Institute of Information Science, Academia Sinica

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Digging for Meaning in the Big Data of Human Biology

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Digging for Meaning in the Big Data of Human Biology

  • LecturerProf. Tzong-Yi Lee (Department of Computer Science & Engineering, Yuan Ze University)
    Host: Ting-Yi Sung
  • Time2016-06-22 (Wed.) 14:00 ~ 16:00
  • LocationAuditorium 106 at IIS new Building
Abstract

With the advent of high-throughput technologies, molecular biology is experiencing a surge in both growth and scope. As the amount of experimental data increases, so is the demand for the development of ways to analyze these results. For example, the next-generation sequencing (NGS) technology has generated various sequencing data. Mass spectrometry (MS)-based experiments are also widely applied in proteomics studies. Rapidly advancing technologies have offered us the opportunities to examine the genome, transcriptome and proteome in comprehensive ways. Yet, extracting meaningful information from this vast sea of data and approaching biological problems from a systems biology perspective have become the Holy Grail in bioinformatics. Hence, the trend in bioinformatics toward the development of genome and proteome-wide assays necessitates an increased reliance upon bioinformatics and systems biology to organize and interpret the large-scale data sets from biological experiments. In recent years, my research interests were on new ideas, original research findings, and practical applications that intend to answer biological questions through high-throughput technologies and to gain insights into the molecular machinery of the cell. In selecting research areas to focus on, I am drawn to research problems in which I can solve fundamental problems in biology and human disease while also pushing the state of the art in data mining and machine learning. Furthermore, I have collaborated with scientists in domains other than bioinformatics to extend the community discovery algorithms for broader applications. The longer-term goals are focused on the integration of bioinformatics and big data analytics to address emerging biological and clinical questions for precision medicine.