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BioMed Research International
Volume 2013 (2013), Article ID 848952, 7 pages
Integration of Data from Omic Studies with the Literature-Based Discovery towards Identification of Novel Treatments for Neovascularization in Diabetic Retinopathy
1Institute of Medical Genetics, Department of Obstetrics and Gynecology, University Medical Centre Ljubljana, 3 Šlajmerjeva Street, 1000 Ljubljana, Slovenia
2Institute of Biostatistics and Medical Informatics, Faculty of Medicine, 1000 Ljubljana, Slovenia
3National Library of Medicine, NIH, Bethesda, MD 20894, USA
Received 16 July 2013; Accepted 13 August 2013
Academic Editor: Goran Petrovski
Copyright © 2013 Ales Maver et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- E. Y. Chew, W. T. Ambrosius, M. D. Davis et al., “Effects of medical therapies on retinopathy progression in type 2 diabetes,” The New England Journal of Medicine, vol. 363, no. 3, pp. 233–244, 2010.
- J. W. Y. Yau, S. L. Rogers, R. Kawasaki et al., “Global prevalence and major risk factors of diabetic retinopathy,” Diabetes Care, vol. 35, no. 3, pp. 556–564, 2012.
- I. Cilenšek, S. Mankoč, M. G. Petrovič, and D. Petrovič, “GSTT1 null genotype is a risk factor for diabetic retinopathy in Caucasians with type 2 diabetes, whereas GSTM1 null genotype might confer protection against retinopathy,” Disease Markers, vol. 32, no. 2, pp. 93–99, 2012.
- M. G. Petrovič, I. Cilenšek, and D. Petrovič, “Manganese superoxide dismutase gene polymorphism (V16A) is associated with diabetic retinopathy in Slovene (Caucasians) type 2 diabetes patients,” Disease Markers, vol. 24, no. 1, pp. 59–64, 2008.
- A. R. Bhavsar, “Diabetic retinopathy: the latest in current management,” Retina, vol. 26, supplement 6, pp. S71–S79, 2006.
- T. N. Crawford, D. V. Alfaro III, J. B. Kerrison, and E. P. Jablon, “Diabetic retinopathy and angiogenesis,” Current Diabetes Reviews, vol. 5, no. 1, pp. 8–13, 2009.
- G. Javey, S. G. Schwartz, and H. W. Flynn Jr., “Emerging pharmacotherapies for diabetic macular edema,” Experimental Diabetes Research, vol. 2012, Article ID 548732, 12 pages, 2012.
- C. G. Bell, A. E. Teschendorff, V. K. Rakyan, A. P. Maxwell, S. Beck, and D. A. Savage, “Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus,” BMC Medical Genomics, vol. 3, article 33, 2010.
- M. A. Grassi, A. Tikhomirov, S. Ramalingam, J. E. Below, N. J. Cox, and D. L. Nicolae, “Genome-wide meta-analysis for severe diabetic retinopathy,” Human Molecular Genetics, vol. 20, no. 12, pp. 2472–2481, 2011.
- H. D. VanGuilder, G. V. Bixler, L. Kutzler et al., “Multi-modal proteomic analysis of retinal protein expression alterations in a rat model of diabetic retinopathy,” PLoS ONE, vol. 6, no. 1, Article ID e16271, 2011.
- W. M. Freeman, G. V. Bixler, R. M. Brucklacher et al., “Transcriptomic comparison of the retina in two mouse models of diabetes,” Journal of Ocular Biology, Diseases, and Informatics, vol. 2, no. 4, pp. 202–213, 2009.
- D. B. Allison, X. Cui, G. P. Page, and M. Sabripour, “Microarray data analysis: from disarray to consolidation and consensus,” Nature Reviews Genetics, vol. 7, no. 1, pp. 55–65, 2006.
- D. R. Swanson, “Fish oil, Raynaud's syndrome, and undiscovered public knowledge,” Perspectives in Biology and Medicine, vol. 30, no. 1, pp. 7–18, 1986.
- D. Hristovski, T. Rindflesch, and B. Peterlin, “Using literature-based discovery to identify novel therapeutic approaches,” Cardiovascular & Hematological Agents in Medicinal Chemistry, vol. 11, pp. 14–24, 2013.
- D. Hristovski, S. Dżeroski, B. Peterlin, and A. Rożić-Hristovski, “Supporting discovery in medicine by association rule mining of bibliographic databases,” Studies in Health Technologies and Informatics, vol. 84, pp. 1344–1348, 2001.
- D. Hristovski, B. Peterlin, J. A. Mitchell, and S. M. Humphrey, “Using literature-based discovery to identify disease candidate genes,” International Journal of Medical Informatics, vol. 74, no. 2–4, pp. 289–298, 2005.
- D. Hristovski, B. Peterlin, J. A. Mitchell, and S. M. Humphrey, “Improving literature based discovery support by genetic knowledge integration,” Studies in Health Technology and Informatics, vol. 95, pp. 68–73, 2003.
- D. Hristovski, A. Kastrin, B. Peterlin, and T. C. Rindflesch, “Combining semantic relations and DNA microarray data for novel hypotheses generation,” in Linking Literature Information and Knowledge for Biologie, vol. 6004 of Lecture Notes in Computer Science, pp. 53–61, Springer, Berlin, Germany, 2010.
- D. Hristovski, A. Kastrin, B. Peterlin, and T. C. Rindflesch, “Semantic relations for interpreting DNA microarray data,” AMIA Annual Symposium Proceedings/AMIA Symposium AMIA Symposium, vol. 2009, pp. 255–259, 2009.
- R. C. Gentleman, V. J. Carey, D. M. Bates et al., “Bioconductor: open software development for computational biology and bioinformatics,” Genome Biology, vol. 5, no. 10, p. R80, 2004.
- T. Barrett and R. Edgar, “Gene expression omnibus: microarray data storage, submission, retrieval, and analysis,” Methods in Enzymology, vol. 411, pp. 352–369, 2006.
- F. Hong, R. Breitling, C. W. McEntee, B. S. Wittner, J. L. Nemhauser, and J. Chory, “RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis,” Bioinformatics, vol. 22, no. 22, pp. 2825–2827, 2006.
- M. Ashburner, C. A. Ball, J. A. Blake et al., “Gene ontology: tool for the unification of biology,” Nature Genetics, vol. 25, no. 1, pp. 25–29, 2000.
- B. T. Sherman, D. W. Huang, Q. Tan et al., “DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis,” BMC Bioinformatics, vol. 8, article 426, 2007.
- A. Reiner, D. Yekutieli, and Y. Benjamini, “Identifying differentially expressed genes using false discovery rate controlling procedures,” Bioinformatics, vol. 19, no. 3, pp. 368–375, 2003.
- D. Hristovski, 2009, SemBT, http://sembt.mf.uni-lj.si/.
- T. C. Rindflesch and M. Fiszman, “The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text,” Journal of Biomedical Informatics, vol. 36, no. 6, pp. 462–477, 2003.
- M. Masseroli, H. Kilicoglu, F. Lang, and T. C. Rindflesch, “Argument-predicate distance as a filter for enhancing precision in extracting predications on the genetic etiology of disease,” BMC Bioinformatics, vol. 7, article 291, 2006.
- C. B. Ahlers, M. Fiszman, D. Demner-Fushman, et al., “Extracting semantic predications from Medline citations for pharmacogenomics,” in Proceedings of the Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, vol. 2007, pp. 209–220, Lister Hill National Center for Biomedical Communications, Bethesda, Md, USA, 2007.
- S. J. Kirwin, S. T. Kanaly, C. R. Hansen, B. J. Cairns, M. Ren, and J. L. Edelman, “Retinal gene expression and visually evoked behavior in diabetic long evans rats,” Investigative Ophthalmology & Visual Science, vol. 52, no. 10, pp. 7654–7663, 2011.