Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms

dc.contributor.authorYang, Jack Y.
dc.contributor.authorDunker, A. Keith
dc.contributor.authorLiu, Jun S.
dc.contributor.authorQin, Xiang
dc.contributor.authorArabnia, Hamid R.
dc.contributor.authorYang, William
dc.contributor.authorNiemierko, Andrzej
dc.contributor.authorChen, Zhongxue
dc.contributor.authorLuo, Zuojie
dc.contributor.authorWang, Liangjiang
dc.contributor.authorLiu, Yunlong
dc.contributor.authorXu, Dong
dc.contributor.authorDeng, Youping
dc.contributor.authorTong, Weida
dc.contributor.authorYang, Mary Qu
dc.contributor.departmentDepartment of Biochemistry and Molecular Biology, IU School of Medicineen_US
dc.date.accessioned2016-05-25T20:04:09Z
dc.date.available2016-05-25T20:04:09Z
dc.date.issued2014
dc.description.abstractAdvances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective approaches at higher systems level. In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from which genes and proteins actively interact to lead to cellular behaviours and physiological phenotypes. As biological interactions mediate many biological processes that are essential for cellular function or disease development, it is important to systematically identify genomic information including genetic mutations from GWAS (genome-wide association study), differentially expressed genes, bidirectional promoters, intrinsic disordered proteins (IDP) and protein interactions to gain deep insights into the underlying mechanisms of gene regulations and networks. Furthermore, bidirectional promoters can co-regulate many biological pathways, where the roles of bidirectional promoters can be studied systematically for identifying co-regulating genes at interactive network level. Combining information from different but related studies can ultimately help revealing the landscape of molecular mechanisms underlying complex diseases such as cancer.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationYang, J. Y., Dunker, A. K., Liu, J. S., Qin, X., Arabnia, H. R., Yang, W., … Yang, M. Q. (2014). Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms. BMC Bioinformatics, 15(Suppl 17), I1. http://doi.org/10.1186/1471-2105-15-S17-I1en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttps://hdl.handle.net/1805/9664
dc.language.isoen_USen_US
dc.publisherSpringer (Biomed Central Ltd.)en_US
dc.relation.isversionof10.1186/1471-2105-15-S17-I1en_US
dc.relation.journalBMC bioinformaticsen_US
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMCen_US
dc.subjectComputational Biologyen_US
dc.subjectmethodsen_US
dc.subjectGenome, Humanen_US
dc.subjectNeoplasmsen_US
dc.subjectgeneticsen_US
dc.subjectpathologyen_US
dc.subjectTranscriptomeen_US
dc.subjectTranslational Medical Researchen_US
dc.titleAdvances in translational bioinformatics facilitate revealing the landscape of complex disease mechanismsen_US
dc.typeConference proceedingsen_US
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