Development and maintenance of bioinformatics tools for mouse biology

在我们之前的工作中，我们开发了四个主要的生物信息学工具/数据库：（1）基于Web的ANOVA-FDR软件，提供用户友好的微阵列数据分析（http：//lgsun.grc.nia.nih.gov/ANOVA/）;（2）用于从与小鼠基因组比对的表达序列组装转录物的算法和全自动计算管道;（3）一个基于网络的浏览器，以可视化小鼠基因的所有转录本和可变剪接形式（NIA小鼠基因索引：http：//lgsun.grc.nia.nih.gov/geneindex/mm9/）;（4）基于网络的数据库和工具，用于可视化和绘制小鼠基因组的转录因子结合位点（CisView：http：//lgsun.grc.nia.nih.gov/geneindex/mm6/cisview.html）;和（5）基于网络的工具，用于基于全基因组染色质免疫沉淀结合测序（ChIP-Seq）方法鉴定共有序列基序（CisFinder：http：//lgsun.grc.nia.nih.gov/CisFinder/）。 我们还开发了一种新的算法来模拟由两个竞争的转录因子调控的基因表达。 利用这里开发的生物信息学工具，我们分析了小鼠ES细胞中特异性转录因子过表达后产生的全局基因表达谱。这些分析有助于鉴定两种活性的顺式调节元件（即，被P300、CHD 7、介体、粘着蛋白和SWI/SNF结合）或被抑制（即，具有H3 K27 me 3组蛋白标记并被Polycomb因子结合）状态。这些结果也被用于鉴定特定转录因子的最可能的下游靶基因。 我们继续将我们的软件工具应用于我们自己和合作的各种生物学问题，并发表了一些论文。我们不断努力维护和更新我们开发并提供给研究界的生物信息学资源。我们将继续致力于开发新的算法和网站，以满足生物信息学的需求。

In our previous work, we developed four major bioinformatics tools/databases: (1) the web-based ANOVA-FDR software to provide user-friendly microarray data analysis (http://lgsun.grc.nia.nih.gov/ANOVA/); (2) an algorithm and a fully-automated computational pipeline for transcript assembly from expressed sequences aligned to the mouse genome; (3) a web-based browser to visualize all transcripts and alternative spliced forms of mouse genes (NIA Mouse Gene Index: http://lgsun.grc.nia.nih.gov/geneindex/mm9/); (4) a web-based database and tool to visualize and map the transcription factor binding sites of the mouse genome (CisView: http://lgsun.grc.nia.nih.gov/geneindex/mm6/cisview.html); and (5) a web-based tool to identify consensus sequence motifs based on the genome-wide chromatin-immunoprecipitation coupled with sequencing (ChIP-Seq) method (CisFinder: http: http://lgsun.grc.nia.nih.gov/CisFinder/). We have also developed a new algorithm to simulate the gene expression regulated by two competing transcription factors. Utilizing the bioinformatics tools developed here, we analyzed the global gene expression profiles generated after the overexpression of specific transcriptions factors in mouse ES cells. The analyses helped to identify cis-regulatory elements for both active (i.e., bound by P300, CHD7, mediator, cohesin, and SWI/SNF) or repressed (i.e., with H3K27me3 histone marks and bound by Polycomb factors) states. These results were also used to identify most likely downstream target genes for specific transcription factors. We continued to apply our software tools to various biological problems of our own and in collaboration, which yielded a few publications. We are working constantly to maintain and update the bioinformatics resources that we have developed and made available to the research community. We will continue working on the development of new algorithms and websites for bioinformatics needs.