Faculty

Chair

412-648-3333
bahar@pitt.edu
Office: BST3 3058
Lab Website
Ivet Bahar, PhD - Distinguished Professor and John K. Vries Chair, Department of Computational & Systems Biology
Ph.D. in Chemistry, Istanbul Technical Institute; B.S. and M.S. in Chemical Engineering, Bogazici U.
Biomolecular systems are not static: they constantly move, change shape, and interact with each other. Understanding the mechanisms of their interactions and their binding, catalytic and allosteric signaling effects is not possible without a molecular level modeling of their collective dynamics. A major research goal in my lab is to investigate the dynamics of molecular systems in the cellular environment cellular using fundamental principles of physical sciences and engineering. Another is the development of novel quantitative molecular and system pharmacology tools toward discovering novel drugs or repurposing existing drugs, with focus on neurosignaling disorders.
Liu B, Liu Q, Palaniappan S, Yang L, Bahar I, Thiagarajan PS, Ding JL (2016) Innate Immune Memory and Homeostasis May Be Conferred Through crosstalk between TLR3 and TLR7 Pathways Science Signaling 9: 436.

Cooper GF, Bahar I, Becich MJ, Benos PV, Berg J, Espino JU, Glymour C, Jacobson RC, Kienholz M, Lee AV, Lu X, Scheines RB (2015) The Center for Causal Discovery of biomedical knowledge from Big Data J Am Med Inform Assoc 22: 1132-1136.

412-648-3315
benos@pitt.edu
Office: BST3 3059
Lab Website
Panayiotis (Takis) V. Benos, PhD - Professor, Vice Chair of Faculty Affairs
Molecular Biology, University of Crete, 1997
Our ultimate goal is to investigate the causes of chronic diseases and cancer by using all available data. Our work involves the development of new machine learning methods for the integration of multi-modal, large, biomedical datasets in a probabilistic graphical framework. For this purpose we collaborate with many clinical researchers in the University of Pittsburgh and elsewhere.
Olave N, Lal CV, Halloran B, Pandit K, Cuna AC, Faye-Petersen OM, Kelly DR, Nicola T, Benos PV, Kaminski N, Ambalavanan N (2016) Regulation of alveolar septation by microRNA-489? Am J Physiol Lung Cell Mol Physiol 10: 476-487.

Cooper GF, Bahar I, Becich MJ, Benos PV, Berg J, Espino JU, Glymour C, Jacobson RC, Kienholz M, Lee AV, Lu X, Scheines RB (2015) The Center for Causal Discovery of biomedical knowledge from Big Data J Am Med Inform Assoc 22: 1132-1136.

412-648-8171
faeder@pitt.edu
Office: BST3 3082
Lab Website
James R. Faeder, PhD - Associate Professor, Vice Chair for Educational Programs/Initiatives
Ph.D. in Chemical Physics, University of Colorado at Boulder
I am interested in developing mathematical models of biological regulatory processes that integrate specific knowledge about protein-protein interactions. My current research includes the development of specific models of signal transduction and the development of new stochastic simulation algorithms that will greatly broaden the scope of models that can be developed. Other research areas include model reduction, parameter estimation and uncertainty analysis, and automated model construction from databases of protein interactions.
Harris LA, Hogg JS, Tapia JJ, Sekar JAP, Gupta S, Korsunsky I, Arora A, Barua D, Sheehan RP, Faeder JR (2016) BioNetGen 2.2: Advances in Rule-Based Modeling Bioinformatics .

Hawse WF, Sheehan RP, Miskov-Zivanov N, Menk AV, Kane LP, Faeder JR, Morel PA (2015) Cutting Edge: Differential Regulation of PTEN by TCR, Akt, and FoxO1 Controls CD4+ T Cell Fate Decisions J Immunol 194: 4615-9.
Faculty

412-648-8646
jayoob@pitt.edu
Office: BST3 3053
Lab Website
Joseph C. Ayoob, PhD - Associate Professor
Ph.D., Neuroscience, Johns Hopkins University School of Medicine; B.A. Biology, University of Pennsylvania
Research: As an experimentalist, I use molecular-genetic approaches to study developmentally-regulated cell death and engulfment. Studying this process during the development of an organism will give us new insights into how this same process also eliminates pre-cancerous cells in the adult. Training and Outreach: To reach out to and train the next generation of scientists, we have initiated Tiered Mentoring and Training programs for undergraduates (TECBio REU @ Pitt) and high school students (DiSCoBio Summer Academy) to prepare them for careers in STEM (see Education page for more info).
Ayoob JC, Chennubhotla C (2012) First Steps International Innovation 30-32.

Wu Z, Sweeney LB, Ayoob JC, Chak K, Andreone, BJ, Ohyama T, Kerr R, Luo L, Zlatic M, Kolodkin AL (2011) A combinatorial semaphorin code instructs the initial steps of sensory circuit assembly in the Drosophila CNS Neuron 70: 281-298.

412-624-1223
jberg@pitt.edu
Office:
Lab Website
Jeremy M. Berg, PhD - Professor
Ph.D. in Chemistry, Harvard University
Specific interactions between macromolecules are key to essentially all biological processes. Our research program has two related goals. The first is to understand the structural and chemical bases by which these specific interactions occur. The second is to understand why, biologically and evolutionarily, particular interactions have the strengths that they do. Systems of particular interest involve peroxisomal protein targeting and protein and nucleic acid interactions involving zinc-binding domains. Jeremy M. Berg is Director of the Institute of Personalized Medicine, Associate Vice Chancellor for Science Strategy and Planning in the Health Sciences, and Professor of Computational and Systems Biology at the University of Pittsburgh.
Levine AS, Alpern RJ, Andrews NC, Antman K, Balser JR, Berg JM (2015) Research in academic medical centers: Two threats to sustainable support SCIENCE TRANSLATIONAL MEDICINE 7: 289fs22.

Geskin A, Legowski E, Chakka A, Chandran UR, Barmada MM, LaFramboise WA, Berg JM, Jacobson RS (2015) Needs Assessment for Research Use of High-Throughput Sequencing at a Large Academic Medical Center PloS 10: e0131166.

412-648-7776
ccamacho@pitt.edu
Office: BST3 3077
Lab Website
Carlos J. Camacho, PhD - Associate Professor
Ph.D. in Physics, University of Maryland, College Park
A striking set of specific and non-specific interactions encoded in the protein structure tolerates binding only to a unique substrate. My main research interests focus on modeling the physical interactions responsible for molecular recognition, and in the development of new technologies for structural prediction, their substrates and supramolecular assemblies. Any progress in these fundamental problems is bound to bring about a better understanding of how proteins work cooperatively in a cell, promoting breakthroughs in every aspect of the biological sciences.
Koes DR, Pabon NA, Phillips MA, Camacho CJ (2015) A Teach-Discover-Treat Application of ZincPharmer: An Online Interactive Pharmacophore Modeling and Virtual Screening Tool PLoS One 10: e0134697.

Koes DR, Camacho CJ (2015) Indexing Volumetric Shapes with Matching and Packing Knowledge and Information Systems 43: 157-180.

-412-648 x 3335
anc201@pitt.edu
Office: BST3 3079
Lab Website
Anne Ruxandra Carvunis, PhD - Assistant Professor
Ph.D., Bioinformatics, Université Joseph Fourier, Grenoble, France
What makes each species unique? Why is it that drugs that cure rats in the lab are often powerless against human disease? A major goal of my research is to work out the molecular mechanisms of change and innovation in biological systems in order to define the genetic and network-level determinants of species-specificity.
Carvunis AR, Wang T, Skola D, Yu A, Chen J, Kreisberg J, Ideker T (2015) Evidence for a common evolutionary rate in metazoan transcriptional networks ELife 4: e11615.

Carvunis AR, Ideker T (2014) Siri of the Cell - what biology could learn from the iPhone Cell 157(3): 534-8.

412-648-7794
chakracs@pitt.edu
Office: BST3 3081
Lab Website
Chakra Chennubhotla, PhD - Associate Professor
Ph.D. in Computer Science, University of Toronto
Developing computational models and methods to improve the understanding of major interactions and allosteric mechanisms that underlie the proper functioning of biomolecular systems. In particular (i) developing information-theoretic concepts for determining the probabilistic rates, pathways, and sequences of information flow in multicomponent and cellular biomolecular systems, (ii) designing and interpreting FRET based experiments to explore and assess functional implications of molecular interactions and correlations, and (iii) developing novel computer vision methods for analyzing, refining and interpreting structure, dynamics, and function in biomolecular images and movies.
Ramanathan A, Pullum LL, Hobson TC, Stahl CG, Steed CA, Quinn SP, Chennubhotla C, Valkova S (2015) Discovering Multi-Scale Co-Occurrence Patterns of Asthma and Influenza with Oak Ridge Bio-Surveillance Toolkit Front Public Health 3: 182.

Quinn SP, Zahid MJ, Durkin JR, Francis RJ, Lo CW, Chennubhotla C (2015) Automated identification of abnormal respiratory ciliary motion in nasal biopsies Sci Transl Med 7: 299.

412-648-3338
mchikina@pitt.edu
Office: BST3 3078
Lab Website
Maria Chikina, PhD - Assistant Professor
Ph.D. in Molecular Biology, Princeton University
The rise of genome-scale experimental methods has greatly accelerated the speed of biological data accumulation. However, as datasets increase in size, it becomes easier to find patterns and correlations, but harder to distinguish true biological insight from technological and statistical artifacts. Consequently, exploiting large-scale datasets to inform our understanding of biological systems remains a challenge. My work has focused on bridging the gap between statistically rigorous computational techniques and knowledge of underlying biological and experimental processes to develop methods that overcome the biases and artifacts inherent in the structure of large-scale datasets and transform noisy data into concrete biological knowledge.
Tao J, Xu E, Zhao Y, Singh S, Li X, Couchy G, Chen X, Zucman-Rossi J, Chikina M, Monga SP (2016) Modeling a Human HCC Subset in Mice Through Co-Expression of Met and Point-Mutant β-Catenin Hepatology .

Chikina M, Robinson JD, Clark NL (2016) Hundreds of Genes Experienced Convergent Shifts in Selective Pressure in Marine Mammals Mol Biol Evol .

412-855-4562
nclark@pitt.edu
Office: BST3 3080
Lab Website
Nathan L. Clark, PhD - Assistant Professor
Ph.D. in Genome Sciences at University of Washington, Seattle
Adaptive evolution brings about genetic changes in response to new challenges such as pathogens or a new environment. Our lab exploits genetic signatures left by these adaptations to determine mechanisms of functional change in proteins. In addition, we study the coevolutionary relationships between genes to infer new genetic interactions and to inform a systems-level view of the genome. Our overarching goal is to understand how proteins and their networks change over time, and we develop novel evolutionary tools to this end.
Chikina M, Robinson JD, Clark NL (2016) Hundreds of Genes Experienced Convergent Shifts in Selective Pressure in Marine Mammals Mol Biol Evol .

Hancks DC, Hartley MK, Hagan C, Clark NL, Elde NC (2015) Overlapping Patterns of Rapid Evolution in the Nucleic Acid Sensors cGAS and OAS1 Suggest a Common Mechanism of Pathogen Antagonism and Escape PLoS Genet 11: 5.

412-383-5745
dkoes@pitt.edu
Office: BST3 3086
Lab Website
David R. Koes, PhD - Assistant Professor
Ph.D. in Computer Science, Carnegie Mellon University
Removing barriers to computational drug discovery bit by bit. I create novel computational methods for accelerating the pace of discovery and enhancing the accuracy of virtual screening.
Koes DR, Vries JK (2017) Error assessment in molecular dynamics trajectories using computed NMR chemical shifts Computational and Theoretical Chemistry 1099: 152-166.

Sunseri J, Ragoza M, Collins J, Koes DR (2016) A D3R prospective evaluation of machine learning for protein-ligand scoring Journal of computer-aided molecular design 30(9): 761-771.

412-648-8607
robinlee@pitt.edu
Office: BST3 3083
Lab Website
Robin E.C. Lee, PhD - Assistant Professor
Ph.D. in Cellular and Molecular Medicine, University of Ottawa
To decide between irreversible cell fates such as growth, differentiation or death, cells process information about their environment through a network of molecular circuits. Our research combines principles of systems and synthetic biology with large-scale data to understand how information flows through these circuits. By observing input-output relationships in the same cell using microfluidics, live-cell dynamics and single-molecule microscopy, we aim to decode the ‘language’ of signaling dynamics and develop mathematical models of information flow with single-cell resolution. Our ultimate goal is to understand how population-level responses emerge from single-cell heterogeneity and to rationally manipulate cell fate decisions in disease.
Shrestha A, Lee REC, Megeney LA (2015) Monitoring the proteostasis function of the Saccharomyces cerevisiae metacaspase Yca1 Methods Mol Biol 1133: 223-235.

Lee REC, Walker SR, Savery K, Frank DA, Gaudet S (2014) Fold Change of Nuclear NF-κB Determines TNF-Induced Transcription in Single Cells Molecular cell 53(6): 867-879.

412-383-8042
lezon@pitt.edu
Office: BST3 3084
Lab Website
Tim Lezon, PhD - Assistant Professor
Ph.D. in Physics, Pennsylvania State University
My research focuses on identifying disease-specific pathways from phenotypic screens. Non-clonal cellular heterogeneity is a rich source of information on the molecular activity of cellular pathways, and I construct analytical and computational tools for extracting this information. The specific applications that I am focused on are developing targeted therapies for breast cancer, identifying combinations of drugs that will effectively treat Huntington’s disease, and advancing computational pathology through analysis of intratumor heterogeneity.
Gough AH, Chen N, Shun TY, Lezon T, Boltz RC, Reese CE, Wagner J, Vernetti LA, Grandis JR, Lee AV, Stern AM, Schurdak ME, Taylor DL (2014) Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery PLoS One 9(7): e102678.

Bakan A, Dutta A, Mao W, Liu Y, Chennubhotla CS, Lezon T, Bahar IS (2014) Evol and ProDy for bridging protein sequence evolution and structural dynamics Bioinformatics .

412-648-3333
oltvai@pitt.edu
Office: BST3 3087
Lab Website
Zoltan Oltvai, MD - Associate Professor of Pathology
MD, Semmelweiss Medical University, Budapest
Dr. Oltvai’s research interest is in the area of systems biology of cell metabolism, including the metabolism of prokaryotic and mammalian cells, including tumor cells. Dr. Oltvai is a staff pathologist in the Division of Clinical Microbiology. He is also a faculty member of the Interdisciplinary Biomedical Science Graduate Program, the Medical Scientist Training Program, the Cellular and Molecular Pathology Graduate Training Program, and the Joint CMU-Pitt PhD Program in Computational Biology.
No publications authored or co-authored by Zoltan Oltvai were found.

412-648-3338
dltaylor@pitt.edu
Office: BST3 10045
Lab Website
D. Lansing Taylor, PhD - Distinguished Professor; Director, University of Pittsburgh Drug Discovery Institute
Ph.D. in Cell Biology, State University of New York at Albany
My research interests have been rooted in understanding the temporal-spatial dynamics of signaling molecules and proteins in living cells, coupled to defining the mechanisms of fundamental cell functions such as cell division and cell migration. I have always integrated the development of new technologies in fluorescence-based reagents and light microscope imaging in order to improve the ability to define molecular events in cells and tissue models. My interests have evolved from single cell activities to understanding cellular population dynamics, including the biological basis for heterogeneity in response to perturbagens such as drug treatments.
Shanhang J, Miedel MT, Ngo M, Hessenius R, Wang P, Bahreini A, Li Z, Ding Z, Chen N, Shun TY, Zuckerman DM, Taylor DL, Puhalla SL, Lee AV, Oesterreich S, Stern AM (2017) Clinically observed estrogen receptor alpha mutations within the ligand-binding domain confer distinguishable phenotypes indicative of Darwinian-like somatic evolution Oncology .

Vernetti L, Senutovitch N, Boltz R, DeBiasio R, Shun TY, Gough A, Taylor DL (2015) A human liver microphysiology platform for investigating physiology, drug safety and disease models J Exp Biol Med .

-412-383 x 5856
avogt@pitt.edu
Office: BST3 10047
Lab Website
Andreas Vogt, PhD - Associate Professor
Ph.D. in Pharmaceutical Chemistry, University of Hamburg
My major research interest is the discovery of new therapeutic agents for diseases related to cell proliferation and intracellular signaling. Specific targets of interest are the mitogen-activated protein kinase phosphatases (MKPs), cellular enzymes involved in cancer, inflammation, and myocardial ischemia that have largely eluded discovery efforts. An important part of my research is the development of analysis tools to increase information content of biological assays and to enable small molecule drug discovery in whole multicellular organisms such as zebrafish.
Salum LB, Mascarello A, Canevarolo RR, Altei WF, Laranjeira AB, Neuenfeldt PD, Stumpf TR, ChiaradiaDelatorre LD, Vollmer LL, Daghestani HN, Melo CP, Silveira AB, Leal PC, Frederico MJ, Nascimento LF, Santos AR, Andricopulo AD, Day BW, Yunes RA, Vogt A, Yunes JA, Nunes RJ (2015) N-3,4,5-trimethoxybenzohydrazide as microtubule destabilizer: Synthesis, cytotoxicity, inhibition of cell migration and in vivo activity against acute lymphoblastic leukemia European Journal of Medicinal Chemistry 96: 504-518.

Rosenker KM, Paquette WD, Johnston PA, Sharlow ER, Vogt A, Bakan A, Lazo JS, Wipf P (2015) Synthesis and biological evaluation of 3-aminoisoquinolin-1(2H)-one based inhibitors of the dual- specificity phosphatase Cdc25B. Bioorganic and Medicinal Chemistry 23: 2810-2818.

412-383-9146
vriesjk@pitt.edu
Office: BST3 3061
Lab Website
John K. Vries, MD - Associate Professor
M.D., University of California San Francisco
Asymmetry in the distribution of attributes along biological sequences generates signals with characteristic frequency and phase spectra. Asymmetry in the distribution of contacts in 3-dimensional models also generates signals with characteristic spectra. In some cases, these spectra are correlated. My research attempts to predict tertiary structure from these correlations. The long term goal is go develop an alignment-independent method for protein classification. The methodologies employed include n-gram analysis, Fourier analysis, eigenfunction decomposition and all poles spectral density estimation. In related research, correlations between the periodicity of pairwise relationships in molecular dynamics simulations and the results of Gaussian network analysis are compared.
Koes DR, Vries JK (2017) Error assessment in molecular dynamics trajectories using computed NMR chemical shifts Computational and Theoretical Chemistry 1099: 152-166.

Lui VW, Peyser ND, Ng PK, Hritz J, Zeng Y, Lu Y, Li H, Wang L, Gilbert BR, General IJ, Bahar I, Ju Z, Wang Z, Pendleton KP, Xiao X, Du Y, Vries JK, Hammerman PS, Garraway LA, Mills GB, Johnson DE, Grandis JR (2014) Frequent mutation of receptor protein tyrosine phosphatases provides a mechanism for STAT3 hyperactivation in head and neck cancer Proc Natl Acad Sci U S A 111(3): 1114-1119.

412-383-5743
xing1@pitt.edu
Office: BST3 3084
Lab Website
Jianhua Xing, PhD - Associate Professor
Ph.D., Theoretical Chemistry, University of California, Berkeley, 2002
The Xing lab is interested in the following fundamental questions. How do thousands of molecules species orchestrate temporally and spatially to determine a cell phenotype? How can one regulate and direct cell phenotype? Specifically, the lab currently focuses on Epithelial-to-Mesenchymal Transition (EMT), characterized by loss of cell-cell adhesion and increased cell motility. EMT plays important roles in embryonic development, tissue regeneration, wound healing and pathological processes such as fibrosis in lung, liver, and kidney, and cancer metastasis. The lab studies the coupled gene expression and epigenetic dynamics of EMT.
Zhang H, Tian X, Kim KS, Xing JH (2014) Statistical mechanics model for the dynamics of collective epigenetic histone modification, Physical Review Letters Physical Review Letters 112: 068101 .

Wang P, Song C, Zhang H, Wu Z, Tian XJ, Xing JH (2014) Epigenetic state network approach for describing cell phenotypic transitions Interface Focus 4(3): 20130068.
Research Faculty

412-648-9614
hoc2@pitt.edu
Office: BST3 3070
Lab Website
Mary H. Cheng, PhD - Research Assistant Professor
Ph.D. Chemical Engineering, Rensselaer Polytechnic Institute
I have modeling experience in a wide range of ion channels/transporters, including several types of sodium coupled neurotransmitter transporters, neurotransmitter-gated ion channels, voltage-gated ion channels/transporters, and gape junction Claudin-2. My research interest and expertise lie in protein modeling and medicinal chemistry, focusing on molecular mechanisms of i) transporter functions, i.e., transporter cycle; ii) ion transport through membrane protein channels, i.e. channel conductance and charge selectivity; iii) drug modulation of protein receptors, i.e. ligand binding sites and binding affinity; and iv) protein-lipid and lipid-lipid interactions. I am particularly interested in development/implement of multi-scale modeling technology to investigate biological systems at both molecular and cellular levels. I developed a hybrid molecular dynamics/Brownian dynamics methodology that can be applied to investigate ion permeation through membrane protein channels.
Cheng MH, Block E, Hu F, Cobanoglu MC, Sorkin A (2015) Insights into the Modulation of Dopamine Transporter Function by Amphetamine, Orphenadrine, and Cocaine Binding Front Neurol 6: 134.

Bahar I, Cheng MH, Lee JY, Kaya C, Zhang S (2015) Structure-Encoded Global Motions and Their Role in Mediating Protein-Substrate Interactions Biophys J .

412-383-5915
gough@pitt.edu
Office: BST3
Lab Website
Albert Gough, PhD - Research Associate Professor
Ph.D. in Biology/Biophysics, Carnegie Mellon University
My research is focused on relating in vitro cellular systems models to in vivo biological functions. Using automated high content imaging systems we are able to create cellular models with readouts that indicate a wide range of cellular functions. Alterations in function at the tissue, organ and organism level, should be related to alterations in cellular functions. However, the interactions and heterogeneity at the cellular level complicates that relationship. Presently we are building a cellular model in which to analyze cancer pathway interactions and heterogeneity. The goal is to provide an approach to developing therapies that address the heterogeneity of biological systems.
Vernetti L, Senutovitch N, Boltz R, DeBiasio R, Shun TY, Gough A, Taylor DL (2015) A human liver microphysiology platform for investigating physiology, drug safety and disease models J Exp Biol Med .

Senutovitch N, Vernetti L, Boltz R, DeBiasio R, Gough A, Taylor DL (2015) Fluorescent Protein Biosensors Applied to Microphysiological Systems Exp Biol Med .

412-648-7775
liubing@pitt.edu
Office: BST3 3085
Lab Website
Bing Liu, PhD - Research Assistant Professor
Ph.D. in Computational Systems Biology, National U of Singapore
Computational modeling and analysis of the dynamics of biological systems; development of high-performance computing, formal verification, and machine learning techniques for systems biology.
Liu B, Liu Q, Palaniappan S, Yang L, Bahar I, Thiagarajan PS, Ding JL (2016) Innate Immune Memory and Homeostasis May Be Conferred Through crosstalk between TLR3 and TLR7 Pathways Science Signaling 9: 436.

412-383-9893
mmiedel@pitt.edu
Office: BST W904
Lab Website
Mark T. Miedel, PhD - Research Assistant Professor
PhD in Cell Biology and Physiology, University of Pittsburgh School of Medicine
Identifying the mechanisms that cause resistance in ER ligand binding domain mutants, and to use this information to develop novel therapeutic strategies for the treatment of endocrine-resistant metastatic breast cancer.
Shanhang J, Miedel MT, Ngo M, Hessenius R, Wang P, Bahreini A, Li Z, Ding Z, Chen N, Shun TY, Zuckerman DM, Taylor DL, Puhalla SL, Lee AV, Oesterreich S, Stern AM (2017) Clinically observed estrogen receptor alpha mutations within the ligand-binding domain confer distinguishable phenotypes indicative of Darwinian-like somatic evolution Oncology .

412-648-3090
mes234@pitt.edu
Office: BST3 10045
Lab Website
Mark E. Schurdak, PhD - Visiting Research Associate Professor
Ph.D. in Pharmacology, Baylor College of Medicine
My research interests center on applying a systems biology/pharmacology approach to develop more effective drug discovery strategies that utilize integrated phenotype/function-based analysis (where all targets involved are functioning in a more physiologic relevant environment) and to better understand the molecular mechanisms that cause drugs to succeed or fail in the clinic.
Gough AH, Chen N, Shun TY, Lezon T, Boltz RC, Reese CE, Wagner J, Vernetti LA, Grandis JR, Lee AV, Stern AM, Schurdak ME, Taylor DL (2014) Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery PLoS One 9(7): e102678.

DAiuto L, Zhi Y, KumarDas D, Wilcox MR, Johnson JW, McClain L, MacDonald ML, DiMaio R, Schurdak ME, Piazza P, Viggiano L, Sweet R, Kinchington PR, Bhattacharjee AG, Yolken R, Nimgaonka VL (2014) Large-scale generation of human iPSC-derived neural stem cells/early neural progenitor cells and their neuronal differentiation ORGANOGENESIS 10: 365-377.

412-383-5806
ihs2@pitt.edu
Office: BST3 3089
Lab Website
Indira Shrivastava, PhD - Research Assistant Professor
Ph.D. University of Pune, Chemistry
Research Interests: I am interested in analyzing the functional dynamics of biomolecular complexes, molecular modeling and simulation approaches. The computational models I employ include: elastic network models (ANM/GNM), Molecular Dynamics (MD) simulations, and Quantum chemical (QM) calculations. The aim is to analyze the 3-D structure of the protein and its interactions with ligands and/or environment, as a function of space and time. I am also interested in harnessing allosteric properties of protein in identifying potential binding sites in targets and potential leads for drug-discovery.
Gasanov SE, Shrivastava I, Israilov FS, Kim AA, Rylova KA, Zhang B, Dagda RK (2015) Naja naja oxiana Cobra Venom Cytotoxins CTI and CTII Disrupt Mitochondrial Membrane Integrity: Implications for Basic Three-Fingered Cytotoxins PLoS One 10: .

Chu CT, Ji J, Dagda RK, Jiang JF, Tyurina YY, Kapralov AA, Tyurin VA, Yanamala N, Shrivastava I (2013) Cardiolipin externalization to the outer mitochondrial membrane acts as an elimination signal for mitophagy in neuronal cells Nat Cell Biol 15: 1197-1205.

412-648-9897
Sternam@pitt.edu
Office: BST3 10048
Lab Website
Andrew M. Stern, PhD - Research Associate Professor
Ph.D. in Biological Chemistry, University of California at Los Angeles
The overarching goal of our research is to identify mechanisms involved in complex human disease progression and use this knowledge to develop novel therapies for individual patients. We apply a holistic clinically relevant quantitative systems biology and pharmacology approach. This involves the development, implementation, and integration of several high throughput and high content molecular and cell-based technologies and models to comprehensively define fundamental biological processes that are perturbed in particular diseases.
Shanhang J, Miedel MT, Ngo M, Hessenius R, Wang P, Bahreini A, Li Z, Ding Z, Chen N, Shun TY, Zuckerman DM, Taylor DL, Puhalla SL, Lee AV, Oesterreich S, Stern AM (2017) Clinically observed estrogen receptor alpha mutations within the ligand-binding domain confer distinguishable phenotypes indicative of Darwinian-like somatic evolution Oncology .

Gough AH, Chen N, Shun TY, Lezon T, Boltz RC, Reese CE, Wagner J, Vernetti LA, Grandis JR, Lee AV, Stern AM, Schurdak ME, Taylor DL (2014) Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery PLoS One 9(7): e102678.

412-383-7475
shf28@pitt.edu
Office: BST3 3071
Lab Website
Shikhar Uttam, PhD - Research Assistant Professor
Ph.D. Electrical Engineering (Minor: Mathematics) The University of Arizona, Tucson
My research has two broad themes: 1. Cancer prognosis and prediction; 2. Development of new computational imaging, optical, and machine learning approaches. Within cancer research my focus has been on cancer prognosis in colorectal, breast, and esophageal disease models, where I have used computational imaging and physical optics to characterize alterations in precancerous cells with nanoscale sensitivity. Recently, my research scope has expanded to include understanding the tumor micro environment and its role in cancer progression and recurrence. This work focuses on machine learning approaches applied to multiplexed fluorescence imaging of tumor bio-markers to characterize and model the effect of tumor heterogeneity on cancer progression.
Uttam S, Pham HV, LaFace J, Leibowitz B, Yu J, Brand RE, Hartman DJ, Liu Y (2015) Early prediction of cancer progression by depth-resolved nanoscale mapping of nuclear architecture from unstained tissue specimens Cancer Res. 75: 4718-4727.

Uttam S, Liu Y (2015) Fourier phase in Fourier-domain optical coherence tomography J. Opt. Soc. Am. A 32: 2286-2306.

412-383-5856
vernetti@pitt.edu
Office: BST3
Lab Website
Larry Vernetti, PhD - Research Associate Professor
Ph.D. in Toxicology, University of Arizona
The focus of my research is developing early in vitro safety assessment and in vitro ADME models to identify risky compound candidates and allowing the drug developer to focus on fewer but more likely to succeed candidates. An important part of this research is the identification of the molecular mechanism of toxicity (MOA) within the cell, and then understanding how this can be used to predict target organ toxicity. The need for such an application is clear just by considering liver toxicity as an example. Despite decades of extensive animal testing, only half of the pharmaceutics which eventually produced clinical liver toxicity showed evidence of liver damage during animal trials. Bridging this gap is a necessary step forward to developing safer and effective drugs.
Vernetti L, Senutovitch N, Boltz R, DeBiasio R, Shun TY, Gough A, Taylor DL (2015) A human liver microphysiology platform for investigating physiology, drug safety and disease models J Exp Biol Med .

Senutovitch N, Vernetti L, Boltz R, DeBiasio R, Gough A, Taylor DL (2015) Fluorescent Protein Biosensors Applied to Microphysiological Systems Exp Biol Med .
Emeritus Faculty

412-648-3333
mailto:
Office:
Lab Website
Hagai Meirovitch, PhD - Professor Emeritus
Ph.D. in Statistical Mechanics, The Weizmann Institute of Science
Structure and function of proteins by the energetic and statistical approaches. Development of modeling of solvation, methods for calculating the entropy and the free energy of macromolecules and fluids (water), and simulation and conformational search techniques for protein systems. These methods are components of a new statistical mechanics methodology for treating flexibility applied to loops, peptides, and active sites to understand protein-protein and protein-ligand recognition processes (e.g., antibody-antigen interactions) and to analyze NMR and x-ray data of flexible molecules.
Cheluvaraja S, Meirovitch H (2006) Calculation of the entropy and free energy of peptides by molecular dynamics simulations using the hypothetical scanning molecular dynamics method J Chem Phys 124: 1.

White RP, Meirovitch H (2006) Free volume hypothetical scanning molecular dynamics method for the absolute free energy of liquids J Chem Phys 124: 204108.