Discovering gene regulatory networks through combination of diverse large-scale biological evidence

当前后基因组分子生物学和生物信息学研究的一个主要挑战是充分理解基因调控：在细胞生命过程中，每个基因是如何以及何时开启和关闭的，特别是在响应不断变化的环境或细胞状态时。基因调控对生物体的生存至关重要，而破译基因是如何被调控的对于理解基因调控错误是至关重要的，而基因调控错误是疾病和发育畸形的主要原因。破译基因调控是一个逆向工程问题。目标是通过实验证据来理解一个系统（在这个例子中是细胞）是如何工作的。为此，生物学家干扰输入（环境变化或基因改变）并监测输出（例如，测量细胞中基因的相对丰度）。输出的不同测量代表了同一调节机制的各个方面，可以结合起来制定精确的基因调节模型。这些模型通常被称为基因调控或转录网络。

A major challenge in current post-genome molecular biology and bioinformatics research is to fully understand gene regulation: how and when each and every gene is switched on and off during the life of the cell, particularly in response to changing environmental or cellular states. Gene regulation is essential to organism survival, and deciphering how genes are regulated is critical for understanding genetic misregulation, a major cause of disease and developmental malformations. Deciphering gene regulation is a reverse-engineering problem. The goal is to understand how a system (in this case the cell) works from experimental evidence. To this end, biologists disturb the inputs (changes in the environment or genetic alterations) and monitor the outputs (for example, measurements of relative abundance of genes in the cell). Distinct measurements of the outputs represent aspects of the same regulatory mechanism and can be combined to formulate accurate models of gene regulation. These models are usually called gene regulatory or transcriptional networks.