My Research

I am a quantitative scientist, and my education and career trajectory have always had an interdisciplinary focus, combining mathematics, chemistry, and biology. I have a Master’s in Integrated Science (Mathematics and Biology) from University of Colorado, Denver, and a PhD in Statistics from University of Rochester. I have deep appreciation for the power of mathematics and computational approaches in helping us comprehend complex systems. My research involves two primary foci. First, I am interested in how computational tools and modeling can help us understand protein interactions, aggregation, and oligomerization. I also pursue questions in quantitative image analysis, including integration of multimodal microscopy data, modeling longitudinal image data, and using quantitative tools and advanced imaging methods to detect nanoscale crystals in crystallization screening. My work uses tools from computational statistics, Bayesian inference, high-dimensional data analysis, and machine learning.

I harbor longstanding interest in the way metals behave in and influence biological processes, particularly their role in disease biology. I have pursued these interests in the context of cancer biology, infectious disease, neurotoxicology, and structural biology. I work extensively in applying quantitative approaches in infectious disease and cancer research. I am excited to be applying my quantitative tools to the many unique questions that arise in structural biology. 

Publications (Selected)


          *Featured on cover


  • Srivastava, P, Tzetzo, SL, Gomez, EC, Eng, KH, Sait, SNJ, Kuechle, JB, Singh, PK, De Jong, K, Wiatrowski, KR, Peresie, J and Dimitroff, A, Lynch, ML, Wang, J, Abrams, S, Griffiths, EA, & Nemeth, M (2020). Inhibition of LSD1 in MDS progenitors restores differentiation of CD141 Hi conventional dendritic cells. Leukemia. 34: 24602472.
  • Konstorum, A, Lynch, ML, Torti, SV, Torti, FM, & Laubenbacher, RC (2018). A Systems Biology Approach to Understanding the Pathophysiology of High-Grade Serous Ovarian Cancer: Focus on Iron and Fatty Acid Metabolism. OMICS: a Journal of Integrative Biology, 22(7), 502.

              *On the top 20 read list of articles in OMICS

  • Malcolm, KB, Dinwoodey, DL, Cundiff, MC, Regis, SM, Borondy-Kitts, AK, Wald, C, Lynch, ML, Al-Husami, W, McKee, AB & McKee, BJ (2018). Qualitative coronary artery calcium assessment on CT lung screening exam helps predict first cardiac events. Journal of Thoracic Disease, 10(5), 2740.
  • Ghorani, E, Rosenthal, R, McGranahan, N, Reading, JL, Lynch, M, Peggs, KS, Swanton, C, & Quezada, SA (2018). Differential binding affinity of mutated peptides for MHC class I is a predictor of survival in advanced lung cancer and melanoma. Annals of Oncology, 29(1), 271.
  • Lemler, DL, Lynch, ML, Tesfay, L, Deng, Z, Paul, BT, Wang, X, Hegde, P, Manz, DH, Torti, SV & Torti, FM (2017). DCYTB is a predictor of outcome in breast cancer that functions via iron-dependent mechanisms.  Breast Cancer Research 19 (25).
  • Basuli, D, Tesfay, L, Deng, Z, Paul, B, Yamamoto, Y, Ning, G, Xian, N, McKeon, F, Lynch, ML, Crum, CP, Hedge, P, Brewer, M, Wang, X, Miller, LD, Dyment, N, Torti, FM, & Torti, SV (2017). Iron addiction: A novel therapeutic target in ovarian cancer. Oncogene, 36, 4089.
  • Gerber, C, Harel, M, Lynch, ML, Herbst, KW, Ferrer, FA, & Shapiro, LH (2016). Proximal tubule proteins are significantly elevated in bladder urine of patients with ureteropelvic junction obstruction and may represent novel biomarkers. Journal of Pediatric Urology, 12 (2), 120.e1.
  • Lynch, ML & DeGruttola, V (2015). Predicting time to threshold for initiating antiretroviral treatment to evaluate cost of treatment as HIV prevention. Journal of the Royal Statistical Society Series C, Applied Statistics, 64(2), 359.
  • Lynch, ML & Clement, JM (2015). Bayesian Functional Data Methods in Copy Number Alteration Studies: Applications in Urothelial Bladder Carcinoma. In JSM Proceedings, Biometrics Section.  Alexandria, VA: American Statistical Association, 2129.
  • Duda, JB, Lynch, ML, Bhatt, S, Dogra, VS (2012). Computed Tomography Mimics of Acute Appendicitis: Predictors of Appendiceal Disease Confirmed at Pathology. Journal of Clinical Imaging Science, 2, 73.
  • Strain, JJ, Davidson, PW, Thurston, SW, Harrington, D, Mulhern, MS, McAfee, AJ, van Wijngaarden, E, Shamlaye, CF, Henderson, J, Watson, GE, Zareba, G, Cory-Slechta, DA, Lynch, M, Wallace, JM, McSorley, EM, Bonham, MP, Stokes-Riner, A, Sloane-Reeves, J, Janciuras, J, Wong, R, Clarkson, TW & Myers, GJ (2012). Maternal PUFA status but not prenatal methylmercury exposure is associated with children’s language functions at age five years in the Seychelles. Journal of Nutrition, 142(11), 1943.
  • Lynch, ML, Huang, LS, Cox, C, Strain, JJ, Myers, GJ, Bonham, MP, Shamlaye, CF, Stokes-Riner, A, Wallace, JM, Duffy, EM, Clarkson, TW & Davidson, PW (2011). Varying coefficient function models to explore interactions between maternal nutritional status and prenatal methylmercury toxicity in the Seychelles Child Development Nutrition Study. Environmental Research, 111 (1), 75.
  • Watson, GE, Lynch, M, Myers, GJ, Shamlaye, CF, Thurston, SW, Zareba, G, Clarkson, TW & Davidson, PW (2011). Prenatal exposure to dental amalgam: evidence from the Seychelles Child Development Study main cohort. Journal of the American Dental Association, 142(11), 1283.
  • Hietala, KA, Lynch, ML, Allhouse, JC, Johns, CJ & Roane, TM (2006). A mathematical model of Saccharomyces cerevisiae growth in response to cadmium toxicity. Journal of Basic Microbiology, 46(3), 19.


  • California State University at Los Angeles, Interdisciplinary Studies, BS
  • University of Colorado at Denver, Mathematics and Biology, Masters of Integrated Sciences
  • University of Rochester, Statistics, PhD
  • Harvard TH Chan School of Public Health, Postdoc


Miranda Lynch, PhD

T: 716-898-8672