SEQUENCE ANALYSIS COMPONENT

资源的这一部分的主要重点是应用 模式识别方法，以发现监管要素，如 转录因子结合位点，在一组共调节基因。 我们 尚未从DNA阵列组获得数据集进行分析。 然而，我们一直在评估我们的计划的能力， 鉴定酵母启动子中正确的功能域， 具有已知调控位点的基因集合。 控制器具有 允许我们测试不同的方法，并进行改进， 提高其检测能力。 我们还获得了一些 来自帕特·布朗的实验数据集，并对这些数据进行分析， 进一步测试该方法以可靠地鉴定调节位点。 我们还探索了我们的方法阐明 当多个蛋白质参与协同作用时， 调控 我们已经使用来自MetJ阻遏物的数据完成了这一点， e.因为有足够的数据进行分析。 一篇论文 描述了这些结果。 我们认为 检测多个结合位点并解释其 合作相互作用对一些酵母基因很重要， 我们在E上采用和改进的方法。大肠杆菌的例子很有用 经验和准备。 我们还一直在开发和完善我们的 特异性鉴定蛋白质-蛋白质中所涉及的基序的方法 交互. 为此，我们使用了MHC-肽相互作用的数据 以识别被识别的子域并对能量域进行建模， 单个氨基酸的贡献。 这种方法似乎是 运行良好，并将通过其他数据集进一步完善。 我们 我认为这种方法将适用于其他类型的数据， 蛋白质-蛋白质相互作用，特别是用于识别 允许蛋白质对接成复合物的基序。

The primary focus of this component of the Resource is to apply pattern recognition methods to discover regulatory elements, such as transcription factor binding sites, in sets of co-regulated genes. We have not yet gotten datasets from the DNA array group for analysis. However, we have been assessing the ability of our programs to identify the correct functional domains in yeast promoters using collections of genes with known regulatory sites. The controls have allowed us to test different approaches and to make refinements to to improve their detection capability. We have also obtain a couple of experimental datasets from Pat Brown and have run analyses on those as further tests of the methods to reliably identify regulatory sites. We have also explored the ability of our methods to elucidate cooperative interactions when multiple proteins are involved in the regulation. We have done this using data from the MetJ repressor from E. coli because adequate data exist for this analysis. A paper describing these results has been submitted. We think that the ability to detect multiple binding sites and account for their cooperative interactions will be important for some yeast genes, and the approach we've adopted and refined on an E. coli example is useful experience and preparation. We have also been developing and refining an adaptation of our method to specifically identify motifs involved in protein-protein interactions. For this we have used data on MHC-peptide interactions to identify the sub-domain being recognized and to model the energetic contributions of individual amino acids. This method appears to be working well and will be further refined with additional datasets. We think this method will be applicable to other types of data concerning protein-protein interactions, specifically for the identification of motifs that allow for docking of the proteins into complexes.