This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Molecular prediction and personalization is the future direction of medicine. With the rapid development of microarray technology, it has become increasingly promising to identify novel biomarkers for the diagnosis and prognosis of human disease. However, current molecular classifiers for the prediction of clinical outcomes are not optimized. The long list of molecular markers can be reduced and the prediction accuracy can be further increased by using appropriate data mining algorithms. There exists an urgent need for a general feature selection scheme for identifying potential diagnostic and prognostic markers from high-throughput data. Furthermore, the development of a suitable methodology for elucidating the complex molecular interrelations in disease progression is critical. The extracted biomarker patterns can be used to predict clinical outcome for individual patients. The goal of this proposal is to test the hypothesis that a systems biology framework combining bioinformatic, genomic, proteomic, and clinical approaches and information enables the construction of clinically important molecular prediction models. Specifically, we will (1) develop a general feature selection scheme to identify novel biomarkers from microarray data; and (2) optimize a network model to construct molecular prediction models for individualized clinical decision-making. The network model extracts molecular expression patterns to predict clinical outcome for individual patients. The long-term goals are twofold: 1) to develop a novel model framework for identifying important biomarkers that contain valuable information concerning the molecular mechanisms and therapeutic targets underlying disease, and 2) to make accurate predictions in individualized diagnosis, prognosis, and therapeutics. We anticipate that the proposed computational framework will fill gaps in current bioinformatics research. The proposed informatics framework and the identified molecular classifiers may have an important impact in bioinformatics and influence clinical care in general. We will disseminate the software system by providing web-based public access.

National Institute of Health (NIH)
National Center for Research Resources (NCRR)
Exploratory Grants (P20)
Project #
Application #
Study Section
Special Emphasis Panel (ZRR1-RI-8 (01))
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
West Virginia University
Internal Medicine/Medicine
Schools of Medicine
United States
Zip Code
Brooks, Celine; Snoberger, Aaron; Belcastro, Marycharmain et al. (2018) Archaeal Unfoldase Counteracts Protein Misfolding Retinopathy in Mice. J Neurosci 38:7248-7254
Grisez, Brian T; Ray, Justin J; Bostian, Phillip A et al. (2018) Highly metastatic K7M2 cell line: A novel murine model capable of in vivo imaging via luciferase vector transfection. J Orthop Res :
Nichols, Cody E; Shepherd, Danielle L; Hathaway, Quincy A et al. (2018) Reactive oxygen species damage drives cardiac and mitochondrial dysfunction following acute nano-titanium dioxide inhalation exposure. Nanotoxicology 12:32-48
Shumar, Stephanie A; Kerr, Evan W; Geldenhuys, Werner J et al. (2018) Nudt19 is a renal CoA diphosphohydrolase with biochemical and regulatory properties that are distinct from the hepatic Nudt7 isoform. J Biol Chem 293:4134-4148
Bedenbaugh, M N; O'Connell, R C; Lopez, J A et al. (2018) Kisspeptin, gonadotrophin-releasing hormone and oestrogen receptor ? colocalise with neuronal nitric oxide synthase neurones in prepubertal female sheep. J Neuroendocrinol 30:
Rodgers, H M; Huffman, V J; Voronina, V A et al. (2018) The role of the Rx homeobox gene in retinal progenitor proliferation and cell fate specification. Mech Dev 151:18-29
Deng, Wentao; McLaughlin, Sarah L; Klinke, David J (2017) Quantifying spontaneous metastasis in a syngeneic mouse melanoma model using real time PCR. Analyst 142:2945-2953
Alway, Stephen E; McCrory, Jean L; Kearcher, Kalen et al. (2017) Resveratrol Enhances Exercise-Induced Cellular and Functional Adaptations of Skeletal Muscle in Older Men and Women. J Gerontol A Biol Sci Med Sci 72:1595-1606
Alway, Stephen E; Mohamed, Junaith S; Myers, Matthew J (2017) Mitochondria Initiate and Regulate Sarcopenia. Exerc Sport Sci Rev 45:58-69
Haramizu, Satoshi; Asano, Shinichi; Butler, David C et al. (2017) Dietary resveratrol confers apoptotic resistance to oxidative stress in myoblasts. J Nutr Biochem 50:103-115

Showing the most recent 10 out of 306 publications