A New Approach For Identifying Regulatory Motifs in Groups of Co-regulated Genes

达特茅斯学院因在罗伯特·格罗斯博士的指导下进一步开发BEAM软件而获奖。BEAM是一种新的模体发现程序，具有简单易用、精度高、对噪声数据有很强的鲁棒性等优点。它不需要用户输入除基因列表之外的任何信息，但BEAM在寻找非退化候选调控基序方面优于其他程序。BEAM是一个模式驱动的程序，它采用了剪枝搜索策略。与完整列举所有可能的主题相比，这导致搜索空间减少了几个数量级。只关注每个基序长度上得分最高的子基序的搜索树可能会识别出与生物相关的基序。这种高效的方法允许BEAM除了使用标准的过度表示外，还可以利用计算要求很高的目标函数。该奖项的研究旨在将BEAM扩展到一套可以发现其他类型的调控基序的程序--那些包含模棱两可的字符和两部分基序的程序。此外，我们将开发一种方法，允许我们寻找可能一起发挥作用的主题的组合。整个程序套件将通过一个集成的前端提供。达特茅斯大学环境的一个重要组成部分是本科生参与研究。参与开发我们的初始方法和开发波束算法的关键人员中有三个是本科生。这些学生和研究生一样，在实验室发挥作用，参加期刊俱乐部、研讨会和实验室会议。一旦我们的论文被接受并完成了代码的文档编制，BEAM源代码将在网络上免费共享。这将在标准GNU许可证下完成。到目前为止，Java代码可以在Mac、Windows和Unix系统上运行。

Dartmouth College is given an award for further development of the BEAM software under the direction of Dr. Robert Gross. BEAM (Beam-search Enumerative Algorithm for Motif finding) is a new kind of motif finding program that is simple to use, accurate, and very robust to noisy data. It does not require the user to input any information other than a list of genes, yet BEAM outperforms other programs in finding non-degenerate candidate regulatory motifs. BEAM is a pattern-driven program that employs a pruned search strategy. This results in a reduction of the search space by several orders of magnitude compared to a complete enumeration of all possible motifs. A search tree that focuses only on the highest scoring submotifs at every motif length is likely to identify the biologically relevant motifs. The highly efficient approach allows BEAM to utilize computationally demanding objective functions in addition to the standard over-representation. The research in this award is aimed at expanding BEAM into a suite of programs that can find additional types of regulatory motifs - those containing ambiguous characters as well as bipartite motifs. In addition, we will develop an approach that allows us to look for combinations of motifs that might function together. The entire suite of programs will be made available through an integrated front end. An important part of the Dartmouth environment is the involvement of undergraduates in research. Three of the key people involved in developing our initial approach and in developing the BEAM algorithm are undergraduates. These students function in the lab as would graduate students, participating in journal clubs, seminars, and lab meetings. The BEAM source code will be shared freely over the web once we have papers accepted and have completed the documentation of the code. This will be done under the standard GNU license. As of now, the Java code runs on Mac, Windows, and Unix systems.