{"id":7,"date":"2016-09-19T12:43:55","date_gmt":"2016-09-19T16:43:55","guid":{"rendered":"http:\/\/erzsoregan.voices-old.wooster.edu\/?page_id=7"},"modified":"2025-04-17T13:39:42","modified_gmt":"2025-04-17T13:39:42","slug":"erzsebet-ravasz-regan","status":"publish","type":"page","link":"https:\/\/erzsoregan.voices.wooster.edu\/","title":{"rendered":"Erzs\u00e9bet Ravasz Regan"},"content":{"rendered":"\n
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  Whitmore-Williams Associate Professor
Chair of Biochemistry and Molecular Biology
The College of Wooster
Pronouns<\/i>: she\/her\/hers<\/div>\n
  Mailing address<\/i>:
Ruth Williams Hall of Science, Room 291
931 College Mall
Wooster, OH 44691
Work<\/i> #:    1-330-263-2092
Work fax<\/i>: 1-330-263-2378
 E-mail<\/i>: eregan@wooster.edu<\/div>\n
Book a brief meeting<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Biological systems, from our bodies to cellular regulatory networks, are built of modules. And modules of modules, a hierarchy.<\/p>\n\n\n\n

This is great news! It means reductionism is in, sort of, as long as we carefully chop the biological system at its joints. We understand the modules in isolation, and put them together to figure out how the whole system works. Right?<\/p>\n\n\n\n

Well. This is yet to work for drug discovery (see “ Eroom’s law<\/a>” for the extent of their troubles). The problem is, when these modules are wired together, they create a system which is strongly dependent on its microenvironment and history. A registry of modules (and their behaviors) is not sufficient to decipher their coordinated response. We need to understand the laws that govern this coordination. Assuming they exist.<\/p>\n\n\n\n

If and when we uncover general rules<\/em> that link regulatory modules into hierarchies, we may then be in a position to understand cellular regulation one module at a time, at every<\/strong> level of the hierarchy<\/b>.<\/p>\n\n\n\n

Research interests:<\/span><\/b><\/p>\n\n\n\n

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The central goal of my research program is to uncover the principles of coordination between cellular phenotypes at multiple scales of organization, and build predictive models of this coordination in health and disease. To this end, I pursue four complementary lines of inquiry:<\/p>\n

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  1. Computational modeling of coupled biological circuits, each of which drive small-scale phenotypic switches. The goal is to predict the emergent, complex coordination of biological phenotypes. This work focuses on a) modeling regulatory networks that drive cellular life and death processes, and their breakdown in cancer, and b) modeling mammalian stem cell states and their crosstalk with the cell cycle. Several generations of College of Wooster Independent Study students have been involved in this effort, and their work is showcased here<\/a>!<\/em><\/strong><\/li>\n
  2. Development of theoretical measures, computational tools, and visualization techniques to aid dy- namical modeling of multi-scale, hierarchically organized phenotypes (difficult for most biology\/ BCMB IS students; but potential collaborative opportunity for physics majors).<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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    Recent publications <\/span><\/b>(Wooster undergraduate students marked with *<\/strong>)<\/span>:<\/span><\/b><\/p>\n

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    1. *G. Greene, *I. Zonfa, E. Ravasz Regan<\/strong>, A Boolean network model of hypoxia, mechanosensing and TGF-\u03b2 signaling captures the role of phenotypic plasticity and mutations in tumor metastasis<\/a>, PLOS Computational Biology<\/em> 21(4): e1012735.\n
    2. *H. Sizek, D. Deritei, *K. Fleig, *M. Harris, P.L. Regan, K. Glass, E. Ravasz Regan<\/strong>, Unlocking Mitochondrial Dysfunction-Associated Senescence (MiDAS) with NAD+ \u2013 a Boolean Model of Mitochondrial Dynamics and Cell Cycle Control<\/a>, Translational Oncology<\/em> 49:102084, 2024 (special issue \u201cNon-genetic heterogeneity and adaptive mechanisms in cancer evolution and drug resistance\u201c).\n<\/li>\n
    3. *Emmalee Sullivan, *Marlayna Harris, *Arnav Bhatnagar, *Eric Guberman, *Ian Zonfa, E. Ravasz Regan<\/strong>, Boolean modeling of mechanosensitive epithelial to mesenchymal transition and its reversal<\/a>, iScience<\/em> 26(4), 2023.<\/li>\n
    4. B. Zakirov , G. Charalambous , R. Thuret , I. M. Aspalter , K. Van-Vuuren , T. Mead, K. Harrington , E. Ravasz Regan<\/strong>, S. P. Herbert, K. Bentley, Active perception during angiogenesis: filopodia speed up Notch selection of tip cells in silico<\/em> and <\/a>in vivo, Phil. Trans. R. Soc. B, <\/em>376: 20190753, 2021.<\/li>\n
    5. *E. Guberman, *H. Sherief, E. Ravasz Regan, <\/strong>Boolean model of anchorage dependence and contact inhibition points to coordinated inhibition but semi-independent induction of proliferation and migration<\/a>, Computational and Structural Biotechnology Journal<\/em> 18, 2145-2165<\/em>, 2020.<\/li>\n
    6. E. Ravasz Regan,<\/strong> Stochastic phenotypic switching in endothelial cell heterogeneity<\/a>. In: Levine H (ed). Phenotypic Switching: Implications in Biology and Medicine<\/em>; Academic Press; 2020, 0128179961 (ISBN-13: 978-0-128-17996-3).<\/li>\n
    7. D. Deritei , J. Rozum , E. Ravasz Regan<\/strong>, R Albert, A feedback loop of conditionally stable circuits drives the cell cycle from checkpoint to checkpoint<\/a>, Scientific Reports, <\/em>9: 16430, 2019.<\/em><\/li>\n
    8. *<\/strong>H. Sizek, *<\/strong>A. Hamel, D. Deritei, *<\/strong>S. Campbell, E. Ravasz Regan<\/strong>,  Boolean model of growth signaling, cell cycle and apoptosis predicts the molecular mechanism of aberrant cell cycle progression driven by hyperactive PI3K<\/a>. PLoS Computational Biology<\/em> 15(3): e1006402, 2019.<\/li>\n<\/ol>\n<\/div>\n\n\n\n

      Prior Research Experience:<\/strong><\/p>\n\n\n\n