Professor Matzavinos' interests are focussed on applied mathematics and mathematical biology. Further details can be found in the sections below.
Kim, Daniel, Bowman, Clark, Del Bonis-O’Donnell, Jackson T., Matzavinos, Anastasios, Stein, Derek Giant Acceleration of DNA Diffusion in an Array of Entropic Barriers. Phys. Rev. Lett.. 2017; 118 (4) |
Chumley, Timothy, Aydogmus, Ozgur, Matzavinos, Anastasios, Roitershtein, Alexander Moran-type bounds for the fixation probability in a frequency-dependent Wright–Fisher model. Journal of Mathematical Biology/Journal of Mathematical Biology. 2017; |
Zayernouri, Mohsen, Matzavinos, Anastasios Fractional Adams–Bashforth/Moulton methods: An application to the fractional Keller–Segel chemotaxis system. Journal of Computational Physics. 2016; 317 : 1-14. |
Matzavinos, Anastasios, Ptashnyk, Mariya Homogenization of oxygen transport in biological tissues. Applicable Analysis. 2016; 95 (5) : 1013-1049. |
Matzavinos, Anastasios, Roitershtein, Alexander, Seol, Youngsoo Random walks in a sparse random environment. Electronic Journal of Probability. 2016; 21, no. 72 : 1-20. |
Matzavinos, Anastasios, Ptashnyk, Mariya Stochastic homogenization of the Keller–Segel chemotaxis system. Nonlinear Analysis: Theory, Methods & Applications. 2016; 144 : 58-76. |
Sturrock, Marc, Murray, Philip, Matzavinos, Anastasios, Chaplain, Mark Mean field analysis of a spatial stochastic model of a gene regulatory network. Journal of Mathematical Biology. 2015; 71 (4) : 921-959. |
Matzavinos, Anastasios, Shtylla, Blerta, Voller, Zachary, Liu, Sijia, Chaplain, Mark A. J. Stochastic modelling of chromosomal segregation: Errors can introduce correction. Bulletin of Mathematical Biology. 2014; 76 (7) : 1590-1606. |
Liu, Sijia, Matzavinos, Anastasios, Sethuraman, Sunder Random walk distances in data clustering and applications. Advances in Data Analysis and Classification. 2013; 7 (1) : 83-108. |
Sturrock, M., Hellander, A., Matzavinos, A., Chaplain, M. A. J. Spatial stochastic modelling of the Hes1 gene regulatory network: Intrinsic noise can explain heterogeneity in embryonic stem cell differentiation. Journal of The Royal Society Interface. 2013; 10 (80) |
Giedt, Randy J., Pfeiffer, Douglas R., Matzavinos, Anastasios, Kao, Chiu-Yen, Alevriadou, B. Rita Mitochondrial dynamics and motility inside living vascular endothelial cells: Role of bioenergetics. Ann Biomed Eng. 2012; 40 (9) : 1903-1916. |
Giedt, Randy J., Yang, Changjun, Zweier, Jay L., Matzavinos, Anastasios, Alevriadou, B. Rita Mitochondrial fission in endothelial cells after simulated ischemia/reperfusion: Role of nitric oxide and reactive oxygen species. Free Radical Biology and Medicine. 2012; 52 (2) : 348-356. |
Schafer, Kelsey N., Kim, Sohee, Matzavinos, Anastasios, Kuret, Jeff Selectivity requirements for diagnostic imaging of neurofibrillary lesions in Alzheimer's disease: A simulation study. NeuroImage. 2012; 60 (3) : 1724-1733. |
Ben-Ari, Iddo, Matzavinos, Anastasios, Roitershtein, Alexander On a species survival model. Electronic Communications in Probability. 2011; 16 : 226-233. |
Ben-Ari, Iddo, Boushaba, Khalid, Matzavinos, Anastasios, Roitershtein, Alexander Stochastic analysis of the motion of DNA nanomechanical bipeds. Bulletin of Mathematical Biology. 2011; 73 (8) : 1932-1951. |
Preedy, Katharine F., Schofield, Pietà G., Liu, Sijia, Matzavinos, Anastasios, Chaplain, Mark A.J., Hubbard, Stephen F. Modelling contact spread of infection in host–parasitoid systems: Vertical transmission of pathogens can cause chaos. Journal of Theoretical Biology. 2010; 262 (3) : 441-451. |
Matzavinos, A., Kao, C.-Y., Green, J. E. F., Sutradhar, A., Miller, M., Friedman, A. Modeling oxygen transport in surgical tissue transfer. Proceedings of the National Academy of Sciences. 2009; 106 (29) : 12091-12096. |
Joshi, Badal, Wang, Xueying, Banerjee, Sayanti, Tian, Haiyan, Matzavinos, Anastasios, Chaplain, Mark A.J. On immunotherapies and cancer vaccination protocols: A mathematical modelling approach. Journal of Theoretical Biology. 2009; 259 (4) : 820-827. |
Matzavinos, Anastasios Dynamic irregular patterns and invasive wavefronts: The control of tumour growth by cytotoxic T-lymphocytes. Selected Topics in Cancer Modeling. 2008; : 1-30. |
Congdon, E. E., Kim, S., Bonchak, J., Songrug, T., Matzavinos, A., Kuret, J. Nucleation-dependent Tau Filament Formation: The Importance of Dimerization and an Estimation of Elementary Rate Constants. Journal of Biological Chemistry. 2008; 283 (20) : 13806-13816. |
Matzavinos, Anastasios, Othmer, Hans G. A stochastic analysis of actin polymerization in the presence of twinfilin and gelsolin. Journal of Theoretical Biology. 2007; 249 (4) : 723-736. |
Hu, Jifeng, Matzavinos, Anastasios, Othmer, Hans G. A theoretical approach to actin filament dynamics. Journal of Statistical Physics. 2007; 128 (1) : 111-138. |
Chaplain, Mark, Matzavinos, Anastasios Mathematical modelling of spatio-temporal phenomena in tumour immunology. Tutorials in Mathematical Biosciences III. 2006; : 131-183. |
Matzavinos, Anastasios, Chaplain, Mark, Kuznetsov, Vladimir Mathematical modelling of the spatio-temporal response of cytotoxic T-lymphocytes to a solid tumour. Mathematical Medicine and Biology. 2004; 21 (1) : 1-34. |
Matzavinos, Anastasios, Chaplain, Mark A.J. Travelling-wave analysis of a model of the immune response to cancer. Comptes Rendus Biologies. 2004; 327 (11) : 995-1008. |
Some specific interests include the following:
Selected research projects
Modeling oxygen transport in surgical tissue transfer:
Part of my recent work has focused on mathematical models of oxygen transport in tissue in the context of reconstructive microsurgery. This clinical technique is used to transfer large amounts of tissue from one location on a patient to another in order to restore physical deformities caused by trauma, tumors, or congenital abnormalities. The trend in this field is to transfer tissue using increasingly smaller blood vessels, which decreases problems associated with tissue harvest but increases the possibility that blood supply to the transferred tissue may not be adequate for healing. Mathematical modeling research in this area helps surgeons understand the relationship between tissue volume and blood vessel diameter to ensure success in these delicate operations. I have been an integral part of a research team consisting of applied mathematicians, medical doctors and bioengineers, focusing on the development of mathematical models that can be used to predict successful tissue transfer based on blood vessel diameter, tissue volume, and oxygen delivery. Part of this work has appeared in the Proceedings of the National Academy of Sciences.
Evaluating triggers and enhancers of tau fibrillization in neurodegenerative diseases:
Alzheimer's disease is characterized in part by the aggregation of tau protein into filamentous inclusions. The mechanism of tau filament formation and its modulation by mutation and post-translational modification is of fundamental importance for the control of the disease. In recent work with Dr. Jeff Kuret of the Center for Molecular Neurobiology at the Ohio State University, we investigated the fibrillization of recombinant full-length four-repeat human tau as a function of time and submicromolar tau concentrations using a combination of electron microscopy assays and mathematical modeling methods. The resulting experimental data were fit to a homogeneous nucleation model with rate constant constraints established from filament dissociation rate, critical concentration, and mass-per-unit length measurements. Results indicated for the first time that once assembly-competent protein conformations were attained, the rate-limiting step in the fibrillization pathway was tau dimer formation. Various aspects of this work have appeared in the Journal of Biological Chemistry.
Spatial stochastic modeling of intracellular signaling pathways:
There are numerous sources of stochasticity and heterogeneity in biological systems, and these can have important consequences for understanding the overall system behavior. Intrinsic noise is commonly found in many intracellular signaling pathways. This noise can arise due to low abundance of molecular species, randomness in certain key processes (e.g. binding and unbinding of transcription factors to promoter sites), stochasticity in production processes (transcription, translation) and degradation events. In addition to being inherently stochastic, intracellular signal transduction is inherently spatial.
In a collaborative project with Mark Chaplain at the University of Dundee in Scotland, we seek to investigate and classify the stochastic spatial dynamics of various types of intracellular signaling pathways. In recently published work, we have developed a spatial stochastic model of the Hes1 pathway that yields results in close agreement with experimental studies of Hes1 oscillations observed in mouse embryonic stem cells. Computational investigations of the model suggest that intrinsic noise is the main driving force for the heterogeneity observed in stem cell differentiation responses under the same environmental conditions. Part of this work has appeared in the Journal of the Royal Society Interface.
Random walk distances in data clustering and applications:
Clustering data into groups of similarity is well recognized as an important step in many diverse applications. Well known clustering methods, dating to the 70's and 80's, include the K-means algorithm and its generalization, the Fuzzy C-means (FCM) scheme, and hierarchical tree decompositions of various sorts. More recently, spectral techniques have been employed to much success. However, with the inundation of many types of data sets into virtually every arena of science, it makes sense to introduce new clustering techniques which emphasize geometric aspects of the data, the lack of which has been somewhat of a drawback in most previous algorithms.
In recent work with Sunder Sethuraman of the University of Arizona, we have considered a slate of random walk distances arising in the context of several weighted graphs formed from the data set, in a comprehensive generalized FCM framework, which allow to assign fuzzy variables to data points which respect in many ways their geometry. Our method groups together data which are in a sense well connected as in spectral clustering, but also assigns to them membership values as in FCM.
The effectiveness and robustness of our method has been demonstrated on several standard synthetic benchmarks and other standard data sets such as the Iris and the Yale face data sets. Part of this work has appeared in Advances in Data Analysis and Classification.
NSF CAREER award. Mesoscale Computational Modeling of Intracellular Soft Matter. Period of performance: June 1, 2016 - May 31, 2021. Principal Investigator: Anastasios Matzavinos.
NSF CDS&E-MSS award. Collaborative Research: Computational Modeling, Simulation, and Validation for Tissue Transplantation. Period of performance: August 1, 2015 - July 31, 2018. Principal Investigator: Anastasios Matzavinos.
Subcontract on Emerging Functions of Mitochondrial Fission in Postischemic Endothelial Cells. NIH R21 grant, 2011-2013. Principal Investigator: B. Rita Alevriadou. One-year subcontract awarded to Anastasios Matzavinos.
Subcontract on Imaging Agents for Diagnosis of Tauopathic Neurodegenerative Diseases, Alzheimer's Drug Discovery Foundation, 2009. Principal Investigator: Jeff Kuret. Subcontract awarded to Anastasios Matzavinos.
Year | Degree | Institution |
---|---|---|
2004 | PhD | University of Dundee |
2001 | MSc | University of Athens |
1998 | BS | University of Crete |
NSF CAREER award. Mesoscale Computational Modeling of Intracellular Soft Matter. Period of performance: June 1, 2016 - May 31, 2021. Principal Investigator: Anastasios Matzavinos.
NSF CDS&E-MSS award. Collaborative Research: Computational Modeling, Simulation, and Validation for Tissue Transplantation. Period of performance: August 1, 2015 - July 31, 2018. Principal Investigator: Anastasios Matzavinos.
Nominated and elected full member of Sigma Xi, the Scientific Research Society, 2012.
Awarded a Mathematical Biosciences Institute (MBI) Early Career Award, 2011.
APMA 1070 - Quantitative Models of Biological Systems |
APMA 1200 - Operations Research: Probabilistic Models |
APMA 1940U - Filtering and Prediction of Hidden Markov Models |
APMA 2190 - Nonlinear Dynamical Systems: Theory and Applications |