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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. 2014 Jul 21;15:248.
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.
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.
Master of Research: University of York, England, UK.
Master of Veterinary Science: College of Veterinary Science, Hyderabad, India.
Bachelor of Veterinary Science & Animal Husbandry: College of Veterinary Science, Hyderabad, India.
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
BS: Peking University, 1978-1982.
PhD: Harvard University, Cambridge, MA, 1983-1988 (degree awarded 1990).
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 research networks.
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.
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.
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 experimental datasets.
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
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
Michael Wagner, PhD, works on applications of machine learning techniques to bioinformatics problems such as protein structure prediction, disease classification and protein identification. His research lab currently is investigating machine-learning-based scoring algorithms for peptide mass fingerprinting to better understand how to optimally mine mass spectrometry data to make high-confidence predictions of protein identities. The underlying computational engine for many of these problems is a massively parallel implementation of a linear programming solver (PCx), which can solve large-scale support vector regression, support vector machine and linear feasibility problems.
Dr. Wagner also is involved in collaborations to perform genome-wide association studies, where his work has concentrated on developing an adequate, rapid data flow infrastructure that includes parallelized genotype calling algorithms.
Dipl. Wi-Ing.: Universitaet Karlsruhe, Germany, 1995.
MS: Operations Research, Cornell University, Ithaca, NY, 1998.
PhD: Operations Research, Cornell University, Ithaca, NY, 2000.
Thompson SD, Sudman M, Ramos PS, Marion MC, Ryan M, Tsoras M, Weiler T, Wagner M, Keddache M, Haas JP, Mueller C, Prahalad S, Bohnsack J, Wise CA, Punaro M, Zhang D, Rosé CD, Comeau ME, Divers J, Glass DN, Langefeld CD. The susceptibility loci juvenile idiopathic arthritis shares with other autoimmune diseases extend to PTPN2, COG6, and ANGPT1. Arthritis Rheum. 2010 Nov;62(11):3265-76.
Freudenberg JM, Sivaganesan S, Wagner M, Medvedovic M. A semi-parametric Bayesian model for unsupervised differential co-expression analysis. BMC Bioinformatics. 2010 May 7;11:234.
Jain R, Wagner M. Kolmogorov-Smirnov scores and intrinsic mass tolerances for peptide mass fingerprinting. J Proteome Res. 2010 Feb 5;9(2):737-42.
Jain A, Velayutham P, Wagner M, Butler DL. Accessing the tissue engineering literature: a new paradigm. Tissue Eng Part A. 2008 Mar;14(3):459-60.
Judith W. Dexheimer, PhD
is a biomedical informatics researcher with an interest in clinical decision support systems with a goal of improving clinical care and patient outcomes. Her research focuses on decision support in the emergency department with an interest in the effectiveness and efficacy of alerts and reminders throughout the hospital.
Medical informatics; clinical decision support; artificial intelligence
Judith Dexheimer, PhD, has a background in developing, implementing and evaluating clinical information systems including clinical decision systems, organizational and workflow aspects of informatics applications, computerized applications for emergency medicine and implementation of artificial intelligence techniques, computerized guideline applications and evidence-based medicine, public health informatics, and preventive care measures.
Her research focuses on the design, implementation and evaluation of clinical decision support systems in pediatric emergency medicine to improve clinical care.
PhD: Biomedical Informatics, Vanderbilt University, Nashville, TN, 2011.
MS: Biomedical Informatics, Vanderbilt University, Nashville, TN, 2006.
Dexheimer JW, Abramo TJ, Arnold DH, Johnson KB, Shyr Y, Ye F, Fan K, Patel N, Aronsky D. An Asthma Management System in a Pediatric Emergency Department. Int J Med Inform. 2012.
Dexheimer JW, Talbot TR, Ye F, Shyr Y, Jones I, Gregg WM, Aronsky D. A Computerized Pneumococcal Vaccination Reminder System in the Adult Emergency Department. Vaccine. 2011 Sept;29(40):7035-41.
Dexheimer JW, Arnold DH, Abramo TJ, Aronsky D. Development of an Asthma Management System in a Pediatric Emergency Department. AMIA Annu Symp Proc. 2009 Nov;142-46.
Dexheimer JW, Sanders DL, Rosenbloom ST, Talbot TR, Aronsky D. Prompting Clinicians: A Systematic Review of Preventive Care Reminders. J Am Med Inform Assoc. 2008 May-Jun;15(3):311-20.
Biggerstaff JP, Weidow B, Dexheimer J, Warnes G, VIdosh J, Patel S, Newman M, Patel P. Soluble fibrin inhibits lymphocyte adherence and cytotoxicity against tumor cells: implications for cancer metastasis and immunotherapy. Clin Appl Thromb Hemost. 2008 Apr;14(2):193-202.
Dexheimer JW, Brown LE, Leegon J, Aronsky D. Comparing Decision Support Methodologies for Identifying Asthma Exacerbations. Medinfo. 2007;12(Pt 2):880-4.
Dexheimer JW, Jones I, Chen Q, Talbot TR, Mason D, Aronsky D. Providers’ Beliefs, Attitudes, and Behaviors Prior to Implementing a Computerized Pneumococcal Vaccination Reminder. Acad Emerg Med. 2006 Dec;13(12):1312-18.
Biggerstaff JP, Weidow BL, Vidosh J, Dexheimer J, Patel S, Patel P. Soluble Fibrin Inhibits Monocyte Adherence and Cytotoxicity against Tumor Cells: Implications for Cancer Metastasis. Thrombosis Journal. 2006 Aug 22;4(1):12.
Dexheimer JW, Gregg W, Talbot TR, Aronsky D. Creating and Validating a Pneumococcal Vaccination Registry. AMIA Annu Symp Proc. 2005;201-5.
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.
Biomedical informatics; clinical informatics; data linkage; infant mortality; maternal child health; neonatal abstinence syndrome; preterm birth; public health informatics
Eric S. Hall, PhD, is a biomedical informaticist and researcher focused on improving perinatal health outcomes in at-risk populations. Dr. Hall currently leads data management and integration supporting research and quality improvement within the Cincinnati Children's Hospital Medical Center Perinatal Institute.
Dr. Hall's primary interests involve the linkage and integration of disparate data sets to facilitate the analysis of high-risk populations. These maternal and child health data include hospital electronic health records, vital records, geospatially-based measures from the American Communities Survey and other public data resources, and measures collected by community-based programs. While his principal focus has been on preterm birth and infant mortality reduction, Dr. Hall's interests extend to other high-risk maternal and child populations including those affected by withdrawal following in utero exposure to narcotics.
Dr. Hall has participated as a key member of many interdisciplinary teams within the Perinatal Institute and as part of multi-institutional collaborations. He is also the director of data analysis and management for Cradle Cincinnati, a collective impact collaborative to reduce infant mortality in Hamilton County, Ohio.
PhD: University of Utah, Salt Lake City, UT, 2008.
MS: Brigham Young University, Provo, UT, 2003.
BS: Brigham Young University, Provo, UT, 2001.
Li Q, Kirkendall ES, Hall ES, Ni Y, Lingren T, Kaiser M, Lingren N, Zhai H, Solti I, Melton K. Automated Detection of Medication Administration Errors in Neonatal Intensive Care. J Biomed Inform. 2015 Jul 16.
Hall ES, Wexelblatt SL, Crowley M, Grow JL, Jasin LR, Klebanoff MA, McClead RE, Meinzen-Derr J, Mohan VK, Stein H, Walsh MC. A multicenter cohort study of treatments and hospital outcomes in neonatal abstinence syndrome. Pediatrics. 2014 Aug;134(2):e527-34.
Hall ES, Folger AT, Kelly EA, Kamath-Rayne BD. Evaluation of gestational age estimate method on the calculation of preterm birth rates. Matern Child Health J. 2014 Apr;18(3):755-62.
Goyal NK, Hall ES, Ammerman RT, Meinzen-Derr JK, Jones DE, Short JA, Van Ginkel JB. Association of maternal and community factors with enrollment in home visiting among at-risk, first time mothers. Am J Public Health. 2014 Feb;104 Suppl 1:S144-51.
Hall ES, Goyal NK, Ammerman RT, Miller M, Jones DE, Short JA, Van Ginkel JB. Development of a linked perinatal data resource from state administrative and community-based program data. Matern Child Health J. 2014 Jan;18(1):316-25.
Goyal NK, Hall ES, Meinzen-Derr JK, Kahn RS, Short JA, Van Ginkel JB, Ammerman RT. Dosage effect of prenatal home visiting on pregnancy outcomes in at-risk, first-time mothers. Pediatrics. 2013 Nov;132 Suppl 2:S118-25.
South AP, Jones DE, Hall ES, Huo S, Meinzen-Derr J, Liu L, Greenberg JM. Spatial analysis of preterm birth demonstrates opportunities for targeted intervention. Matern Child Health J. 2012 Feb;16(2):470-8.
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, 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, 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.
Kenneth M. Kaufman, PhD
investigates the genetics of complex and rare disorders using genotyping and next-generation DNA technologies. The goal of his research is to identify the underling mechanisms and genetics that lead to complex diseases such as systemic lupus erythematosus.
A large portion of Dr. Kaufman's research career has been on the genetics of systemic lupus erythematsus. Their work has screened 10's of thousands of lupus cases and controls with millions of polymorphic markers. This work has results in the identification, replication and/or fine mapping of over 70 genetic associations with systemic lupus erythematsus.
Recently, they have taken advantage of next generation DNA sequencing to identify variants that directly cause disease. They have developed a number of bioinformatic pipelines that can be applied to any phenotype. These automated pipelines are part of the Cincinnati Analytical Suite for Sequencing Informatics (CASSI) which has been applied to more than 20 different diseases and provides a list of candidate causative variants that lead to disease.
Patel ZH, Kottyan LC, Lazaro S, Williams MS, Ledbetter DH, Tromp H, Rupert A, Kohram M, Wagner M, Husami A, Qian Y, Valencia CA, Zhang K, Hostetter MK, Harley JB, Kaufman KM. The struggle to find reliable results in exome sequencing data: filtering out Mendelian errors. Front Genet. 2014 Feb 12;5:16.
Kaufman KM, Linghu B, Szustakowski JD, Husami A, Yang F, Zhang K, Filipovich AH, Fall N, Harley JB, Nirmala NR, Grom AA. Whole-exome sequencing reveals overlap between macrophage activation syndrome in systemic juvenile idiopathic arthritis and familial hemophagocytic lymphohistiocytosis. Arthritis Rheumatol. 2014 Dec;66(12):3486-95.
Kottyan LC, Zoller EE, Bene J, Lu X, Kelly JA, Rupert AM, Lessard CJ, Vaughn SE, Marion M, Weirauch MT, Namjou B, Adler A, Rasmussen A, Glenn S, Montgomery CG, Hirschfield GM, Xie G, Coltescu C, Amos C, Li H, Ice JA, Nath SK, Mariette X, Bowman S; UK Primary Sjögren's Syndrome Registry, Rischmueller M, Lester S, Brun JG, Gøransson LG, Harboe E, Omdal R, Cunninghame-Graham DS, Vyse T, Miceli-Richard C, Brennan MT, Lessard JA, Wahren-Herlenius M, Kvarnström M, Illei GG, Witte T, Jonsson R, Eriksson P, Nordmark G, Ng WF; UK Primary Sjögren's Syndrome Registry, Anaya JM, Rhodus NL, Segal BM, Merrill JT, James JA, Guthridge JM, Scofield RH, Alarcon-Riquelme M, Bae SC, Boackle SA, Criswell LA, Gilkeson G, Kamen DL, Jacob CO, Kimberly R, Brown E, Edberg J, Alarcón GS, Reveille JD, Vilá LM, Petri M, Ramsey-Goldman R, Freedman BI, Niewold T, Stevens AM, Tsao BP, Ying J, Mayes MD, Gorlova OY, Wakeland W, Radstake T, Martin E, Martin J, Siminovitch K, Moser Sivils KL, Gaffney PM, Langefeld CD, Harley JB, Kaufman KM. The IRF5-TNPO3 association with systemic lupus erythematosus has two components that other autoimmune disorders variably share. Hum Mol Genet. 2015 Jan 15;24(2):582-96.
Kaufman KM, Zhao J, Kelly JA, Hughes T, Adler A, Sanchez E, Ojwang JO, Langefeld CD, Ziegler JT, Williams AH, Comeau ME, Marion MC, Glenn SB, Cantor RM, Grossman JM, Hahn BH, Song YW, Yu CY, James JA, Guthridge JM, Brown EE, Alarcón GS, Kimberly RP, Edberg JC, Ramsey-Goldman R, Petri MA, Reveille JD, Vilá LM, Anaya JM, Boackle SA, Stevens AM, Freedman BI, Criswell LA, Pons Estel BA; Argentine Collaborative Group, Lee JH, Lee JS, Chang DM, Scofield RH, Gilkeson GS, Merrill JT, Niewold TB, Vyse TJ, Bae SC, Alarcón-Riquelme ME; BIOLUPUS network, Jacob CO, Moser Sivils K, Gaffney PM, Harley JB, Sawalha AH, Tsao BP. Fine mapping of Xq28: both MECP2 and IRAK1 contribute to risk for systemic lupus erythematosus in multiple ancestral groups. Ann Rheum Dis. 2013 Mar;72(3):437-44.
Eric S. Kirkendall, MD, MBI, FAAP Associate Chief Medical Information Officer, Information Services
performs research in patient safety, quality improvement, and resource utilization. He is particularly interested in the design and development of novel software and applications to address complex healthcare system challenges, employing techniques such as real-time data acquisition, advanced analytics, artificial intelligence, human factors, and user-centered design.
Associate Chief Medical Information Officer, Information Services
Attending Hospitalist, Division of Hospital Medicine
Clinical Informaticist, Division of Biomedical Informatics
UC Department of Biomedical Informatics
Eric Kirkendall, MD, MBI, is an assistant professor of Pediatrics at Cincinnati Children’s Hospital Medical Center within the University of Cincinnati College of Medicine. He is the first Associate CMIO in Cincinnati Children's history and oversees the design, implementation, and optimization of the electronic health record and other associated technologies.
From a research perspective, Dr. Kirkendall co-leads the Decision Support Analytics Workgroup (DSAW), which investigates the links between the effectiveness of clinical decision support (CDS), patient safety, and user efficiency. His research has demonstrated ties between decreasing alert burden on clinicians, increasing CDS alert salience, and improving patient outcomes.
Many of Dr. Kirkendall’s research projects have also incorporated artificial intelligence techniques (e.g., natural language processing) and other innovative methods to detect adverse events/harm across multiple hospital environments. These techniques are innovative because they allow investigators to use unstructured data that would otherwise be unavailable for analysis. The results have shown vast improvements in detecting errors related to medication administrations. This R21-funded work has led to a R01 grant proposal that is in the pre-award phase currently.
Pediatric acute kidney injury (AKI) results from needless exposure to nephrotoxic medications (NTMx). At CCHMC, Dr. Kirkendall worked with the Center for Acute Care Nephrology to develop a catalog of detection and risk-stratifying electronic triggers that have resulted in NTMx-AKI reductions of 25-50% across four novel metrics, preventing over 400 children from developing AKI. He has led the development of these triggers, as well as development of a custom application that is key to data collection and improvement methods. This work has spread to 9 other sites, with spread to approximately 80 more sites planned.
BS: Biology, University of Toledo, Toledo, OH, 1999.
MD: University of Cincinnati, Cincinnati, OH, 2003.
Residency: Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 2006.
MBI: Oregon Health & Science University, Portland, OR, 2012.
Certification: American Board of Pediatrics, 2006; Clinical Informatics, 2014.
Li Q, Kirkendall ES, Hall ES, Ni Y, Lingren T, Kaiser M, Lingren N, Zhai H, Solti I. Automated Detection of Medication Administration Errors in Neonatal Intensive Care. Journal of Biomedical Informatics. 2015 Jul 15.
Stockwell DC, Bisarya H, Classen DC, Kirkendall ES, Landrigan CP, Lemon V, Tham E, Hyman D, Lehman SM, Searles E, Hall M, Muething SE, Sharek PJ. A Trigger Tool to Detect Harm in Pediatric Inpatient Settings. Pediatrics. 2015 Jun;135(6)1036-42.
Lehmann CU, Council on Clinical Information Technology, Weinberg ST, Alexander GM, Beyer EL, Del Beccaro MA, Francis AB, Handler EG, Johnson TD, Kirkendall ES, Lighter DE, Morgan SJ, Raskas MD, Tham E, Webber EC. Pediatric Aspects of Inpatient health Information Technology Systems. Pediatrics. 2015 Mar.
Stockwell DC, Bisarya H, Classen DC, Kirkendall ES, Lachman PI, Matlow AG, Tham E, Hyman D, Lehman SM, Searles E, Muething SE, Sharek PJ. Development of an Electronic Pediatric All-Cause Harm Measurement Tool Using the Modified Delphi Method. Journal of Patient Safety. 2014 Aug 26.
Kirkendall ES, Spires WL, Mottes TA, Schaffzin JK, Barclay C, Goldstein SL. Development and Performance of Electronic Acute Kidney Injury Triggers to Identify Pediatric Patients at Risk for Nephrotoxic Medication-associated Harm. Applied Clinical Informatics. 2014 Apr 2;5(2):313-33.
Li Q, Melton K, Lingren T, Kirkendall ES, Hall E, Zhai H, Ni Y, Kaiser M, Stoutenborough L, Solti I. Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care. J Am Med Inform Assoc. 2014 Sep;21(5):776-84.
Kirkendall ES, Kouril M, Minich T, Spooner SA. Analysis Of Electronic Medication Orders With Large Overdoses: Opportunities For Mitigating Dosing Errors. Applied Clinical Informatics. 2014;5(1):25-45.
Goldstein SL, Kirkendall E, Nguyen H, Schaffzin JK, Bucuvalas J, Bracke
T, Seid M, Ashby M, Foertmeyer N, Brunner L, Lesko A, Barclay C, Lannon
C, Muething S. Electronic Health Record Identification of Nephrotoxin
Exposure and Associated Acute Kidney Injury. Pediatrics. 2013
Kirkendall ES, Spooner SA, Logan JR. Evaluating the accuracy of electronic pediatric drug dosing rules. J Am
Med Inform Assoc. 2013 Jun 28.
Kirkendall ES, Kloppenborg E,
Papp J, White D, Frese C, Hacker D, Schoettker PJ, Muething S, Kotagal
U. Measuring Adverse Events and Levels of Harm in Pediatric Inpatients
with the Global Trigger Tool. Pediatrics. 2012 Nov;130(5):e1206-14.
NINJA2: Reduction of Nephrotoxic Medication-associated Acute Kidney Injury in Children. Co-investigator. Agency for Healthcare Research and Quality. 2015-2018.
Pursuing Perfection in Pediatric Therapeutics. Clinical Scientist – Informatics Expert. Agency for Healthcare Research and Quality. 2011-2016.
PHIS+: Augmenting the Pediatric Health Information System Database. Clinical Scientist – Informatics and Subject Matter Expert. Agency for Healthcare Research and Quality. 2010-2015.
Kakajan Komurov, PhD Member, Cancer Biology and Neural Tumors Program
Member, Cancer Biology and Neural Tumors Program
Komurov K, Ram PT. Patterns of human gene expression variance show strong associations with signaling network hierarchy. BMC Syst Biol. 2010 Nov 12;4:154.
Komurov K, White MA, Ram PT. Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data. PLoS Comput Biol. 2010 Aug 19;6(8).
Taube JH*, Herschkowitz JI*, Komurov K*, Zhou AY, Gupta S, Yang J, Hartwell K, Onder TT, Gupta PB, Evans KW, Hollier BG, Ram PT, Lander ES, Rosen JM, Weinberg RA, Mani SA. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc Natl Acad Sci U S A. 2010 Aug 31;107(35):15449-54. (*Co-first author)
Komurov K, Padron D, Cheng T, Roth M, Rosenblatt KP, White MA. Comprehensive mapping of the human kinome to epidermal growth factor receptor signaling. J Biol Chem. 2010 Jul 2;285(27):21134-42.
Komurov K, Gunes MH, White MA. Fine-scale dissection of functional protein network organization by statistical network analysis. PLoS One. 2009 Jun 24;4(6):e6017.
Komurov K, White M. Revealing static and dynamic modular architecture of the eukaryotic protein interaction network. Mol Syst Biol. 2007;3:110.
Alexey Porollo, PhD Member, Center for Autoimmune Genomics and Etiology
Member, Center for Autoimmune Genomics and Etiology
Member, Division of Biomedical Informatics
UC Department of Environmental Health
MSc: Mari State University, Yoshkar-Ola, Russia, 1995.
PhD: Tver State University, Tver and Mari State University, Yoshkar-Ola, Russia, 1999.
Post-doc: Children’s Hospital Medical Center, Cincinnati, OH, 2006.
Porollo A, Sesterhenn TM, Collins MS, Welge JA, Cushion MT. Comparative Genomics of Pneumocystis Species Suggests the Absence of Genes for myo-Inositol Synthesis and Reliance on Inositol Transport and Metabolism. MBio. 2014 Nov 4;5(6).
Fechter K, Porollo A. MutaCYP: Classification of missense mutations in human cytochromes P450. BMC Med Genomics. 2014 Jul 30;7(1):47.
Subramanian Vignesh K, Landero Figueroa JA, Porollo A,
Caruso JA, Deepe GS Jr. Granulocyte
macrophage-colony stimulating factor induced Zn sequestration enhances macrophage
superoxide and limits intracellular pathogen survival. Immunity. 2013 Oct
Syed K, Porollo A, Miller D, Yadav JS. Rational engineering of the fungal P450 monooxygenase
CYP5136A3 to improve its oxidizing activity toward polycyclic aromatic hydrocarbons.
Protein Eng Des Sel. 2013
Green JV, Orsborn KI, Zhang M, Tan QK, Greis KD, Porollo A, Andes DR, Long Lu J, Hostetter MK. Heparin-binding motifs and biofilm formation by Candida albicans. J Infect Dis. 2013 Nov 15;208(10):1695-704.
Ma L, Tao Y, Duran A, Llado V, Galvez A, Barger JF, Castilla
EA, Chen J, Yajima T, Porollo A, Medvedovic M, Brill LM, Plas DR, Riedl
SJ, Leitges M, Diaz-Meco MT, Richardson AD, Moscat J. Control of nutrient stress-induced metabolic
reprogramming by PKCζ in tumorigenesis. Cell.
2013 Jan 31;152(3):599-611.
Porollo A, Meller J, Joshi Y, Jaiswal V, Smulian AG, Cushion MT. Analysis of current antifungal agents and their targets within the Pneumocystis carinii genome. Curr Drug Targets. 2012 Nov;13(12):1575-85.
Duran A, Amanchy R, Linares JF, Joshi J, Abu-Baker S,
Porollo A, Hansen M, Moscat J, Diaz-Meco MT. p62
is a key regulator of nutrient sensing in the mTORC1 pathway. Mol Cell. 2011 Oct 7;44(1):134-46.
Porollo A, Meller J. Prediction-based
fingerprints of protein-protein interactions. Proteins. 2007 Feb 15;66(3):630-45.
Adamczak R, Porollo A, Meller J. Accurate prediction of solvent accessibility using neural
networks-based regression. Proteins.
2004 Sep 1;56(4):753-67.
Directed Culturing of
Pneumocystis Using Metatranscriptomics. Co-Principal Investigator. National
Institutes of Health: Heart, Lung and Blood Institute. May 2013-Feb 2018. R01HL119190-01.
Sequestration and Histoplasma. Co-Investigator. National Institute of
Allergy and Infectious Diseases. May 2013–Apr 2018. 1R01AI106269-01.
Suppression of IgE-Mediated Disease by Polyclonal Rapid Desensitization. Co-Investigator. National Institute of Allergy and Infectious Diseases. Jul 2014-Jun 2019. 1R01AI113162-01.
Alexander J. Towbin, MD Radiologist, Department of Radiology and Medical Imaging
is interested in radiology informatics; cancer imaging and abdominal imaging.
Radiologist, Department of Radiology and Medical Imaging
Neil D. Johnson Chair, Radiology Informatics
Co-Chief, Thoracoabdominal Imaging
Associate Professor, UC Department of Radiology
Radiology informatics; cancer imaging; abdominal imaging
MD: Doctor of Medicine, University of Cincinnati, Cincinnati, OH, 2002.
Internship: Pediatrics, Cincinnati Children’s Hospital Medical Center-University of Cincinnati College of Medicine, Cincinnati, OH, 2002-2003.
Residency: Diagnostic Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, 2003-2007.
Fellowship: Pediatric Radiology, Cincinnati Children’s Hospital Medical Center-University of Cincinnati College of Medicine, Cincinnati, OH, 2008.
Certification: American Board of Radiology, 2007.
Hummel T, Anyane-Yeboa A, Mo J, Towbin A, Weiss B. Response of NF1-related plexiform neurofibroma to high-dose carboplatin. Pediatr Blood Cancer. 2011 Mar;56(3):488-90.
Towbin AJ, Luo GG, Yin H, Mo JQ. Focal nodular hyperplasia in children, adolescents, and young adults. Pediatr Radiol. 2011 Mar;41(3):341-9.
Towbin AJ, Hall S, Moskovitz J, Johnson ND, Donnelly LF. Creating a comprehensive customer service program to help convey critical and acute results of radiology studies. AJR Am J Roentgenol. 2011 Jan;196(1):W48-51.
Hawkins CM, Towbin AJ. Rupture of the left mainstem bronchus following endotracheal intubation in a neonate. Pediatr Radiol. 2010 Nov 13.
Donnelly LF, Gessner KE, Dickerson JM, Koch BL, Towbin AJ, Lehkamp TW, Moskovitz J, Brody AS, Dumoulin CL, Jones BV. Quality initiatives: department scorecard: a tool to help drive imaging care delivery performance. Radiographics. 2010 Nov;30(7):2029-38.
Towbin AJ, Chaves I. Chronic granulomatous disease. Pediatr Radiol. 2010 May;40(5):657-68; quiz 792-3.
Rayburg M, Kalinyak KA, Towbin AJ, Baker PB, Joiner CH. Fatal bone marrow embolism in a child with hemoglobin SE disease. Am J Hematol. 2010 Mar;85(3):182-4.
Rayburg M, Towbin A, Yin H, Maugans T, Maurer B, Nagarajan R, Weiss B. Langerhans cell histiocytosis in a patient with stage 4 neuroblastoma receiving oral fenretinide. Pediatr Blood Cancer. 2009 Dec;53(6):1111-3.
Towbin AJ, Ying J, Fleck R. Transient hepatic attenuation differences in neonates. Pediatr Radiol. 2009 Aug;39(8):798-803.
Towbin AJ. The CT appearance of intraoral chewing gum. Pediatr Radiol. 2008 Dec;38(12):1350-2.
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.
Visit the Weirauch Lab.
Transcription factors; transcriptional regulation; functional genomics; genome analysis
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, Cincinnati Children's. 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.
Yan Xu, PhD Director of Bioinformatics Core, Neonatology & Pulmonary Biology; Perinatal Institute
research interests are the identification of gene signatures, regulatory networks and biological pathways controlling lung development, maturation and diseases. She is actively involved in the development of detailed developmental lung-map via high-throughput single cell genomics to provide useful tools and resources for the lung research community.
Director of Bioinformatics Core, Neonatology & Pulmonary Biology; Perinatal Institute
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.
Du Y, Guo M, Whitsett JA, Xu Y. 'LungGENS': a web-based tool for mapping single-cell gene expression in the developing lung. Thorax. 2015 Jun 30.
Bridges JP, Schehr A, Wang Y, Huo L, Besnard V, Ikegami M, Whitsett JA, Xu Y. Epithelial SCAP/INSIG/SREBP Signaling Regulates Multiple Biological Processes During Perinatal Lung Maturation. PLoS One. 2014 May 7;9(5):e91376.
Xu Y, Wang Y, Besnard V, Ikegami M, Wert SE, Heffner C, Murray SA, Donahue LR, Whitsett JA. Transcriptional programs controlling perinatal lung maturation. PLoS One. 2012;7(8):e37046.
Xu Y, Whitsett JA. Functional Genomics - Transcriptional Networks Controlling Lung Maturation and Surfactant Homeostasis.Hutton J (Ed). Pediatric Biomedical Informatics: Computer Applications in Pediatric Research (Translational Bioinformatics). 2012. Publisher: Springer.
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;11(1):451.
Xu Y, Saegusa C, Schehr A, Grant S, Whitsett JA, Ikegami M. C/EBPa is required for pulmonary cytoprotection during hyperoxia. American journal of physiology. 2009;297(2):L286-298.
Xu Y, Ikegami M, Wang Y, Matsuzaki Y, Whitsett JA. Gene expression and biological processes influenced by deletion of Stat3 in pulmonary type II epithelial cells. BMC Genomics. 2007;8:455.
Xu Y, Liu C, Clark JC, Whitsett JA. Functional genomic responses to cystic fibrosis transmembrane conductance regulator (CFTR) and CFTR(508) in the lung. J Biol Chem. 2006;281:11279-11291.
Wan H, Xu Y, Ikegami M, Stahlman MT, Kaestner KH, Ang SL, Whitsett JA. Foxa2 is required for transition to air breathing at birth. Proc Natl Acad Sci USA. 2004;101:14449-14454.
Xu Y, Clark JC, Aronow BJ, Dey CR, Liu C, Wooldridge JL, Whitsett JA. Transcriptional adaptation to cystic fibrosis transmembrane conductance regulator deficiency. J Biol Chem. 2003;278:7674-7682.
“Lung Map” Atlas Research Center. Co-Investigator. National Heart, Lung, and Blood Institute. Jan 2014-Jan 2019.
Transcriptional Programming of Asthma Related Pathology in Respiratory Epithelial. Co-Investigator. National Heart, Lung, and Blood Institute. Apr 2013-Mar 2018.
Airway Progenitor Cell Proliferation and Differentiation During Lung Repair. Co-Investigator. National Heart, Lung, and Blood Institute. Jan 2012-Dec 2016.
Mechanisms Underlying DICER1 Suppression of Pleuropulmonary Blastoma. Co-Investigator. St. Baldrick's Foundation. Jul 2011-Jun 2016.
Osr Transcription factors regulate embryonic lung development. Co-Investigator. National Heart, Lung, and Blood Institute. Sept 2014-Aug 2016.
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