CAREER: Dissecting the Mechanisms of Genetic Control of Biological Systems via High-Dimensional Sparse Graphical Models

自从各种生物（包括人类和其他模式生物）的基因组测序项目完成以来，计算基因组学、系统生物学和遗传学研究的基本目标一直是全面了解基因组编码的指令集如何在细胞系统和生物体中执行。高通量技术和下一代测序技术的最新进展使研究人员能够收集大量基因组和细胞系统的其他方面的数据。这些数据集是了解生物系统遗传控制详细机制的关键，并进一步加深我们对细胞生物学的了解，具有广泛应用的潜力。该项目将开发基于高维稀疏图形模型的统计机器学习方法，用于基因组数据集的综合分析。由于图形模型为表示所观察到的基因组数据背后的未知生物过程的复杂结构提供了强大的工具，因此本项目中开发的计算方法将能够从基因组规模的数据集中提取有关基因调控系统的遗传控制的丰富信息。该项目还将包括通过指导研究生并将研究成果纳入课程来培养下一代计算生物学家。该项目将涉及计算科学家和生物学家之间的合作，参与面向高中生的拓展计划，向他们展示结合生物和计算机科学的另一种职业道路。此外，该项目将有助于提高妇女对科学和工程的参与。

Since the completion of genome sequencing projects for various organisms including human and other model organisms, the fundamental goal of research in computational genomics, systems biology, and genetics has been to gain a complete understanding of how the instruction sets encoded in genomes get executed within a cell system and organism. The recent advances in the high-throughput technology and next-generation sequencing technology have allowed the researchers to collect a large amount of data for the genomes and various other aspects of a cell system. Such datasets hold the key to understanding the detailed mechanisms of the genetic control of a biological system and further deepening our knowledge of cell biology with the potential for broad application. This project will develop statistical machine learning methods based on high-dimensional sparse graphical models for integrative analysis of genomic datasets. As graphical models provide a powerful tool for representing the complex structure of the unknown biological processes that underlie the observed genomic data, the computational methods to be developed in this project will be able to extract rich information on the genetic control of gene regulation systems from genome-scale datasets.This project will also include training the next-generation computational biologists by supervising graduate students and incorporating the research results into the curriculum. The project will involve collaboration between computational scientists and biologists to participate in outreach programs for high-school students to present them an alternative career path that combines biological and computer sciences. In addition, the project will contribute to increasing womens participation in science and engineering.