USING COMPUTERS TO ANALYZE TRANSCRIPTION FACTOR NETWORKS

这项研究计划的目标是开发和实施描述转录因子网络的新计算方法，转录因子网络是控制许多发育和其他细胞过程的“硬连线”遗传信号。该方法使用大量的基因表达数据集和调控区域的原始序列，将转录因子的表达与潜在的结合序列相关联，即表达基因调控区域中的任何短基序。该项目的第一阶段要求使用现有的微阵列表达数据集和原始上游序列开发算法。该提案的第二部分需要将该技术应用于多细胞生物，并开发分子技术来收集细胞类型特异性表达数据。转录因子与人类遗传疾病（如视网膜母细胞瘤）有关。了解转录因子网络对疾病和发育缺陷的治疗具有巨大的潜力。

The goal of this research proposal is to develop and implement new computational methods that describe transcription factor networks, the "hardwired" genetic signals that control many developmental and other cellular processes. The method uses large gene expression data sets and raw sequence of regulatory regions to correlate expression of a transcription factor with a potential binding sequence, that is, any short motif in the regulatory regions of expressed genes. The first stage of the project calls for developing the algorithm using existing microarray expression data sets and raw upstream sequence. The second part of the proposal entails adapting the technique to a multicellular organism and developing molecular techniques to gather cell-type specific expression data. Transcription factors have been implicated in human genetic disease (e.g. retinoblastoma). Understanding transcription factor networks has great potential for treatment of diseases and developmental defects.