title: Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms.
abstract: Advances 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.
authors.forename: Jack Y
authors.initials: JY
authors.lastname: Yang
authors.forename: A
authors.initials: A
authors.lastname: Dunker
authors.forename: Jun S
authors.initials: JS
authors.lastname: Liu
authors.forename: Xiang
authors.initials: X
authors.lastname: Qin
authors.forename: Hamid R
authors.initials: HR
authors.lastname: Arabnia
authors.forename: William
authors.initials: W
authors.lastname: Yang
authors.forename: Andrzej
authors.initials: A
authors.lastname: Niemierko
authors.forename: Zhongxue
authors.initials: Z
authors.lastname: Chen
authors.forename: Zuojie
authors.initials: Z
authors.lastname: Luo
authors.forename: Liangjiang
authors.initials: L
authors.lastname: Wang
authors.forename: Yunlong
authors.initials: Y
authors.lastname: Liu
authors.forename: Dong
authors.initials: D
authors.lastname: Xu
authors.forename: Youping
authors.initials: Y
authors.lastname: Deng
authors.forename: Weida
authors.initials: W
authors.lastname: Tong
authors.forename: Mary
authors.initials: M
authors.lastname: Yang
mesh_terms: D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human; D023281:Genomics; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000473:pathology*; D010641:Phenotype; D059467:Transcriptome; D057170:Translational Research, Biomedical