Joseph C. Ayoob

Associate Professor, Computational & Systems Biology, Pitt

Publications

Ivet Bahar

• Biomolecular systems dynamics, multiscale modeling and simulations, computer-aided drug design, molecular and systems pharmacology, bridging sequence evolution, structure and function.

Ziv Bar-Joseph
*Currently on leave of absence

• Our group develops computational methods for understanding the interactions, dynamics and conservation of complex biological systems.

John P. Barton

• The evolution of pathogens such as HIV and SARS-CoV-2 presents a major threat to public health. My group works to combat this threat by studying how pathogens evolve and how they interact with the immune system. We’re particularly interested in questions related to the predictability of evolution and coevolution of hosts and pathogens. For example, which strains of a pathogen will become dominant in the near future? Can we control evolution to prevent pathogens from escaping immune control or developing resistance to drugs? Our work combines mathematical modeling, data analysis, and collaborations with experimentalists and clinicians to pursue these questions.

Publications

Carlos Camacho

• We develop new technologies to predict and model protein structures, their physical interactions, and substrates.

Oana Carja

• I work to quantitatively understand the evolutionary architecture of intelligent, collective systems, using the tools of dynamical systems, network theory, population genetics, machine learning and statistical inference, and widely available, yet underused, datasets.

Anne-ruxandra Carvunis

• Our research aims at understanding the molecular mechanisms of evolutionary change and innovation by examining systems biology in the light of evolution and evolution in the light of systems biology.

Wei Chen

• We develop statistical and computational methods for analyzing bulk and single-cell multi-omics data and understanding complex diseases such as childhood asthma and age-related macular degeneration.

Publications

Yu-Chih Chen

• We aim to establish comprehensive high-throughput multi-omics single-cell analysis including genome, epigenome, transcriptome, proteome, functional, and morphological methods. With large amounts of data collected from high-throughput single-cell multi-omics analysis, machine learning techniques can predict patient prognosis and suggest treatments for precision medicine.

Maria Chikina

Associate Professor, Computational & Systems Biology, Pitt

• The goal of Dr. Chikina’s research is to use genome scale data to advance our understanding of how genes contribute to the function of a complex organism, in health and disease.

Vaughn Cooper

Associate Professor, Microbiology and Molecular Genetics, Pitt

• We study evolution-in-action in the laboratory, in infections, and in cancers using genomics to identify and ultimately predict adaptations.

Jishnu Das

Assistant Professor, Immunology, Pitt

• Our research focuses on the development and use of machine-learning, high-dimensional statistical and topological network-analyses methods for biologically meaningful integration of multi-omic datasets. These analyses help us understand immune mechanisms in a wide range of contexts, encompassing both natural and vaccine-mediated immunity.

Dannie Durand

Associate Professor, Biological Sciences, CMU

• Computational molecular biology and computational genomics; especially, the evolution of genomic organization and function.

Jacob Durrant

Associate Professor, Biological Sciences, Pitt

• Develop broadly applicable, innovative computer-aided drug design (CADD) techniques and apply those techniques to further infectious-disease, neurological, and cancer drug discovery.

Publications

James Faeder

Program Director CPCB, Pitt
Associate Professor, Computational & Systems Biology, Pitt

• Developing mathematical models of biological regulatory processes that integrate specific knowledge about protein-protein interactions. 

Rachel Gottschalk

Assistant Professor, Immunology, Pitt

• Our lab uses quantitative approaches to understand how cells process stimuli to determine the appropriate functional response.  Identifying the activating receptors, kinases and trascription factors that make up signaling pathways is necessary but not sufficient to predict how a cell will respond.

Olexandr Isayev

Assistant Professor, Chemistry, CMU

• Theoretical and computational chemistry, machine learning, cheminformatics, drug discovery, computer-aided molecular design, materials informatics

Keisuke Ishihara

Assistant Professor, Computational and Systems Biology, Pitt

• Synthetic morphogenesis of 3D tissues. Brain and cardiac organoids. We integrate high-throughput 3D imaging, genome engineering, and pharmacology to control cell fate and tissue morphology.

Joshua Kangas

Assistant Teaching Professor, Computational Biology, CMU
Co-Director of MSAS Program, CMU

Publications

Seyoung Kim

Associate Professor, Computational Biology, Computer Science, CMU

• Developing statistical machine learning techniques to address significant methodological problems in computational genomics.

Carl Kingsford

Program Director CPCB, CMU
Hebert A. Simon Professor of Computer Science, Computational Biology, CMU

• Designing ML, combinatorial, and optimization algorithms to extract insight from genomics data.

David Koes

Program Associate Director CPCB, Pitt
Associate Professor, Computational & Systems Biology, Pitt

• We develop computational algorithms and full-scale systems to support rapid and inexpensive drug discovery and apply these methods to develop novel therapeutics.

Dennis Kostka

Associate Professor, Developmental Biology, Pitt

• We model epigenomic marks during differentiation and development and build methods to elucidate the role of transcriptional enhancer sequences in vertebrate left-right patterning.

Robin E. C. Lee

Associate Professor, Computational & Systems Biology, Pitt

• We use single cell experiments and mathematical models to understand how cells process information to make cell fate decisions.

Shuchang (Silvia) Liu

Assistant Professor, Pathology, Pitt

Our lab is interested in bioinformatics and biostatistics analysis on high-throughput genomic data, such as multi-omics Microarray and sequencing data.

Publications

Nate Lord

Assistant Professor, Computational & Systems Biology, Pitt

• Developing embryos must orchestrate the fates and movements of their cells with precision. However, precise control is no easy feat; genetic mutations, unexpected environmental perturbations and noisy signaling all threaten to scramble communication. Despite these challenges, development is remarkably robust. How do developing systems ensure precise pattern formation? How are mistakes corrected when they occur? Can we learn to engineer synthetic systems to have the reliability of developing embryos? Answers to these questions must span multiple scales, from signaling responses in individual cells to collective cell movement and morphogenesis. Our lab will tackle these questions with a combination of optogenetic manipulation, quantitative microscopy, computational modeling and classical embryology. Over the long run, we hope to learn the mechanistic principles that enable embryos to avoid and correct errors in development.

Xinghua Lu

Professor, Biomedical Informatics, Pitt

• Computational methods to identify signaling pathways underlying biological processes and diseases as well as statistical methods for acquiring knowledge from biomedical literature.

Jose Lugo-Martinez

Assistant Professor, Computational Biology, CMU
Co-Director of MSAS Program, CMU

• Developing the next generation of mechanism-driven computational methods to perform learning, inference, and decision-making on biomedical and health care data to accelerate scientific knowledge discovery and generate confident and testable data-driven discoveries.
  
  Publications

Jian Ma

Ray and Stephanie Lane Professor of Computational Biology, CMU

• Developing novel algorithms to study genome structure and function, chromatin and nuclear genome organization, and gene regulation in mammalian genomes as well as in cancer.

Natasa Miskov-Zivanov

Assistant Professor, Electrical and Computer Engineering, Bioengineering, Pitt

• Biological design automation and systems and synthetic biology.

Hosein Mohimani

Assistant Professor, Computational Biology, CMU

• Dr. Mohimani’s research focuses on the development of computational metabolomics and metagenomics methods for antibiotic discovery and microbiome analysis.

Robert F. Murphy

Ray and Stephanie Lane Professor of Computational Biology Emeritus, CMU

• Cell and computational biology. Experimental and computational methods to learn and represent how proteins are organized within eukaryotic cells.

Allyson F. O'Donnell

Assistant Professor, Biological Sciences, Pitt

• Our research focuses on how cells control protein localization in response to nutritional and environmental stressors. We are interested in gaining a deep mechanistic understanding of how the ‘decisions’ are made to selectively relocalize membrane proteins via vesicle-mediated trafficking in response to cellular signaling cues. We use a wealth of biochemical, genetic and cell biological approaches, including high content and systems level studies, in our work. Our research focuses on how cells control protein localization in response to nutritional and environmental stressors. We are interested in gaining a deep mechanistic understanding of how the ‘decisions’ are made to selectively relocalize membrane proteins via vesicle-mediated trafficking in response to cellular signaling cues. We use a wealth of biochemical, genetic and cell biological approaches, including high content and systems level studies, in our work.

Hatice Ülkü Osmanbeyoğlu

Assistant Professor, Biomedical Informatics, Pitt

• My research focuses on developing data-driven computational approaches to understand disease mechanisms in order to assist in the development of personalizing anticancer treatments.

Andreas Pfenning

Assistant Professor, Computational Biology, CMU

• The neurogenomics laboratory studies how genome sequence differences influence behavior and neurological disorder predisposition.

Roni Rosenfeld

Professor & Department Head Machine Learning, CMU
Professor, Language Technologies Institute, Computer Science, Computational Biology, CMU

• The long-term vision of our DELPHI research group is to make epidemiological forecasting as universally accepted and useful as weather forecasting is today.

Russell Schwartz

Professor & Department Head Computational Biology, CMU
Professor, Biological Sciences, CMU

• Computational genomics, population genetics, and phylogenetics, cancer heterogeneity and progression, computational biophysics, simulation and model inference of complex reaction networks.

Jason Shoemaker

Associate Professor, Chemical/Petroleum Engineering, Pitt

• Computationally Driven Discovery in Health Biological information – from molecular events to personal genomics – has exploded. Our group aims to develop computational approaches to exploit large-scale data to promote disease treatment discovery and optimization.

D. Lansing Taylor

Director, Drug Discovery Institute, Pitt
Distinguished Professor and Allegheny Foundation Professor of Computational & Systems Biology, Pitt

• I am focusing my efforts in Quantitative Systems Pharmacology in order to change the paradigm in drug discovery and development.

George Tseng

Professor and Vice Chair for Research, Department of Biostatistics, Pitt
Professor, Human Genetics, Computational & Systems Biology, Pitt

• We develop rigorous, timely, and useful statistical and computational methodologies to understand disease mechanisms and improve disease diagnosis and treatment.

Publications

Shikhar Uttam

Assistant Professor, Computational & Systems Biology, Pitt

• We study cancer systems biology of tumor microenvironments at multiple scales by integrating high-dimensional microscopy, imaging and data science, and systems and bioinformatics approaches.

Leila Wehbe

Assistant Professor, Machine Learning Department & Neuroscience Institute, CMU

• Her research is focused on computational modeling of the brain representation of language and other high-level tasks. She uses machine learning and neuroimaging -- fMRI and MEG -- to study how the brain represents information during complex naturalistic tasks. Her research is at the interface between natural language processing, machine learning and cognitive neuroscience.

Bryan Wilder

Assistant Professor, Machine Learning Department, Carnegie Mellon University 

Publications

Erik Wright

Assistant Professor, Biomedical Informatics, Pitt

• Developing new strategies for treating pathogens in the clinic, ultimately turning the tide against increasing antibiotic resistance.

Publications

Eric Xing
*Currently on leave of absence

Professor, Machine Learning, Language Technologies Institute, Computer Science, CMU

• We develop machine learning, statistical methodology, and computational systems for solving problems of learning, reasoning, and decision-making in artificial, biological, and social systems.

Jianhua Xing

Professor, Computational & Systems Biology, Pitt

• The lab currently focuses on Epithelial-to-Mesenchymal Transition (EMT), characterized by loss of cell-cell adhesion and increased cell motility.

Min Xu

Assistant Professor, Computational Biology, CMU
Co-Director of MSCB, CMU

• We develop computational methods for modeling cell organization derived from electron cryotomography 3D images.

Hassane Zarour, MD

Professor, Department of Medicine, Division of Hematology/Oncology
Professor, Department of Immunology
Professor, Department of Dermatology

• Our research focuses on translational cancer immunotherapy from the laboratory into the clinic and includes:

  1. The mechanisms of tumor-induced immune cell dysfunction, including the role of multiple inhibitory receptor pathways (PD-1, Tim-3, BTLA and TIGIT). 

  2. Novel combinatorial immunotherapies in cancer patients, including dual immune checkpoint blockades and intratumoral TLR9 agonist together with PD-1 blockade.

  3. Studies of the gut microbiome in cancer Immunotherapy. 

Publications

Bokai Zhu

Assistant Professor, Department of Medicine, Division of Endocrinology and Metabolism, Aging Institute of UPMC, Pitt

• 12h-clock, Hepatic Metabolic Homeostasis, Aging-associated Diseases