Matthew K Martz PhD

Machine Learning · AI · Biochemistry · Molecular Biology · Cell Biology

AI and Machine Learning Research

Updating this content to discuss current research direction. Please reach out with to discuss in the meantime.

Biomedical Sciences

Cell biology, a centuries old field dating back to the early work of Robert Hooke in his observations of plant cell walls[1] and Antonie van Leeuwenhoek with his analysis of 'living cells'[2], is the study of how and why cells function as they do. My work and interests lie in uncovering the connection between low level chemical processes and the high level cellular events that epitomize these fundamental units of life. Elucidating how this information is initiated and compiled reveals an understanding of normal cellular function while introducing questions as to how perturbations to these intrinsic processes are handled.

Translation of low level input to high level function In addressing questions of this sort, research evolves as a sort of biphasic process. The first is the establishment of signaling pathways in the cell in both the normal state and in response to environmental stimuli, and how these lead to physiological changes. The second is how the cell detects and handles aberrations to these processes to ensure fidelity. However, both phases require the pursuit of a similar root understanding. Whether interrogating a typical housekeeping pathway or a regulatory network attenuating an aberrant signal, the cell must translate low level chemical changes to high level outcomes. It is not surprising that cell biology is growing to encompass numerous fields of study and exemplifies the emergence of truly multidisciplinary research.

Systems biology approaches these complex interactions that manifest in high level outcomes from a holistic perspective and in doing so, I aim to adopt an effective integrative approach in answering cell biological questions. Utilization of both traditional biochemical and molecular biological techniques with cross-disciplinary computational methodologies not only allows for ways to manage and interpret data on previously unachievable scales, it provides platforms for asking question and addressing questions in novel ways. This is exemplified in the ability to analyze derivations in, or interactions between, vast regulatory networks. However, the adoption of computer and data sciences is not limited simply to the large scale gathering, storing, and analysis of experimental data, these fields can allow for exciting new theoretical ds escriptions of cells.

Barker-Plummer, David, 'Turing Machines', The Stanford Encyclopedia of Philosophy (Summer 2013 Edition), Edward N. Zalta (ed.), URL = <http://plato.stanford.edu/archives/sum2013/entries/turing-machine/>. Addressing problems from a systems level requires an effective integrative research approach, combining traditional biochemical and molecular biological techniques with novel computational and microscopy methodologies. While adapting new technologies for basic science research I will be further working towards developing models of cellular processes and their regulation as computational machines. The goal is to be able to establish the basic algorithms of these networks and develop sets of cellular heuristics that comprise the decisions that are undertaken. This algorithmic description of cells will further enhance our understanding of cell biology while allowing for novel quantitative approaches from a systems level.

    Selected recent publications:
  1. Ramona Schrage, ..., Matthew Martz, ..., Evi Kostenis. The experimental power of FR900359 to study Gq-regulated biological processes. Nature Communications 6, Article number: 10156. 14 December 2015.
  2. Michelle C Helms, Elda Grabocka, Matthew K Martz, Christopher C Fischer, Nobuchika Suzuki, Philip B Wedegaertner. Mitotic-dependent phosphorylation of leukemia-associated RhoGEF (LARG) by Cdk1. Cellular Signalling, Volume 28, Issue 1, January 2016, Pages 43-52.
  3. Martz MK, Grabocka E, Beeharry N, Yen TJ, Wedegaertner PW. Leukemia-Associated RhoGEF (LARG) is a Novel RhoGEF in Cytokinesis and Required for the Proper Completion of Abscission. Mol. Biol. Cell September 15, 2013 vol. 24 no. 18 2785-2794. This paper describes a novel RhoGEF in mitosis acting at a temporally distinct point in the cytokinetic process. We demonstrate that LARG is required for proper abscission kinetics in membrane scission between nascent forming daughter cells. The depletion of LARG from cells further appears to result in cytokinetic apoptosis. Moreover, we establish the mitotic kinase Aurora B as mediator of perturbed abscission kinetics in the abscence of LARG and highlights a more omnipotent abscission checkpoint. Together with recent work in late cytokinesis, these studies reveal a more complex role for RhoA signaling post-contractile ring ingrestion.
  4. Matthew Martz and Philip Wedegaertner: Faculty of 1000 Biology, 23 Jul 2010 F1000Prime.com/4242964#eval4039063 A commentary on a wonderful paper from the Siderovski lab demonstrating support for a kinetic scaffold model wherein the GTP hydrolysis activity of RGS proteins alone is sufficient to confer both signal onset and decay.
  5. Carkaci-Salli N, Flanagan JM, Martz MK, Salli U, Walther DJ, Bader M, Vrana KE. Functional domains of human tryptophan hydroxylase 2 (hTPH2). J Biol Chem. 2006 Sep 22;281(38):28105-12. Epub 2006 Jul 24. This work begins to indentify the structure-function relationship of hTPH2, the central nervous system isoform of the enzyme responsible for the rate limiting, initial step in serotonin production. We describe the purification and characterization of both the wildtype enzyme as and several important truncation mutants in terms of protein stability and enzyme function. These procedural studies should prove invaluable in future kinetic studies of hTPH2 as well as highlight key mutants in obtaining stable protein for structural analysis.

Relevant publication information can be found at Google Scholar

A current vitae is available in PDF format Download PDF

As can be readily inferred from the research interests outlined above, aside from cell biological research, I have a fascination with computer science. This is an intellectual itch that ranges from algorithm design and artificial intelligence to data science—I have outlined some of the projects below that have served as a vehicle for these interests. While addressing fundamental issues of computation, many of these endeavours serve to also improve understanding and proficiency of programming efficient and fast code.

Code and related projects can be found on Github

... Then felt I like some watcher of the skies When a new planet swims into his ken; Or like stout Cortez when with wond'ring eyes He stared at the Pacific ... - John Keats, ms of sonnet (1816)

1. Write down the problem. 2. Think real hard. 3. Write down the solution. -"The Feynman Algorithm" as described by Murray Gell-Mann

Updated: Mon Sept 9, 2013. Some icons from glyphicons.