Bruce J. Aronow, PhD
Co-director, Computational Medicine Center
focuses his research on unraveling the role and mechanism by which the functional capabilities of the human genome shape human health and the body’s ability to adapt to stressful challenges. With the co-leadership of Anil Jegga, DVM, his lab is using a variety of available data on structural and functional genomics and biological systems to form models of how biological systems assemble, adapt and become impaired in disease. Visit the Aronow/Jegga Lab.
513-636-0263
bruce.aronow@cchmc.org
Bruce J. Aronow, PhD
Co-director, Computational Medicine Center
Academic Information
Professor, UC Department of Pediatrics
Show All
Specialties
Biography
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.
Education and Training
BS: Chemistry, Stanford University, Stanford, CA, 1976
PhD: Biochemistry, University of Kentucky, Lexington, KY, 1986
Research Fellowship: Division of Basic Science Research, Cincinnati Children's Research Foundation, Cincinnati, OH, 1986-1989
Publications
View PubMed Publications 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.
Grants
CTSA - Enabling Tehnologies: Center for Translational & Molecular Disease. National Institutes of Health. Apr 2009 - Mar 2014.
|
Anil Goud Jegga, DVM, MRes
is a medically oriented computational biologist. His work with Bruce Aronow, PhD, uses a variety of bioinformatics approaches to explore gene regulatory networks and the interaction between genotype and phenotype. He has extensive experience in transcription factor and micro-RNA based gene regulatory mechanisms, gene polymorphism functional analysis, candidate disease gene identification and prioritization. Visit the Aronow/Jegga Lab.
513-636-0261
anil.jegga@cchmc.org
Anil Goud Jegga, DVM, MRes
Academic Information
Assistant Professor, UC Department of Pediatrics
Show All
Specialties
Biography
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.
Education and Training
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.
Publications
View PubMed Publications
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.
513-636-1302
michal.kouril@cchmc.org
Michal Kouril, PhD
Director, Research IT Services
Academic Information
UC Department of Pediatrics
Show All
Education and Training
PhD: Computer Science, University of Cincinnati, Cincinnati, OH, 2006.
|
Long (Jason) Lu, PhD
works in bioinformatics and systems biology. He focuses on using quantitative approaches from disciplines such as computer science and applied mathematics to address fundamental questions in molecular biology. In particular, he is interested in deciphering the human genetic blueprint, modeling complex biological systems (such as biomolecular networks and pathways), and facilitating drug discovery and development. Visit the Lu Lab.
513-636-8720
long.lu@cchmc.org
Long (Jason) Lu, PhD
Academic Information
Assistant Professor, UC Department of Pediatrics
Show All
Specialties
Education and Training
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.
Publications
View PubMed Publications
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.
Grants
The Molecular Basis for High Density Lipoprotein Heterogeneity. Co-Investigator. National Institutes of Health. Jul 2010 - Jun 2012.
Probing the Robustness of a Developmental System. Co-Investigator. National Science Foundation. May 2009 - May 2013.
|
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.
513-636-7977
jun.ma@cchmc.org
Jun Ma, PhD
Academic Information
Professor, UC Department of Pediatrics
Show All
Specialties
Molecular mechanisms of gene regulation and embryonic development
Education and Training
PhD: Harvard University, Cambridge, MA, 1983-1988 (degree awarded 1990).
BS: Peking University, 1978-1982.
Publications
View PubMed Publications
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.
Grants
Probing the Robustness of a Developmental System. National Science Foundation. May 2009 - Apr 2013. #IOS-0843424.
|
Keith Marsolo, PhD
Director, Software Development and Data Warehouse
leads the development of the i2b2 research data warehouse at Cincinnati Children’s, which incorporates data from the Epic electronic health record and many other database systems used by hospital clinicians and researchers. He is head of the software development group, which focuses on developing systems for electronic data capture and reporting / creating collaborative websites for clients within the research foundation.
513-803-0333
keith.marsolo@cchmc.org
Keith Marsolo, PhD
Director, Software Development and Data Warehouse
Academic Information
Assistant Professor, UC Department of Pediatrics
Show All
Biography
Keith Marsolo, PhD, is leading the development of a research data warehouse at Cincinnati Children's. Based on a framework known as i2b2, the warehouse enables users to perform a hospital-wide search of a de-identified data set to determine the existence of a patient cohort. The warehouse incorporates data from the hospital's new Epic electronic health record as well as from many other database systems used by hospital clinicians and researchers. To protect the privacy of patients, Dr. Marsolo and his group also ensure that the appropriate regulatory and security safeguards are in place. For more information, visit the i2b2 Research Data Warehouse web site.
Education and Training
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.
Publications
Wen H, Marsolo KA, Bennett EE, Kutten KS, Lewis RP, Lipps DB, Epstein ND, Plehn JF, 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
advances the science of natural language processing and understanding in biomedical settings. Along with a growing list of collaborators, his lab has developed neuro-cognitive algorithms that enable computers to understand concepts and semantic relationships within clinical text. Pestian also directs the Computational Medicine Center, established in 2003 by a $28 million grant from Ohio's Third Frontier Project. Visit the Pestian Lab.
513-636-1627
john.pestian@cchmc.org
John P. Pestian, PhD, MBA
Director, Computational Medicine Center
Academic Information
Associate Professor, UC Department of Pediatrics
Show All
Specialties
Biography
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
Education and Training
BS: St. Francis College, Lorreto, PA, 1981.
MA: University of Steubenville, Steubenville, OH, 1987.
PhD: Virginia Commonwealth University, Richmond, VA, 1994.
Publications
View PubMed Publications
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.
|
Imre Solti MD, PhD
specializes in clinical informatics and health services research informatics. The mission of his research lab is to develop informatics algorithms and tools to extract all relevant information from the Electronic Health Record, including information buried in narrative text, and to utilize the extracted information in computerized clinical care, patient safety and outcome improvement systems. Visit the Solti Lab..
513-636-2477
imre.solti@cchmc.org
Imre Solti MD, PhD
Academic Information
Assistant Professor, UC Department of Pediatrics
Show All
Specialties
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
Education and Training
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.
Publications
View PubMed Publications
Uzuner O, Solti I, Xia F, Cadag E. Community annotation experiment for ground truth generation for the i2b2 medication challenge. J Am Med Inform Assoc. 2010 Sep-Oct;17(5):519-23.
Uzuner O, Solti I, Cadag E. Extracting medication information from clinical text. J Am Med Inform Assoc. 2010 Sep-Oct;17(5):514-8.
Grants
Increasing Clinical Trial Enrollment: A Semi-Automated Patient Centered Approach. Principal Investigator. National Institutes of Health. Sep 2010 - Sep 2013.
|
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.
513-636-2290
andrew.spooner@cchmc.org
Stephen A. Spooner, MD, MS, FAAP
Chief Medical Information Officer, Biomedical Informatics
Academic Information
Associate Professor, UC Department of Pediatrics
|
Michael Wagner, PhD
Faculty Liaison, Biomedical Informatics Core
works on applications of machine learning techniques to bioinformatics problems such as protein structure prediction, disease classification and protein identification. His lab is investigating machine-learning-based scoring algorithms for peptide mass fingerprinting to better understand how to optimally mine mass spectrometry data and make high-confidence predictions of protein identities. Visit the Wagner Lab.
513-636-2935
michael.wagner@cchmc.org
Michael Wagner, PhD
Faculty Liaison, Biomedical Informatics Core
Academic Information
Associate Professor, UC Department of Pediatrics
Show All
Specialties
Biography
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.
Education and Training
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.
Publications
View PubMed Publications
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.
|
