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Seminars

Big Data Analysis in Genomic Research and Its Clinical Applications

  • 2016-11-28 (Mon.), 10:30 AM
  • Recreation Hall, 2F, Institute of Statistical Science
  • Prof. Eric Y. Chuang
  • Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University

Abstract

Big data analysis is an emerging technique in computational science. It has been widely implemented in various research fields, such as industrial research, market research, scientific research, and bioinformatics research in recent years. DNA microarray and next-generation sequencing (NGS) are two major forms of genomic technologies that generate big data in biomedical science. Both DNA microarray and NGS technologies are able to precisely detect the sequences of specific DNA molecules and then generate huge amount of genomic/transcriptomic data in an efficient manner. For example, NGS technology generates DNA sequence data of three billion nucleotide bases from a single tissue specimen in one experiment. However, dealing with such huge amount of genomic data renders enormous difficulties and challenges for biologists and physicians. In the past ten years, we have successfully developed a number of databases (e.g., miRSystem, Carkinos) and analytical tools (e.g., NTUMAPs, BioCloud) that could be used to analyze genomic data and to further interpret biologically meaningful implications from the genomic data. We have also used DNA microarray and NGS technologies to investigate the molecular portraits of various human diseases and endemic species in Taiwan.. Currently, we are collaborating with YongLin Healthcare Foundation for a research project named “Chinese Breast Cancer Genome Database” that is aimed to perform exome sequencing experiments of one hundred pairs of breast tumor tissues and adjacent normal breast tissues and to identify Chinese breast cancer-specific gene mutations. In this presentation, I will talk about our experience in genomic big data analysis and its clinical impact. The analysis of genomic big data into a finding of molecular biomarkers for human diseases is believed to be a fundamental step that paves the way for the era of precision medicine. Big data analysis in genomics thus requires a high level of computational expertise and a thorough understanding of molecular biology.

Update:2024-12-03 19:32
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