We propose to develop and implement a Knowledge Base and Coordination Center for the Consortium of Cross Organ Mechanism-Associated Phenotypes for Genetic Analyses of Heart, Lung, Blood, and Sleep Diseases (MAPGen). Our team possesses strong expertise in bioinformatics, statistics, computer science, as well as clinical and biological expertise in heart, lung, and blood diseases. We propose three major functions of the center: (1) Develop a knowledge base on interconnections among diseases. We will systematically identify, integrate, and analyze the vast amount of public data (e.g. NCBI GEO, SRA, dbGap, and published papers) to comprehensively describe the shared molecular mechanisms among diseases. We will establish a multi-dimensional disease connectivity map that can be interactively accessed via web- interface. Using this knowledge base, we will design computational approaches to identify biomarkers that can be used to predict more than one disease, to regroup diseases based on the underlying molecular mechanisms, to design novel approaches to predict disease progression, and to identify novel drug usages. (2) Develop a bioinformatics infrastructure for the MAPGen consortium. We will be responsible for the quality control of the data generated by Consortium;we will perform integrative analysis of data generated by different RCs as well those from public domains, in order to gain deep insights and fundamental understandings of the shared molecular mechanisms among the HLBS diseases. We will use the knowledge base developed in Aim 1 to further establish the connections between the HLBS and other diseases. We will work closely with the medical co-investigators at USC as well as all RC teams to develop and validate biological hypotheses. (3) We will establish an Administrative Center to coordinate activities across RCs, including coordination of manuscript and other document preparation;coordination of the activities of all Committees;overall study coordination and quality control;and administering the distribution of additional funds in years 3 and 4.
We aim to synergize the effort across all RCs to achieve the goal of understanding the genetic mechanisms responsible for the interconnections among cross-organ diseases.
The proposed projects will facilitate the identification and characterization of common pathobiologic traits and mechanisms cross organ systems, and provide a basis for the rational, mechanism-based development of new diagnostic, prognostic and therapeutic strategies for heart, lung, blood and sleep disorders.
|Li, Wenyuan; Kang, Shuli; Liu, Chun-Chi et al. (2014) High-resolution functional annotation of human transcriptome: predicting isoform functions by a novel multiple instance-based label propagation method. Nucleic Acids Res 42:e39|
|Blair, David R; Wang, Kanix; Nestorov, Svetlozar et al. (2014) Quantifying the impact and extent of undocumented biomedical synonymy. PLoS Comput Biol 10:e1003799|
|Li, Wenyuan; Dai, Chao; Kang, Shuli et al. (2014) Integrative analysis of many RNA-seq datasets to study alternative splicing. Methods 67:313-24|
|Liu, Chun-Chi; Tseng, Yu-Ting; Li, Wenyuan et al. (2014) DiseaseConnect: a comprehensive web server for mechanism-based disease-disease connections. Nucleic Acids Res 42:W137-46|
|Zhang, Shihua; Zhou, Xianghong Jasmine (2014) Matrix factorization methods for integrative cancer genomics. Methods Mol Biol 1176:229-42|
|Rzhetsky, Andrey; Bagley, Steven C; Wang, Kanix et al. (2014) Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability. PLoS Comput Biol 10:e1003518|
|Negoda, Alexander; Kim, Kwang-Jin; Crandall, Edward D et al. (2013) Polystyrene nanoparticle exposure induces ion-selective pores in lipid bilayers. Biochim Biophys Acta 1828:2215-22|
|Chen, Quan; Sun, Fengzhu (2013) A unified approach for allele frequency estimation, SNP detection and association studies based on pooled sequencing data using EM algorithms. BMC Genomics 14 Suppl 1:S1|
|Blair, David R; Lyttle, Christopher S; Mortensen, Jonathan M et al. (2013) A nondegenerate code of deleterious variants in Mendelian loci contributes to complex disease risk. Cell 155:70-80|