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brunch, 23 July 2017 at Jeremy & Mary's, photo taken by Marjorie
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Alexander Barabanschikov

Alexander Barabanschikov

Research associate
abarabanschikov at yahoo.com

My background is in theoretical physics, in particular, string theory. Having completed my Ph.D. at Northeastern University in 2004, I decided to move to biology and try to apply theoretical and computational methods to investigate some of the fascinating mechanisms of the functioning of the cell. At the molecular level I had experience in modeling and spectroscopic studies of active sites of (mostly heme) proteins. Numerous studies of theoretical models and chemical model compounds help to identify the reactive motions in the molecule that drive processes like ligand binding or dissociation. At the systems level one is immediately faced with the complexity of reaction networks and the extremely large number of difficult to measure parameters. Currently, I am investigating a certain class of reaction networks arising in post-translational modification with the purpose of finding biologically-important characteristics of these networks that are largely independent of the parameters (such as rate constants). I teach at the Moscow Institute of Physics and Technology and visit Boston regularly.

last updated on 10 October 2012

John Biddle

John Biddle

Postdoctoral Fellow
biddlephys at gmail.com

I did my PhD research in theoretical physics at the University of Maryland, focusing on thermodynamics and statistical mechanics, and especially the study of phase transitions and metastable states. My dissertation was directed by Mikhail Anisimov on the topic of thermodynamic anomalies in supercooled water.

Gene expression in eukaryotes is known to take place away from thermodynamic equilibrium. However, the models that are used to describe eukaryotic gene regulation have so far been derived from our understanding of prokaryotes, where gene expression takes place at equilibrium. My research in the Gunawardena lab aims to improve our understanding eukaryotic gene regulation by taking into account non-equilibrium effects.

last updated on 1 September 2016

David Croll

David Croll

Sabbatical visitor
david.croll at regiscollege.edu

My involvement as a visitor to the Gunawardena group stems from my interest in biochemical reaction networks, especially metabolic pathways. I am building metabolic models in little b, with the goal of understanding the dynamic complexity of metabolism. I am also interested in the development of little b to provide a feature-rich language that will allow biological modelers to express biophysical and regulatory features of enzymes in a natural and convenient fashion.

In graduate school at Purdue University I studied theoretical chemical physics and biophysical chemistry, doing my Ph.D. dissertation research in the group of John Markley, where I used multi-nuclear/multi-dimensional NMR techniques to study the physical chemistry of the ovomucoids, a family of protein-proteinase inhibitors. This was followed by a postdoc at the Biophysics Institute at the Boston University School of Medicine, where I used NMR spectroscopy and computation to study lipoprotein dynamics and biophysical properties.

As a faculty member at Regis College, I have supervised model-oriented undergraduate research projects in biochemistry. I have also been involved in metabolically oriented research projects at Tufts University, including the modeling and measurement of whole body cholesterol metabolism.

last updated on 21 December 2008

Shreepriya Das

Shreepriya Das

Postdoctoral fellow

I am a Postdoctoral Research Fellow in Gunawardena Lab in the Department of Systems Biology, Harvard Medical School. I obtained my PhD from the Department of Electrical and Computer Engineering at The University of Texas at Austin under the advisement of Dr Haris Vikalo. Prior to that, I completed my B.Tech in Electronics and Electrical Communication Engineering from the Indian Institute of Technology, Kharagpur. My research interests are broadly in systems biology, signal processing and machine learning. More information can be found on my personal website.

last updated on 6 September 2017

Joseph Dexter

Joseph Dexter

PhD student
jdexter at princeton.edu

I am an undergraduate at Princeton in the Department of Chemistry and the Lewis-Sigler Institute for Integrative Genomics. My research with the Gunawardena group is focused on developing biochemically realistic mathematical models of important metabolic and signaling networks. I am particularly interested in understanding how robust behavior is implemented in biological systems through specific molecular features such as enzymatic multifunctionality and oligomerization. My models strive to capture essential biochemical details and make heavy use of algebraic geometric techniques developed by the Gunawardena group to enable analysis. At Princeton I also work on the application of microfluidics to a variety of problems in systems biology and biophysics. I am an active alumnus of the Research Science Institute and have taught at the program the past two summers. Outside of science, I am a student of the classics, where my research is mostly centered on ancient theatre and how classical literature has influenced modern literary and cultural concerns.

last updated on 8 August 2012

Javier Estrada

Javier Estrada

Postdoctoral Fellow
jestrada at hms.harvard.edu

I am a joint postdoctoral fellow between the DePace and Gunawardena labs. I try to understand transcription in eukaryotes using Drosophila development as inspiration (PMID 27368104). This is a fascinating yet extremely complex problem that I try to understand by finding answers to these questions: can we understand eukaryotic transcription using the same concepts we use for prokaryotes? Do regulatory cofactors play an important role in controlling transcription? Is energy being dissipated when genes are turned on and off? Which mechanisms can realistically explain the high mutation rate of regulatory DNA sequences observed between closely related species? These are fundamental questions that we need to answer if we want to get to a precise description of how the genome works. A list of ingredients doesn't make a good recipe unless we also have instructions for how to use them!

I trained as a physicist at the Universidad Autónoma de Madrid, Spain and previously worked with the Gunawardena lab on "cellular interrogation" (PMID 27367445).

last updated on 1 September 2016

Jeremy Gunawardena

Jeremy Gunawardena

Associate Professor of Systems Biology
(617) 432 4839
jeremyat hms.harvard.edu

I used to be a very pure mathematician, an algebraic topologist, but fell from grace some years ago (to borrow Marc Kac's gracious way of putting it) when I was a Dickson Instructor in the Mathematics Department at the University of Chicago. I volunteered to teach computer science, which made me interested in complexity, which eventually led to a long stint in industrial research at HP (Hewlett-Packard) Labs, where I ran part of the company's "blue skies" research programme. Post-genome systems biology brought complexity to centre stage and brought me to Harvard.

Our focus in the group is on information processing in mammalian cells. In what sense can cellular processes be considered to "process" information? What kind of information is it and how do we measure it? How are information processing tasks implemented by the molecular mechanisms within cells? What systematic methodologies are needed for attacking such problems and how do we develop them? We approach these questions through a combination of experiment, theory and computation.

last updated on 8 August 2012

Dan Lu

Dan Lu

Postdoctoral Fellow
dan_lu at hms.harvard.edu

I completed my PhD in Biochemistry in 2016 at the University of Cambridge working in Gerard Evan's lab. Cancer therapies rely on targeting vulnerabilities in tumour cells that are not present in normal physiological cells. Systemic inhibition of the MYC transcription factor was shown to specific kill tumour cells, but not normal proliferating tissues, establishing a clear therapeutic window. My PhD project was therefore to identify the causal mechanisms of tumour cell death focusing on perturbations of the metabolic and apoptotic pathways.

Currently in the Gunawardena group in collaboration with Galit Lahav's lab, my research project revolves around the transcription factor, p53. The aim is to functionally attribute the roles of post-translational alterations on the p53 protein following stress induction to the subsequent cell fate. The benefits in qualitatively and quantitatively decoding dynamic cell signals are invaluable both in enhancing existing cancer therapies as well as understanding evolutionary and developmental processes.

last updated on 1 September 2016

Mohan Malleshaiah

Mohan Malleshaiah

Postdoctoral Fellow
mohan_malleshaiah at
hms.harvard.edu

I am interested in understanding the nature of molecular networks and how they process signal information to "compute" cell fate decisions. To this end I utilize integrative approaches by combining quantitative measurements (at single-cell & population level) with computational analysis and modelling. I have explained new mechanisms for cell state transition in the budding yeast as well as in pluripotent stem cell model systems.

I did my PhD with Professor Stephen Michnick at University of Montreal where I analyzed the protein complex dynamics within living cells. I analyzed the MAPK signaling proteins to explain a unique zero-order ultrasensitivity mechanism for switch-like budding to mating decision in yeast cells (PMID 20400943). I also explained how yeast cells simultaneously integrate multiple signals and prioritize their response by tuning sensitivity to signals through cross-pathway interactions (PMID 22186894).

Inspired to explain cell fates in the highly complex mammalian system, I chose to analyze stem cells for my postdoctoral research. As a CIHR (Canadian Institutes of Health Research) Fellow at Professor Jeremy Gunawardena's lab, I developed an integrative approach to analyze embryonic stem cells (ESC). In collaboration with Professor Alfonso Martinez-Arias' lab at Cambridge University, I applied this approach to understand the dynamics of transcription factors (TFs) network of pluripotency during ESCs differentiation into the alternative cell fates. We discovered that a subset of pluripotency TFs is reconfigured to generate new networks that promote differentiation (PMID 26832399 and Cell Reports, 2016).

To better understand individual stem cell behavior and their population heterogeneity, I have further implemented single-cell proteomics, and computational methods to analyze the complex data. In collaboration with Professor George Daley's lab. I am analyzing distinct cell populations during reprogramming of pluripotent stem cells to a) totipotent cells and b) hematopoietic stem cell progenitors.

My publications on NCBI.

last updated on 14 November 2016

Chris Nam

Chris Nam

PhD student
kmnam at g.harvard.edu

I am a second-year Ph.D. student in Harvard's Systems Biology program, working on the application of the "linear framework" to an integrated model of gene regulation and expression. I am broadly interested in understanding how different transcriptional regulatory mechanisms can influence the levels of output mRNA and protein molecules.

I graduated from Swarthmore College in 2015 with a B.A. in Mathematics and Computer Science. I began working with Jeremy as a Systems Biology USRI in 2013, supported by NSF 0856285. I worked on applying methods from numerical algebraic geometry to characterize the "parameter geography" of bistability in multisite post-translational modification systems, focusing on the two-site case. I presented multiple posters and two talks with preliminary conclusions on these questions, and we are now finishing up a paper on the results.

last updated on 25 April 2017

Debdas Paul

Debdas Paul

PhD student collaborator

Currently, I am a third-year doctoral student (Dr.-Ing.) at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany, working with Professor Nicole Radde. My thesis is to develop a theoretical framework to compare the design principle of nature and technical load-bearing structures in terms of robustness, optimality, and multi-functionality.

Previously, I have completed my bachelors and masters in computer science and engineering from the West Bengal University of Technology and from the Jadavpur University, India respectively. As a computer science engineer, I have worked on data-driven bioinformatics and application of spectral graph theory in large-scale networks.

Later, I also pursued a double-degree masters in computational systems biology from the Royal Institute of Technology (KTH), Sweden and the Aalto University, Finland where I worked on the machine learning based computational biology (specifically on kernel methods to predict protein-protein interactions) as well as on parameter estimation techniques for stochastic chemical kinetics based on the chemical master equation.

At Jeremy's lab as a visiting graduate student, I am developing a model for the polymerase-II dynamics (recruitment, pause, elongation and termination) in order to bring the gene expression and regulation under a common unified linear framework.

last updated on 6 September 2017

Aishwarya Venkatramani

Aishwarya Venkatramani

UG student

I am an undergraduate at UC San Diego majoring in physics and biochemistry. Currently as a summer intern at Gunawardena group, I am trying to find biological systems that show higher order cooperatively and use molecular dynamics to quantify copperativity. In the past I have done research in computational biology to identify potential drugs against malarial parasite Plasmodium falciparum at Andy McCammon's group in UCSD. I have also worked with experimental research groups to develop a program to quantify RNA in FISH experiments and a code to simulate waves of Cdk1 during S-phase synchronization in Drosophila embryos. Outside of research, I enjoy traveling, hiking, exploring new places and learning about different cultures.

last updated on 12 July 2017

Felix Wong

Felix Wong

PhD student collaborator
fwong at college.harvard.edu

I graduated from Harvard College with an A.B. degree in mathematics and an S.M. degree in computer science in 2014. I am currently a third-year Ph.D. student in Harvard's applied physics program, advised by Ariel Amir and supported by the NSF Graduate Research Fellowship. I have been working with Jeremy's lab since I was an undergraduate and have a particular interest in the "linear framework" and its applications to gene regulation and non-equilibrium mechanisms (PMIDs 25475875 and 27368104). My personal website is here.

last updated on 1 September 2016

 

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