nature publishing journal). 2, 16030. [pubmed] [journal]
- Rohrs, J.A.†, Wang, P., and Finley, S.D.# (2016) “Predictive model of lymphocyte-specific protein tyrosine kinase (LCK) autoregulation”. Cellular and Molecular Bioengineering. 9(3), 351-367. **Selected for the 2016 Young Innovators issue of the journal [pubmed] [journal]
- Soto-Ortiz, L.*# and Finley, S.D. (2016) ''A cancer treatment based on synergy between anti-angiogenic and immune cell therapies''. Journal of Theoretical Biology. 394, 197-211. [pubmed] [journal]
- Finley, S.D.#, Angelikopoulos, P., Koumoutsakos, P., and Popel, A.S. (2015) ''Pharmacokinetics of anti-VEGF agent aflibercept in cancer predicted by data driven, molecular-detailed model''. CPT: Pharmacometrics & Systems Pharmacology. 4(11), 641-649. [pubmed] [journal]
- Finley, S.D.#, Chu, L.H., Popel, A.S. (2015) ''Computational systems biology approaches to anti-angiogenic cancer therapeutics''. Drug Discovery Today. 20(2), 187-197. [pubmed] [journal]
- Logsdon, E.A., Finley, S.D., Popel, A.S., and Mac Gabhann, F. (2014) ''A systems biology view of blood vessel growth and remodeling''. Journal of Cellular and Molecular Medicine. 18(8), 1491-1508. [pubmed] [journal]
- Finley, S.D.#, Dhar, M. and Popel, A.S. (2013) ''Compartment model predicts VEGF secretion and investigates the effects of VEGF Trap in tumor-bearing mice''. Frontiers in Oncology. 3, 196. [pubmed] [journal]
- Finley, S.D.# and Popel, A.S. (2013) ''Effect of tumor microenvironment on tumor VEGF during anti- VEGF treatment: systems biology predictions''. Journal of the National Cancer Institute. 105(11), 802-11. [pubmed] [journal]
- Finley, S.D.# and Popel, A.S. (2012) ''Predicting the effects of anti-angiogenic agents targeting specific VEGF isoforms''. The AAPS Journal. 14(3), 500-509. [pubmed] [journal]
- Klinke, D.J. and Finley, S.D. (2012) ''Timescale analysis of rule-based biochemical reaction networks''. Biotechnology Progress. 28(1), 33-44. [pubmed] [journal]
- Finley, S.D.#, Engel-Stefanini, M.O., Imoukhuede, P.I., and Popel, A.S. (2011) ''Pharmacokinetics and pharmacodynamics of VEGF-neutralizing agents''. BMC Systems Biology. 5:193. [pubmed] [journal]
- Yen, P.**, Finley, S.D.**#, Stefanini, M.O., and Popel, A.S. (2011) ''A two-compartment model of VEGF distribution in the mouse''. PLoS ONE. 6:e27514. **Contributed equally. [pubmed] [journal]
- Finley, S.D., Gupta, D., Cheng, N., and Klinke, D.J. (2011) ''Inferring relevant control mechanisms for Interleukin-12 signaling in naive CD4+ T cells''. Immunology and Cell Biology. 89(1), 100-110. [pubmed] [journal]
- Finley, S.D., Broadbelt, L.J., and Hatzimanikatis, V. (2010) ''In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene''. BMC Systems Biology. 4:7. [pubmed] [journal]