Decoding heterogeneous big data in an integrative way

摘要: Biotechnologies in post-genomic era, especially those that generate data highthroughput, bring opportunities and challenges are never faced before. And one of them is how to decode big heterogeneous for clues useful biological questions. With the exponential growth a variety data, comes with more applications systematic approaches investigate questions an integrative way. Systematic inherently require integration information, which urgently calling lot efforts. In this thesis, effort mainly devoted development methods tools help integrate information. Chapter 2, we employed heuristic strategy summarize/integrate genes essential determination mouse retinal cells format network. These networks experimental evidence could be rediscovered analysis high-throughput set thus would leverage data. 3, described EnRICH, tool developed qualitatively intra-organism We also introduced EnRICH applied construction composite network from different sources, demonstrated used successfully prioritize disease genes. Following work 3 (intra-organism information integration), 4 stepped method can deal inter-organism integration. The proposed able match one-to-one fashion between any two genomes. summary, thesis contributes by its on intraand