Computational and Systems Medicine: from theoretical models to advancing
health care
Ohio University Bioinformatics Distinguished Lecture
Co-organized by the Bioinformatics Core Facility and the Translational Biomedical
Sciences program
Professor Panagiotis (Takis) Benos
Regulatory Genomics and Systems Medicine laboratory
Department of Computational and Systems Biology
University of Pittsburgh School of Medicine
University of Pittsburgh Cancer Institute
Tuesday, April 21, 2015 at 1:30 in Walter 235
Abstract: “We swim in a sea of data...And the sea level is rising rapidly". This quote
accurately depicts how technology for biomedical data collection has inadvertently
transformed biology and medicine. Integrating and co-analyzing these different data
streams has become the research bottleneck and in all likelihood will be a central
research topic for the next decade. My group has historically worked on the
development of statistical and computational methods to model key biological
processes, like transcription factor binding and microRNA processing. More recently
we became interested in how we can combine the power of genomics with the rich
medical data that are available. In this talk, I will present examples of how
computational models rooted in basic science and engineering (physics and machine
learning) can help identify disease causes or stratify patient populations for disease
treatment.
Personal statement: Prof. Benos is the head of the Regulatory Genomics and
Systems Medicine laboratory and the Vice Chair for Academic Affairs at the
Department of Computational and Systems Biology, University of Pittsburgh School
of Medicine. He is also a member of the University of Pittsburgh Cancer Institute
(UPCI) and holds joint appointments in the departments of Biomedical Informatics
and Computer Science. The long-standing goal of his laboratory is to understand and
model gene networks and how their de-regulation leads to chronic diseases. In the
past, they have developed statistical and machine learning algorithms to model
various biological systems, like transcription factor and microRNA binding to their
corresponding targets, and transcriptional and post-transcriptional regulatory
networks in disease. They also developed methods for clustering and classification of
high-throughput data and biological motifs. They routinely make their algorithms
available to the public via web servers they develop, the most successful of which
are STAMP for comparison of DNA motifs, mirConnX for reverse engineering
regulatory networks from gene and microRNA expression data and ComiR for
identification of targets of sets of microRNAs with known expression values. Prof.
Benos collaborates with many researchers at the University of Pittsburgh and
Carnegie Mellon University.
More recently he and his group started working in integration and co-analysis of
heterogeneous datasets, including clinical variables with omics and other types of
data. Dr. Benos’ group is part of the Center for Causal Modeling and Discovery, one
of the 12 such centers in the US funded by NIH under the Big Data to Knowledge
(BD2K) initiative. His role in this center is to lead the effort in one of the Driving
Biomedical Problems (DBPs). In particular, his group and colleagues will develop
graphical model algorithms to co-analyze clinical variables, omics data and tissue
image data from IPF and COPD patients to infer associations between variables (e.g.,
gene expression and lung tissue image features) and to be used for improving
diagnosis of chronic lung diseases, like COPD and IPF. In addition, Prof. Benos was
recently awarded an R01 grant to develop new methodologies for data integration
and co-analysis aiming at new biomarker discovery in melanoma therapies.
Prof. Benos is also deeply committed to the educational mission of the University of
Pittsburgh. He was involved early on in the discussions that led to the establishment
of the Joint CMU-Pitt PhD Program in Computational Biology (CPCB), which he served
as Associate Director from 2007-2009 and as Director from 2009-2013 He serves as
PI on the successfully renewed T32 NIH grant, which supports this program. He is
also currently serving as Associate Director of a newly established PhD program in
Integrative Systems Biology (ISB) at the University of Pittsburgh.
The total number of Dr. Benos peer-reviewed publications is 55, including 7
publications in conference proceedings (peer-reviewed) indexed by PubMed and ISI
Web of Science; and 47 publications in international journals, like Nature, Science,
Proc Natl Acad Sci USA, Genome Research, Genome Biology, EMBO Reports, PLoS
Comput Biol, Journal of Molecular Biology, Nucleic Acids Research, etc. In addition,
Dr. Benos has published 6 invited book chapters and 2 invited reviews. Seventeen of
the peer-reviewed articles were published in the last five years (2010-now), while 21
of the peer-reviewed articles were published after Dr. Benos became Associate
Professor (2009-now). The total number of citations received by April 10, 2015 was
3,109. This number does not include the 5,317 citations that one of his early
publications has received to date. Dr. Benos’ H-index is 27 (all data from Google
Scholar, Apr 10, 2015). Dr. Benos is the primary author (first or last/corresponding) in
half of his peer-reviewed publications (26 of 55).