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Bruce J. Aronow, PhD Co-director, Computational Medicine Center
Co-director, Computational Medicine Center
Professor, UC Department of Pediatrics
Dr. Aronow's research is devoted to unraveling both the role and mechanism by which the functional capabilities of the human genome shape human health and our ability to adapt to stressful challenges. His lab is using a variety of available structural and functional genomic and biological systems descriptive data to form models of how biological systems assemble, adapt and become impaired in disease. The lab's overall hypothesis is that by interconnecting as much experimental and observational information as possible, we can gain new insights into the mechanisms by which different biological systems can achieve health or healthy adaptation, or undergo disease processes. More specific, with the co-leadership of Anil Jegga, DVM, the lab is identifying genetic features that control gene expression including cis-elements, trans factors and microRNAs, which normally work together in extended cell, tissue, organ and systems networks to enable development and homeostasis. Alterations of these features can alter phenotypes and increase or decrease disease. Some of the lab's work includes the identification of conserved, diverged and evolved cis-element clusters that are acted on by transcription and chromatin proteins. The lab has developed a Web-based tool called GenomeTraFaC that at present allows discovery of shared cis-elements in conserved non-coding sequences of mice and humans.
Barnes MG, Grom AA, Thompson SD, Griffin TA, Pavlidis P, Itert L, et al. Subtype-specific peripheral blood gene expression profiles in recent-onset juvenile idiopathic arthritis. Arthritis and rheumatism. 2009 Jul;60(7):2102-12.
Qu XA, Gudivada RC, Jegga AG, Neumann EK, Aronow BJ. Inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships. BMC Bioinformatics. 2009 May;10 Suppl 5:S4.
Gu Y, Harley IT, Henderson LB, Aronow BJ, Vietor I, Huber LA, et al. Identification of IFRD1 as a modifier gene for cystic fibrosis lung disease. Nature. 2009 Apr 23;458(7241):1039-42.
Nishijo K, Chen QR, Zhang L, McCleish AT, Rodriguez A, Cho MJ, et al. Credentialing a preclinical mouse model of alveolar rhabdomyosarcoma. Cancer Res. 2009 Apr 1;69(7):2902-11.
Chen J, Aronow BJ, Jegga AG. Disease candidate gene identification and prioritization using protein interaction networks. BMC Bioinformatics. 2009 Feb;10:73.
Shen H, Powers N, Saini N, Comstock CE, Sharma A, Weaver K, et al. The SWI/SNF ATPase Brm is a gatekeeper of proliferative control in prostate cancer. Cancer Res. 2008 Dec 15;68(24):10154-62.
Brunskill EW, Aronow BJ, Georgas K, Rumballe B, Valerius MT, Aronow J, et al. Atlas of gene expression in the developing kidney at microanatomic resolution. Developmental cell. 2008 Nov;15(5):781-91.
Mahller YY, Sakthivel B, Baird WH, Aronow BJ, Hsu YH, Cripe TP, et al. Molecular analysis of human cancer cells infected by an oncolytic HSV-1 reveals multiple upregulated cellular genes and a role for SOCS1 in virus replication. Cancer Gene Ther. 2008 Nov;15(11):733-41.
Kucherlapati MH, Yang K, Fan K, Kuraguchi M, Sonkin D, Rosulek A, et al. Loss of Rb1 in the gastrointestinal tract of Apc1638N mice promotes tumors of the cecum and proximal colon. Proc Natl Acad Sci U S A. 2008 Oct 7;105(40):15493-8.
Gudivada RC, Qu XA, Chen J, Jegga AG, Neumann EK, Aronow BJ. Identifying disease-causal genes using Semantic Web-based representation of integrated genomic and phenomic knowledge. J Biomed Inform. 2008 Oct;41(5):717-29.
Anil Goud Jegga, DVM, MRes
Associate Professor, UC Department of Pediatrics
Anil Jegga, DVM, MRes, is a biological and medically-oriented computational biologist. He has led bioinformatics analysis and database development initiatives and played a critical role in a variety of successful projects and consortia focusing on genetic and genomic biology of developmental systems, human disease and mouse disease models. His work focuses on the elucidation of gene regulatory networks and the interaction between genotype and phenotype using a variety of bioinformatics approaches. He has extensive experience in transcription factor and micro-RNA based gene regulatory mechanisms, gene polymorphism functional analysis, candidate disease gene identification and prioritization. To aid in the diffusion of genomics into biomedical research and education, Dr. Jegga works with Bruce Aronow, PhD, and their research lab has developed several approaches that integrate bioinformatics with clinical informatics. His current interests include elucidating the p53 tumor suppressor network. In collaboration with scientists at National Institute of Environmental Health Sciences, Dr. Jegga is exploring the evolution of p53 targets and recently reported the unexpected finding that rodents lack some of the evolution-based safeguards in p53 function as humans. Collaborating with researchers from National Institute for Cancer Research, Italy, he is exploring the microRNA-based regulatory mechanisms of the p53 master regulatory network and impact of sequence variations on it.
Rankin SA, Kormish J, Kofron M, Jegga A, Zorn AM. A gene regulatory network controlling hhex transcription in the anterior endoderm of the organizer. Dev Biol. 2011 Jan 4.
Kaimal V, Sardana D, Bardes EE, Gudivada RC, Chen J, Jegga AG. Integrative systems biology approaches to identify and prioritize disease and drug candidate genes. Methods Mol Biol. 2011;700:241-59.
Zhang X, Wang X, Zhu H, Zhu C, Wang Y, Pu WT, Jegga AG, Fan GC. Synergistic effects of the GATA-4-mediated miR-144/451 cluster in protection against simulated ischemia/reperfusion-induced cardiomyocyte death. J Mol Cell Cardiol. 2010 Nov;49(5):841-50.
Maldonado AR, Klanke C, Jegga AG, Aronow BJ, Mahller YY, Cripe TP, Crombleholme TM. Molecular engineering and validation of an oncolytic herpes simplex virus type 1 transcriptionally targeted to midkine-positive tumors. J Gene Med. 2010 Jul;12(7):613-23.
Sardana D, Vasa S, Vepachedu N, Chen J, Gudivada RC, Aronow BJ, Jegga AG. PhenoHM: human-mouse comparative phenome-genome server. Nucleic Acids Res. 2010 Jul;38(Web Server issue):W165-74.
Kaimal V, Bardes EE, Tabar SC, Jegga AG, Aronow BJ. ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems. Nucleic Acids Res. 2010 Jul;38(Web Server issue):W96-102.
Moyer K, Kaimal V, Pacheco C, Mourya R, Xu H, Shivakumar P, Chakraborty R, Rao M, Magee JC, Bove K, Aronow BJ, Jegga AG, Bezerra JA. Staging of biliary atresia at diagnosis by molecular profiling of the liver. Genome Med. 2010 May 13;2(5):33.
Miller SJ, Jessen WJ, Mehta T, Hardiman A, Sites E, Kaiser S, Jegga AG, Li H, Upadhyaya M, Giovannini M, Muir D, Wallace MR, Lopez E, Serra E, Nielsen GP, Lazaro C, Stemmer-Rachamimov A, Page G, Aronow BJ, Ratner N. Integrative genomic analyses of neurofibromatosis tumours identify SOX9 as a biomarker and survival gene. EMBO Mol Med. 2009 Jul;1(4):236-48.
Gowrisankar S, Jegga AG. Regression based predictor for p53 transactivation. BMC Bioinformatics. 2009 Jul 14;10:215.
Chen J, Bardes EE, Aronow BJ, Jegga AG. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res. 2009 Jul 1;37(Web Server issue):W305-11.
Michal Kouril, PhD Director, Research IT Services
leads the team that provides IT resources and support to the research community at Cincinnati Children’s. He also specializes in high performance computing applications in biomedical informatics and combinatorics.
Director, Research IT Services
Assistant Professor, UC Department of Pediatrics
Long (Jason) Lu, PhD
BS: Biotechnology/Bioengineering, Peking University, Beijing, China, 1998.
PhD: Biochemistry, specialized in Computational Molecular Biology, Washington University School of Medicine, St. Louis, MO, 2003.
Postdoc: Research Associate, Bioinformatics, Yale University, New Haven, CT, 2003-06.
Deng J, Deng L, Su S, Zhang M, Lin X, Wei L, Minai AA, Hassett DJ, Lu LJ. Investigating the predictability of essential genes across distantly related organisms using an integrative approach. Nucleic Acids Res. 2011 Feb;39(3):795-807.
Zhang M, Lu LJ. Investigating the validity of current network analysis on static conglomerate networks by protein network stratification. BMC Bioinformatics. 2010 Sep 16;11:466. Gordon SM, Deng J, Lu LJ, Davidson WS. Proteomic characterization of human plasma high density lipoprotein fractionated by gel filtration chromatography. J Proteome Res. 2010 Oct 1;9(10):5239-49. Xu Y, Zhang M, Wang Y, Kadambi P, Dave V, Lu LJ, Whitsett JA. A systems approach to mapping transcriptional networks controlling surfactant homeostasis. BMC Genomics. 2010 Jul 26;11:451.
Deng J, Wang W, Lu LJ, Ma J. A two-dimensional simulation model of the bicoid gradient in Drosophila. PLoS One. 2010 Apr;5(4):e10275.
Gordon S, Durairaj A, Lu LJ, Davidson WS. HDL proteomics: identifying new drug targets and biomarkers by understanding functionality. Current Cardiovascular Risk Report. 2010;4:1-8.
He F, Wen Y, Deng J, Lin X, Lu LJ, Jiao R, et al. Probing intrinsic properties of a robust morphogen gradient in Drosophila. Dev Cell. 2008 Oct;15(4):558-67.
Huang YJ, Hang D, Lu LJ, Tong L, Gerstein MB, Montelione GT. Targeting the human cancer pathway protein interaction network by structural genomics. Mol Cell Proteomics. 2008 Oct;7(10):2048-60. Wu L, Hwang SI, Rezaul K, Lu LJ, Mayya V, Gerstein M, et al. Global survey of human T leukemic cells by integrating proteomics and transcriptomics profiling. Mol Cell Proteomics. 2007 Aug;6(8):1343-53. Lu LJ, Sboner A, Huang YJ, Lu HX, Gianoulis TA, Yip KY, et al. Comparing classical pathways and modern networks: towards the development of an edge ontology. Trends Biochem Sci. 2007 Jul;32(7):320-31.
Jun Ma, PhD
investigates fundamental mechanisms of development through a combination of quantitative experimental approaches and theoretical and simulation approaches. One major focus of Ma’s lab concerns the questions of how morphogen gradients are established, and how precise positional information is encoded by these gradients and interpreted by cells in developing tissues.
Molecular mechanisms of gene regulation and embryonic development
Liu J, Ma J. Fates-shifted is an F-box protein that targets Bicoid for degradation and regulates developmental fate determination in Drosophila embryos. Nat Cell Biol. 2011 Jan;13(1):22-9.
He F, Saunders TE, Wen Y, Cheung D, Jiao R, ten Wolde PR, Howard M, Ma J. Shaping a morphogen gradient for positional precision. Biophys J. 2010 Aug 4;99(3):697-707.
Deng J, Wang W, Lu LJ, Ma J. A two-dimensional simulation model of the bicoid gradient in Drosophila. PLoS One. 2010 Apr 21;5(4):e10275.
He F, Wen Y, Deng J, Lin X, Lu LJ, Jiao R, Ma J. Probing intrinsic properties of a robust morphogen gradient in Drosophila. Dev Cell. 2008 Oct;15(4):558-67.
Baird-Titus JM, Clark-Baldwin K, Dave V, Caperelli CA, Ma J, Rance M. The solution structure of the native K50 Bicoid homeodomain bound to the consensus TAATCC DNA-binding site. J Mol Biol. 2006 Mar 10;356(5):1137-51.
Fu D, Ma J. Interplay between positive and negative activities that influence the role of Bicoid in transcription. Nucleic Acids Res. 2005 Jul 19;33(13):3985-93. Print 2005.
Chaney BA, Clark-Baldwin K, Dave V, Ma J, Rance M. Solution structure of the K50 class homeodomain PITX2 bound to DNA and implications for mutations that cause Rieger syndrome. Biochemistry. 2005 May 24;44(20):7497-511.
Ma J. Crossing the line between activation and repression. Trends Genet. 2005 Jan;21(1):54-9.
Fu D, Wen Y, Ma J. The co-activator CREB-binding protein participates in enhancer-dependent activities of bicoid. J Biol Chem. 2004 Nov 19;279(47):48725-33.
Ma J. Actively seeking activating sequences. Cell. 2004 Jan 23;116(2 Suppl):S75-6, 2 p following S76.
Keith Marsolo, PhD
leads the team that supports Cincinnati Children's i2b2
research data warehouse. His team
participates in a number of large clinical data sharing networks, and also has
a focus on developing tools to support multi-center quality improvement and
Dr. Keith Marsolo is an associate professor in the Division
of Biomedical Informatics. He led the
implementation of Cincinnati Children's research data warehouse, which utilizes
a custom version of the open-source i2b2 framework. The software allows users to perform
de-identified cohort queries, request datasets or biosamples for research
purposes, and in select cases, perform de-identified chart review. Dr. Marsolo and his team have developed
several other stand-alone applications that interface with the EHR, including a
tool that supports Cincinnati Children's research biobank. At the time of registration, patients are asked whether they would allow
their residual clinical samples to be kept for research purposes. The tool allows biobank personnel to query a
sample and then determine, based on the patient’s consent decision and several
other factors, whether it can be kept for research.
Dr. Marsolo is also heavily involved in the creation of data
collection and reporting systems to support multi-center quality improvement
and research networks, as well as query tools for a number of other federated
data sharing networks. Most recently,
led the design and development of an EHR-linked "enhanced" registry
for ImproveCareNow, a multi-center collaborative focused on improving care and
outcomes for children with inflammatory bowel disease. The registry allows users to collect data
directly in the EHR, where it can then be uploaded to the registry and used in
a number of different automated reports. Much of his most recent work involves projects to support the
development and implementation of the PCORI National Patient-Center Clinical
Research Network. Dr. Marsolo earned a bachelor’s in computer science and engineering, a master’s in biomedical engineering
and in computer and information science, and a PhD in computer and information science
from The Ohio State University.
BS: Computer Science and Engineering, The Ohio State University, Columbus, OH, 2002.
MS: Biomedical Engineering, The Ohio State University, Columbus, OH, 2005; Computer and Information Science, The Ohio State University, Columbus, OH, 2006.
PhD: Computer and Information Science, The Ohio State University, Columbus, OH, 2007.
Marsolo K, Spooner SA. Clinical genomics in the world of
the electronic health record. Genet Med. 2013 Oct; 15(10):786-91.
Bonafide CP, Brady PW, Keren R, Conway PH, Marsolo K,
Daymont C. Development of Heart and
Respiratory Rate Percentile Curves for Hospitalized Children. Pediatrics. 2013 Apr;131(4):e1150–7.
Natter MD, Quan J, Ortiz DM, Bousvaros A, Ilowite NT, Inman
CJ, Marsolo K, McMurry AJ, Sandborg CI, Schanberg LE, Wallace CA, Warren RW,
Weber GM, Mandl KD. An i2b2-based,
Generalizable, Open Source, Self-scaling Chronic Disease Registry. J Am Med Inform Assoc. 2013 Jan 1;20(1):172-9.
Marsolo K. Informatics
& operations – let’s get integrated. J Am Med Inform Assoc. 2013 Jan 1;20(1):122-4.
Deleger L, Molnar K, Savova G, Xia F, Lingren T, Li Q,
Marsolo K, Jegga A, Kaiser M, Stoutenborough L, Solti I. Large-scale evaluation of automated clinical note de-identification and
its impact on information extraction. J
Am Med Inform Assoc. 2013 Jan
Marsolo K, Corsmo J, Barnes MG, Pollick C, Nix J, Chalfin J,
Smith C, Ganta R. Challenges in Creating
an Opt-in Biobank with a Registrar-based Consent Process and a Commercial EHR.
J Am Med Inform Assoc. 2012 Nov-Dec;19(6):1115-8.
Marsolo, K. In Search
of a Data-in-Once, Electronic Health Record-Linked, Multicenter Registry— How
Far We Have Come and How Far We Still Have to Go. eGEMs (Generating Evidence & Methods to improve patient outcomes).
2012 Dec:1(1), Article 3.
Marsolo, K. Approaches to Facilitate Institutional
Review Board Approval of Multi-center Research Studies. Med
Care. 2012 Jul;50 Suppl:S77-81.
Wen H, Marsolo KA, Bennett EE, Kutten KS, Lipps DB, Plehn JF,
Epstein ND, Croisille P. Adaptive Postprocessing Techniques for
Myocardial Tissue Tracking with Displacement-Encoded MR Imaging. Radiology. 2008 Jan;246(1):229-40.
Marsolo K, Twa M, Bullimore MA, Parthasarathy S. Spatial Modeling and Classification of
Corneal Shape. IEEE Trans Inf Technol
Biomed. 2007 Mar;11(2):203-12.
John P. Pestian, PhD, MBA Director, Computational Medicine Center
Director, Computational Medicine Center
The founding director of the Division of Biomedical Informatics, Dr. Pestian now focuses on directing and developing the Computational Medicine Center (CMC). The CMC was established in 2003 by a $28 million grant from Ohio's Third Frontier Project.
Dr. Pestian's research lab is focused on using the science of natural language understanding in biomedical settings. Along with a growing list of collaborators, lab members focus on developing and implementing neuro-cognitive algorithms that enable computers to understand the concepts and semantic relationships within clinical text
Pestian J. A conversation with Edwin Shneidman. Suicide Life Threat Behav. 2010 Oct;40(5):516-23.
Pestian J, Spencer M, Matykiewicz P, Zhang K, Vinks AA, Glauser T. Personalizing Drug Selection Using Advanced Clinical Decision Support. Biomed Inform Insights. 2009 Jun 23;2:19-29.
Demner-Fushman D, Ananiadou S, Cohen KB, Pestian J, Tsujii J, Webber B. Themes in biomedical natural language processing: BioNLP08. BMC Bioinformatics. 2008 Nov 19;9 Suppl 11:S1.
Pestian JP, Matykiewicz P, Grupp-Phelan J, Lavanier SA, Combs J, Kowatch R. Using natural language processing to classify suicide notes. AMIA Annu Symp Proc. 2008 Nov 6:1091.
Duch W, Matykiewicz P, Pestian J. Neurolinguistic approach to natural language processing with applications to medical text analysis. Neural Netw. 2008 Dec;21(10):1500-10.
Matykiewicz P, Pestian J, Duch W, Johnson N. Unambiguous concept mapping in radiology reports: graphs of consistent concepts. AMIA Annu Symp Proc. 2006:1024.
Wade SL, Wolfe C, Brown TM, Pestian JP. Putting the pieces together: preliminary efficacy of a web-based family intervention for children with traumatic brain injury. J Pediatr Psychol. 2005 Jul-Aug;30(5):437-42.
Wade SL, Wolfe CR, Pestian JP. A web-based family problem-solving intervention for families of children with traumatic brain injury. Behav Res Methods Instrum Comput. 2004 May;36(2):261-9.
Siegel RM, Kiely M, Bien JP, Joseph EC, Davis JB, Mendel SG, Pestian JP, DeWitt TG. Treatment of otitis media with observation and a safety-net antibiotic prescription. Pediatrics. 2003 Sep;112(3 Pt 1):527-31.
Jegga AG, Sherwood SP, Carman JW, Pinski AT, Phillips JL, Pestian JP, Aronow BJ. Detection and visualization of compositionally similar cis-regulatory element clusters in orthologous and coordinately controlled genes. Genome Res. 2002 Sep;12(9):1408-17.
Nathan Salomonis, PhD
is a genomics and bioinformatics research scientist focusing on understanding
human development and genetic networks underlying disease. His lab develops
computational approaches to evaluate distinct modes of gene regulation and define
molecular networks that govern mammalian progenitor cell specification and
human disease pathology (e.g., Sudden Infant Death Syndrome) from genome-wide
Bioinformatics; genomics; alternative splicing; microRNA
biology; pathway analysis; pathway visualization; pathway curation; SIDS; stem
cell biology; cardiac specification; renal graft dysfunction
Our understanding of human health and ability to treat
disease is being radically transformed by new technologies to read genomes and
transcriptomes at an unprecedented resolution. To capitalize on these
technologies it is essential that we develop holistic models of gene biology
that will best inform clinicians of disease risk. Dr. Salomonis uses
computational approaches to examine the interplay between diverse modes of gene
regulation, including transcription, alternative splicing and microRNA
regulation that underlie important cellular interaction networks.
By applying such techniques to human disease and cellular
dysfunction paradigms, we strive to shed new light on existing problems. To
achieve these goals, we develop community available tools, such AltAnalyze and
GO-Elite, to analyze and interpret genome-level data that is accessible by both
untrained and skilled computational biologists alike. To identify global trends
from complex data sets, we take advantage of pathway-driven approaches, such as
WikiPathways models and aggregate large amounts of publically available data
from a broad range of developmental and disease datasets available in the
public domain. With these tools in hand, we strive to validate predicted
functional effects in the laboratory with a diverse team of collaborative
Soreq L, Salomonis N, Bronstein M, Greenberg DS, Israel Z,
Bergman H, Soreq H. Small RNA
sequencing-microarray analyses in Parkinson leukocytes reveal deep brain
stimulation-induced splicing changes that classify brain region transcriptomes.
Front Mol Neurosci. 2013 May 13;6:10.
Zambon AC, Gaj S, Ho I, Hanspers K, Vranizan K, Evelo CT,
Conklin BR, Pico AR, Salomonis N. GO-Elite:
a flexible solution for pathway and ontology over-representation. Bioinformatics. 2012 Aug
Salomonis N, Conklin BR. Stem cell pluripotency: alternative modes of transcription regulation.
Cell Cycle. 2010 Aug 15;9(16):3133-4.
Salomonis N, Emig D*, Baumbach J, Lengauer T, Conklin BR,
Albrecht M. AltAnalyze and DomainGraph:
analyzing and visualizing exon expression data. Nucleic Acids Res. 2010 Jul;38(Web Server issue):W755-62.
Salomonis N, Schlieve CR, Pereira L, Wahlquist C, Colas A,
Zambon AC, Vranizan K, Spindler MJ, Pico AR, Cline MS, Clark TA, Williams A,
Blume JE, Samal E, Mercola M, Merrill BJ, Conklin BR. Alternative splicing regulates mouse embryonic stem cell pluripotency
and differentiation. Proc Natl Acad
Sci U S A. 2010 Jun 8;107(23):10514-9.
Nakamura K, Salomonis N, Tomoda K, Yamanaka S, Conklin BR. G(i)-coupled GPCR signaling controls the
formation and organization of human pluripotent colonies. PLoS One. 2009 Nov 10;4(11):e7780.
Salomonis N, Nelson B, Vranizan K, Pico AR, Hanspers K,
Kuchinsky A, Ta L, Mercola M, Conklin BR. Alternative
splicing in the differentiation of human embryonic stem cells into cardiac
precursors. PLoS Comput Biol.
Stein T, Salomonis N, Nuyten DS, van de Vijver MJ, Gusterson
BA. Stein T, Salomonis N, Nuyten DS, van de Vijver MJ, Gusterson BA. A mouse mammary gland involution mRNA
signature identifies biological pathways potentially associated with breast
cancer metastasis. J Mammary Gland
Biol Neoplasia. 2009 Jun;14(2):99-116.
Salomonis N, Hanspers K, Zambon AC, Vranizan K, Lawlor SC,
Dahlquist KD, Doniger SW, Stuart J, Conklin BR, Pico AR. GenMAPP 2: new features and resources for pathway analysis. BMC Bioinformatics. 2007 Jun 24;8:217.
Salomonis N, Cotte N, Zambon AC, Pollard KS, Vranizan K,
Doniger SW, Dolganov G, Conklin BR. Identifying
genetic networks underlying myometrial transition to labor. 2005 Genome
for the Progenitor Cell Biology Consortium.
Co-Principle Investigator. National Institutes of Health, Heart, Lung
and Blood Institute. May 2013 - April 2016. U01HL099997.
Imre Solti MD, PhD
Information extraction from EHR; use of computational linguistics and machine learning in health services research; EHR data mining for medication safety and predictive modeling research; automated clinical trial eligibility screening
MD: Albert Szent-Gyorgyi Medical University, Szeged, Hungary, 1992.
PhD: Health Services Organization and Research, Virginia Commonwealth University, Richmond, VA, 2006.
MA: Computational Linguistics, University of Washington, Seattle, WA, 2011.
Stephen A. Spooner, MD, MS, FAAP Chief Medical Information Officer, Biomedical Informatics
practices general academic pediatrics and serves as the Chief Medical Information Officer for Cincinnati Children’s. He is active in the area of data standards in support of child health, and is currently the co-chair of the HL 7 child health work group. He is also co-chair of the Certification Commission for Health Information Technology inpatient work group.
Chief Medical Information Officer, Biomedical Informatics
Attending Physician, Division of Hospital Medicine
Michael Wagner, PhD Faculty Liaison, Biomedical Informatics Core
Faculty Liaison, Biomedical Informatics Core
Large-scale optimization; applications in bioinformatics
Visit the Wagner Lab.
Dipl. Wi-Ing.: Universitaet Karlsruhe, Germany, 1995.
MS: Operations Research, Cornell University, Ithaca, New York, 1998.
PhD: Operations Research, Cornell University, Ithaca, New York, 2000.
Matthew T. Weirauch, PhD
is a computational biologist. His lab seeks to understand the mechanisms of gene transcriptional regulation. Current projects focus on characterizing transcription factor binding specificities, and developing methods for modeling their interactions with DNA, both in vitro and in vivo. His lab applies insights from basic research on transcription factor-DNA interactions to study the mechanisms underlying complex diseases.
Transcription factors; transcriptional regulation; functional genomics; genome analysis
Visit the Weirauch Lab
Matthew T. Weirauch, PhD, a faculty member in the Center for Autoimmune Genomics and Etiology (CAGE), is a computational biologist with special emphasis on genomic approaches for studying transcription factor (TF) interactions with DNA, and how genetic variation proximal to these interactions contributes to human diseases. He recently spearheaded large-scale efforts for the experimental and computational determination of sequence binding motifs for eukaryotic TFs (Weirauch et al., Cell, 2014), and RNA binding proteins (Nature co-first author, 2013). He has also been involved in numerous high-profile genomics efforts, including an evaluation of algorithms for TF-DNA recognition (Weirauch et al., Nature Biotech, 2013), and the largest genetic interaction studies performed to date in both C. elegans (Byrne et al., Journal of Biology, 2007) and S. cerevisiae (Costanzo et al., Science, 2010). Recent work in his group focuses on how disease-associated genomic regions affect TF binding, and how these alterations affect disease onset and progression (Wang et al., Mol Cancer., 2010; Qian et al., Pediatr Blood Cancer, 2014; Kottyan et al., Nature Genetics, 2014; Martin et al., Circulation: Cardiovascular Genetics, 2014; Fang et al., Cell Reports, 2014).
The long-term goal of Dr. Weirauch's lab is to create an accurate computational system for predicting TF and RNA binding protein interactions with the genome/transcriptome, and for understanding the effects of genetic variations on these interactions. As it continues to mature, they are applying this system to predict the effects of genetic variants that are strongly associated with several human diseases. Long-term, they envision that this system will be used for personalized medicine-based approaches – given the genome sequence of a patient, it will produce a prioritized list of genetic variants likely to contribute to disease onset via alterations to protein binding events.
Postdoctoral Fellow: University of Toronto (Donnelly Center for Cellular and Biomolecular Research), Toronto, Ontario, Canada.
PhD: Bioinformatics, University of California Santa Cruz, Santa Cruz, California.
BSc: Computer Science, Pennsylvania State University, University Park, PA.
Weirauch M, Yang A, Albu M, Cote A, Montenegro-Montero A, Drewe P, Najafabadi H, Lambert S, Mann I, Cook K, Zheng H, Goity A, van Bakel H, Lozano J, Galli M, Lewsey M, Huang E, Mukherjee T, Chen X, Reece-Hoyes J, Govindarajan S, Shaulsky G, Walhout AJM, Bouget F, Ratsch G, Larrondo L, Ecker J, Hughes T. Determination and inference of eukaryotic transcription factor sequence specificity.
Cell. 2014 Sep 11;158(6):1431-1443.
Makashir S, Kottyan L, Weirauch M. Meta-analysis of Differential Gene Co-expression: Application to Lupus. Pacific Symposium on Biocomputing. 2014.
Kottyan L, Davis B, Sherrill J, Lui K, Rochman M, Kaufman K, Weirauch M, Vaughn S, Lazaro S, Rupert A, Kohram M, Stucke E, Kemme K, Magnusen A, He H, Dexheimer P, Mukkada V, Putnam P, Strauss A, Abonia JP, Martin L, Harley J, Rothenberg M. Genome-wide association analysis of eosinophilic esophagitis provides insight into the tissue specificity of this allergic disease. Nat Genet. 2014 Aug;46(8):895-900.
Sullivan A, Arsovski A, Lempe J, Bubb K, Weirauch M, et al. Mapping and Dynamics of Regulatory DNA and Transcription Factor Networks in A. thaliana.
Cell Reports. 2014 Sep 10.
Kottyan L, Zoller E, Bene J, Lu X, Kelly J, Rupert A, Lessard C, Vaughn S, Marion M, Weirauch M, et al. The IRF5-TNPO3 association with systemic lupus erythematosus (SLE) has two components that other autoimmune disorders variably share.
Hum Mol Genet. 2014 Sep 8.
Weirauch M, Cote A, Norel R, Annala M, Zhao Y, Riley T, Saez-Rodriguez J, Cokelaer T, Vedenko A, Talukder S, DREAM5 Consortium, et al. Evaluation of methods for modeling transcription factor sequence specificity.
Nature Biotechnology. 2013 Jan 27;31(2):126-34.
Ray D*, Kazan H*, Cook K*, Weirauch M*, Najafabadi H*, Li X, Gueroussov S, Albu M, Zheng H, Yang A, Na H, Irimia M, Matzat L, Dale R, Smith S, Yarosh C, Kelly S, Nabet B, Mecenas D, Li W, Laishram R, Qiao M, Lipshitz H, Piano F, Corbett A, Carstens R, Frey B, Anderson R, Lynch K, Penalva L, Lei E, Fraser A, Blencowe B, Morris Q, Hughes T. A compendium of RNA binding motifs for decoding gene regulation.
Nature. 2013 Jul 10;499(7457):172-177. *co-first authors.
Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear E, Sevier C, Ding H, Koh J, Toufighi K, Mostafavi S, Prinz J, St Onge R, VanderSluis B, Makhnevych T, Vizeacoumar F, Alizadeh S, Bahr S, Brost R, Chen Y, Cokol M, Deshpande R, Li Z, Lin Z, Liang W, Marback M, Paw J, San Luis B, Shuteriqi E, Tong A, van Dyk N, Wallace I, Whitney J, Weirauch M, Zhong G, Zhu H, Houry W, Brudno M, Ragibizadeh S, Papp B, Pál C, Roth F, Giaever G, Nislow C, Troyanskaya O, Bussey H, Bader G, Gingras A, Morris Q, Kim P, Kaiser C, Myers C, Andrews B, Boone C. The genetic landscape of a cell. Science. 2010 Jan 22;327(5964):425-31.
Byrne A, Weirauch M, Wong V, Koeva M, Dixon S, Stuart J, Roy P. A global analysis of genetic interactions in Caenorhabditis elegans.
J Biol. 2007;6(3):8.
ENCODE Project Consortium. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project.
Nature. 2007 Jun 14;447(7146):799-816.
Viral transcription factor interactions with disease-associated genetic variants. Principal Investigator. Trustee Award, CCHMC. Jul 2014 - Jun 2016.
Translational Genomics Analysis Core. Co-Investigator. NIH/NCRR CCTST T1 Pilot, Cincinnati Children's. Jul 2014 - Jun 2016.
Decoding C2H2 Zinc Fingers. Collaborator. Canadian Institutes of Health Research (CIHR) Operating Grant. Oct 2013 - Sep 2016.
Peter S. White, PhD Director, Division of Biomedical Informatics
has an active laboratory that is developing genomic analysis, natural language processing, data integration, and knowledge representation methods to help determine the molecular etiologies of particular pediatric diseases, including childhood cancer, ADHD, mitochondrial disorders, and congenital cardiac defects.
Director, Division of Biomedical Informatics
Professor, UC Department of Biomedical Informatics
Bioinformatics; biomedical informatics; genome informatics
Peter White, PhD, is the chair of the Division of Biomedical Informatics at the University of Cincinnati College of Medicine and Cincinnati Children's. In this role, he oversees informatics research and resources at both institutions, including academic, educational, data services, software development, and Research IT missions. Prior to 2014, Dr. White was research associate professor of pediatrics and section chief of Clinical Informatics at the University of Pennsylvania, and the recipient of the David Lawrence Altschuler Endowed Chair in Genomics and Computational Biology at The Children’s Hospital of Philadelphia (CHOP), where he served as director of the Center for Biomedical Informatics, faculty advisor of CHOP's Bioinformatics Core Facility, co-director of CHOP's Division of Genome Diagnostics, and co-director of the Bioinformatics in Translation section of the Penn/CHOP Clinical and Translational Science Award.
In his research career, Dr. White has explored the development and application of novel approaches for disease gene discovery, including identifying causative genes for neuroblastoma, ADHD, autism, and congenital heart defects. He has also developed innovative approaches for integrating and disseminating clinical, phenotypic, and molecular data to researchers for promoting discovery and hypothesis validation. Dr. White has recently played a lead informatics role on a number of national data projects, including the NICHD Newborn Screening Translational Research Network, the NHLBI Bench to Bassinet Program, the NHGRI Clinical Sequencing and Exploratory Research and IGNITE Consortia, and the NIDCD Audiology and Genetics Database.
Masino AJ, Dechene ET, Dulik MC, Wilkens A, Spinner NB, Krantz ID, Pennington JW, Robinson PN, White PS. Clinical phenotype-based gene prioritization: An initial study using semantic similarity and the Human Phenotype Ontology. BMC Bioinformatics. In press.
D’Alessandro LCA, Werner P, Xie HM, Hakonarson H, White PS, Goldmuntz E. The prevalence of 16p12.1 microdeletion in patients with left-sided cardiac lesions. Congenit Heart Dis. 2014; 9:83-86.
Pennington JW, Ruth B, Italia MJ, Miller J, White PS. Harvest. A Web-based biomedical data discovery and reporting application development platform. J Am Med Inform Assoc. 2014; 21:379-383.
Tarczy-Hornoch P, Amendola L, Aronson SJ, Garraway L, Gray S, Grundmeier RW, Hindorff LA, Jarvik G, Karavite D, Lebo M, Plon SE, Van Allen E, Weck KE, White PS, Yang Y. A survey of informatics approaches to whole exome and whole genome clinical reporting in the electronic medical record. Genet Med. 2013; 15:824-834.
Zhang Z, Leipzig J, Sasson A, Perin JC, Xie M, Sarmady M, Warren P, White P. Efficient digest of high-throughput sequencing data in a reproducible report. BMC Bioinformatics. 2013; 14 (Suppl 11):S3.
Tropeano M, Ahn JW, Dobson RJ, Breen G, Rucker J, Dixit A, Pal DK, McGuffin P, Farmer A, White PS, Andrieux J, Vassos E, Ogilvie CM, Curran S, Collier DA. Male-biased autosomal effect of 16p13.11 copy number variation in neurodevelopmental disorders. PLOS One. 2013; 8:e61365.
Zaidi S, Choi M, Wakimoto H, Ma L, Jianming J, Overton JD, Bjornson RD, Breitbart R, Carriero NJ, Cheung YH, Deanfield J, Glessner J, Hakonarson H, Italia M, Kaltman JR, Kaski J, Kim R, Kline JK, Lee T, Leipzig J, Alexander Lopez, Mane SM, Mitchell LE, Newburger J, Pe'er I, Porter G, Roberts A, Sachidanandam R, Sanders S, Seiden HS, State M, Subramanian S, Tikhonova IR, Warburton D, Wei Z, White PS, Williams IA, Zhao H, Seidman J, Brueckner M, Chung WK, Gelb BD, Goldmuntz E, Seidman CE, Lifton RP. Increased frequency of de novo mutations in histone modifying genes in congenital heart disease. Nature. 2013; 498:220–223.
Gai X, Xie HM, Perin JC, Takahashi N, Murphy K, Wenocur AS, D’arcy M, O’Hara RJ, Goldmuntz E, Grice DD, Shaikh TH, Hakonarson H, Buxbaum JD, Elia J, White PS. Rare structural variation of synapse and neurotransmission genes in autism. Molecular Psychiatry. 2012; 17:402-411.
Elia J, Joseph T. Glessner JT, Wang K, Takahashi N, Shtir CJ, Hadley D, Sleiman PMA, Haitao Zhang3, Kim CE, Robison R, Lyon GJ, Flory JH, Bradfield JP, Imielinski M, Hou C, Frackelton EC, Chiavacci RM, Sakurai T, Rabin C, Middleton FA, Thomas KA, Garris M, Mentch F, Freitag CM, Steinhausen H-C, Todorov AA, Reif A, Rothenberger A, Franke B, Mick EO, Roeyers H, Buitelaar J, Lesch K-P, Banaschewski T, Ebstein RP, Mulas F, Oades RD, Sergeant J, Sonuga-Barke E, Renner TJ, Marcel Romanos M, Romanos J, Warnke A, Walitza S, Meyer J, Pálmason H, Seitz C, Loo SK, Smalley SL, Joseph Biederman J, Kent L, Asherson P, Anney RJL, Gaynor JW, Shaw P, Devoto M, White PS, Grant SFA, Buxbaum JD, Rapoport JL, Williams NM, Nelson SF, Faraone SV, Hakonarson H. Genome-wide copy number variation study associates metabotropic glutamate receptor gene networks with attention deficit hyperactivity disorder. Nature Genetics. 2012; 44:78-84.
Elia J, Gai X, Hakonarson H, White PS. Structural variations in attention-deficit hyperactivity disorder. The Lancet. 2011; 377:377-378.
NHLBI Pediatric Translational Consortium Administrative Coordinating Center. Co-investigator. National Heart, Lung, and Blood Institute (NHLBI)/ National Institutes of Health (NIH). Mar 2011-Aug 2015.
Cincinnati Center for Clinical and Translational Sciences and Training. Co-investigator. National Center for Advancing Translational Sciences (NCATS) / National Institutes of Health (NIH). Apr 2009-Mar 2015.
Eric S. Hall, PhD
participates in a number of interdisciplinary teams investigating prematurity and neonatal disease. Along with coordinating data collection and exchange efforts, his work involves the application of knowledge discovery techniques to clinical data sets, as well as the development of software tools to assist in the summarization of clinical data and the modeling of clinical processes.
Eric S. Hall, PhD, participates in a number of interdisciplinary teams investigating prematurity and neonatal disease. Along with coordinating data collection and exchange efforts, his work involves the application of knowledge discovery techniques to clinical data sets as well as the development of software tools to assist in the summarization of clinical data and the modeling of clinical processes.
Hall ES, Poynton MR, Narus SP, Jones SS, Evans RS, Varner MW, Thornton SN. Patient-level analysis of outcomes using structured labor and delivery data. J Biomed Inform. 2009 Aug;42(4):702-9.
Hall ES, Thornton SN. Generating nurse profiles from computerized labor and delivery documentation. AMIA Annu Symp Proc. 2008 Nov 6:268-72.
Hall ES, Thornton SN. Extracting nursing practice patterns from structured labor and delivery data sets. AMIA Annu Symp Proc. 2007 Oct 11:309-13.
Hall ES, Poynton MR, Narus SP, Thornton SN. Modeling the distribution of Nursing Effort using structured Labor and Delivery documentation. J Biomed Inform. 2008 Dec;41(6):1001-8.
Hall ES, Thornton SN. Aiding clinicians through summarization of perinatal data. AMIA Annu Symp Proc. 2005:975.
Hall ES, Vawdrey DK, Knutson CD, Archibald JK. Enabling remote access to personal electronic medical records. IEEE Eng Med Biol Mag. 2003 May-Jun;22(3):133-9.
Johnson KJ, Hall ES, Boekelheide K. Kinesin localizes to the trans-Golgi network regardless of microtubule organization. Eur J Cell Biol. 1996 Mar;69(3):276-87.
Redenbach DM, Hall ES, Boekelheide K. Distribution of Sertoli cell microtubules, microtubule-dependent motors, and the Golgi apparatus before and after tight junction formation in developing rat testis. Microsc Res Tech. 1995 Dec 15;32(6):504-19.
Stivelman JC, Soucie JM, Hall ES, Macon EJ. Dialysis survival in a large inner-city facility: a comparison to national rates. J Am Soc Nephrol. 1995 Oct;6(4):1256-61.
Hall ES, Hall SJ, Boekelheide K. 2,5-Hexanedione exposure alters microtubule motor distribution in adult rat testis. Fundam Appl Toxicol. 1995 Feb;24(2):173-82.
Jarek Meller, PhD
Adamczak R, Pillardy J, Vallat BK, Meller J. Fast Geometric Consensus Approach for Protein Model Quality Assessment. J Comput Biol. 2011 Jan 18.
Yi Y, Mikhaylova O, Mamedova A, Bastola P, Biesiada J, Alshaikh E, Levin L, Sheridan RM, Meller J, Czyzyk-Krzeska MF. von Hippel-Lindau-dependent patterns of RNA polymerase II hydroxylation in human renal clear cell carcinomas. Clin Cancer Res. 2010 Nov 1;16(21):5142-52.
Shu D, Zhang H, Petrenko R, Meller J, Guo P. Dual-channel single-molecule fluorescence resonance energy transfer to establish distance parameters for RNA nanoparticles. ACS Nano. 2010 Nov 23;4(11):6843-53.
Swaminathan K, Adamczak R, Porollo A, Meller J. Enhanced prediction of conformational flexibility and phosphorylation in proteins. Adv Exp Med Biol. 2010;680:307-19.
Porollo A, Meller J. POLYVIEW-MM: web-based platform for animation and analysis of molecular simulations. Nucleic Acids Res. 2010 Jul;38(Web Server issue):W662-6.
Lam YW, Yuan Y, Isaac J, Babu CV, Meller J, Ho SM. Comprehensive identification and modified-site mapping of S-nitrosylated targets in prostate epithelial cells. PLoS One. 2010 Feb 5;5(2):e9075.
Shinde K, Phatak M, Johannes FM, Chen J, Li Q, Vineet JK, Hu Z, Ghosh K, Meller J, Medvedovic M. Genomics Portals: integrative web-platform for mining genomics data. BMC Genomics. 2010 Jan 13;11:27.
Tan M, Xia M, Chen Y, Bu W, Hegde RS, Meller J, Li X, Jiang X. Conservation of carbohydrate binding interfaces: evidence of human HBGA selection in norovirus evolution. PLoS One. 2009;4(4):e5058.
Haffey WD, Mikhaylova O, Meller J, Yi Y, Greis KD, Czyzyk-Krzeska MF. iTRAQ proteomic identification of pVHL-dependent and -independent targets of Egln1 prolyl hydroxylase knockdown in renal carcinoma cells. Adv Enzyme Regul. 2009;49(1):121-32.
Tan M, Xia M, Cao S, Huang P, Farkas T, Meller J, Hegde RS, Li X, Rao Z, Jiang X. Elucidation of strain-specific interaction of a GII-4 norovirus with HBGA receptors by site-directed mutagenesis study. Virology. 2008 Sep 30;379(2):324-34.
Yan Xu, PhD Director, Bioinformatics Microarray Core
focuses on bioinformatics applications and systems biology. Her research interests are the identification of gene signatures, regulatory networks and biological pathways controlling 1) surfactant homeostasis, 2) lung maturation, 3) lung cell type specific signaling and 4) asthma associated pathology. The goal is to gain better understanding of molecular mechanisms underlying lung development and pathogenesis.
Director, Bioinformatics Microarray Core
Bioinformatics; systems biology application in pulmonary research; lung cell type specific signaling; asthma associated pathology
BS: Pharmacology, Shanghai Medical University, China, 1986.
MS: Pathology, Shanghai Medical University, China, 1989.
PhD: Molecular and Cellular Pharmacology, University of South Alabama, Mobile, Alabama, 1997.
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