Heterogeneous data analysis for annotation of microRNAs and novel genome assembly

Abstract

This thesis is the collection of four published papers demonstrating annotation of genes and microRNAs with the aid of bioinformatics, in particular using heterogeneous data integration. Gene annotation is the process of detecting the structure and biological function of the raw DNA sequences; while microRNA annotation is mainly about identifying its regulatory targets since microRNA modify gene expression by binding to their targets. In order to ef__ciently and accurately annotate microRNAs and coding region of a novel genome, we developed several complex work__ows which integrate the current most relevant data sources and tools. The essence of integration is not to produce even more data but to increase the sensitivity and/or speci__city of the algorithm and system. Currently, in life sciences high-throughput experiments, multiple platforms, and multiple model or non-model species are very commonly applied in different studies. In line with this trend heterogeneous data integration is no doubt an important strategy for the analysis of biological data.