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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: Development of Integrative Bioinformatics Approaches for Robust Biological Knowledge Discovery using Next-generation Sequencing Data
Committee:
Dr. M.D. Wang, Advisor
Dr. Inan, Chair
Dr. QiuButera
Abstract: The objective of the proposed research is to investigate, develop, and validate robust bioinformatics approaches for extracting, discovering, and integrating molecular knowledge using next-generation sequencing data. RNA sequencing, or RNA-seq for short, is a major branch of the next-generation sequencing technology. To carry out this objective, we will first investigate the impact of bioinformatics pipeline components on gene expression estimation and downstream analysis using RNA-seq data. Through such the investigation, we will identify variations in downstream expression estimation and prediction performance induced by pipeline components. To ameliorate such the variations or to remedy poor-performing pipelines, we will implement filtering-based approaches so as to avoid skeptical information propagates through the pipeline as well as to implement a novel normalization method that can mitigate biases and improve the robustness of the RNA-seq expression analysis pipeline. Lastly, we aim to address the curse of dimensionality and to improve the statistical power by developing a novel batch effect correction method so that similar data from multiple sources can be merged as well as developing prediction models that can use multi-modal data as the input. With these novel techniques, we expect to achieve improved biological knowledge discovery and clinical endpoint prediction.
