19-BBSRC-NSF/BIO: Inference of isoform-level regulatory infrastructures with studies in steroid-producing cell

细胞是提供维持生物体生命所需的所有功能的基本单位。细胞功能由蛋白质、基因产物和从基因产生蛋白质的过程（即，基因表达）由复杂的调节系统介导。关于基因调控的机制仍有许多未知之处。给定细胞中的所有基因，它们之间的调控关系可以用一个网络来表示，称为基因调控网络。从实验和计算上重建这些网络一直是一个长期的挑战。一个基因可以表达多种亚型（mRNA分子），从而产生多种不同的蛋白质，这使得潜在的基因调控网络更加复杂。该项目旨在从大规模测序数据中计算重建异构体水平的精确调控网络。该项目将首先开发有效的方法来识别表达的异构体并确定其表达丰度，然后开发一种改进当前状态的网络重建方法。新的计算方法将被验证并应用于免疫学领域-研究类固醇产生细胞的细胞机制。该项目将有助于计算机科学和生物学。公式化的计算问题考虑了生物学中的一个重要问题（推断基因表达的调控机制），公式化的计算任务给计算机科学和数学带来了新的挑战。该项目将提供一个工具包来研究癌症中免疫细胞介导的类固醇合成途径，并揭示肿瘤浸润免疫细胞中类固醇生物合成的基本原理。这项研究可以与教育活动和推广活动相结合，例如关于计算生物学算法主题的课程。该项目产生的软件和数据将方便公众使用。

Cells are the fundamental units that provide all functions needed to sustain life in living organisms. Cellular functions are carried out by proteins, products of genes and the process of producing proteins from genes (i.e., gene expression) is mediated by a complex regulation system. Much remains unknown about the mechanism of gene regulation. Given all genes in a cell, the regulatory relationships between them can be represented by a network, called gene regulatory network. It has been a long-standing challenge to reconstruct these networks experimentally and computationally. A gene can express multiple isoforms (mRNA molecules), and hence produce multiple different proteins, which makes the underlying gene regulatory network more complicated. This project aims to computationally reconstruct accurate regulatory networks at the isoform-level from large-scale sequencing data. The project will first develop efficient approaches to identify the expressed isoforms and to determine their expression abundances, and then develop a network-reconstruction method which improves over the current status. The new computational methods will be validated and applied to the field of immunology--to study cellular mechanisms in steroid-producing cells. The project will contribute to both computer science and biology. The computational problems formulated consider an important problem in biology (infer the regulatory mechanisms of gene expression), and the formulated computational tasks bring new challenges to computer science and mathematics. The project will provide a toolkit to study the immune cell-mediated steroidogenesis pathway in cancer and reveal basic principles of steroid biosynthesis in tumour-infiltrating immune cells. The research can be integrated with educational activities and outreach, such as courses on topics of algorithms in computational biology. The software and data produced in this project will be made easily accessible to the public.