Combinatorial models and algorithms for comparative genomics

我提出的研究计划侧重于开发非平凡的组合模型和有效的算法，用于基因组数据的比较和分析。该项目的主要方面涉及整个基因组的基因顺序比较。特别是，我将研究两个方面：（1）利用组合结构守恒给出的信息，（2）将现有的模型扩展到多基因家族的情况。在这两个问题中，我将集中精力研究公共区间的概念。精确的问题，将在第一时间研究的是检测重排的基因簇，分配合理的进化关系在多基因家庭，和计算的进化方案。由此产生的算法将被实施并用于分析几个基因组数据集，包括原核基因组-基本上是细菌基因组，从生物医学的角度来看是最重要的-和真核基因组-酵母和脊椎动物。我还计划研究生物网络，特别是基因调控网络。我将研究一组几个网络之间的保守结构的概念和可能的祖先网络的重建。最后，我对非编码RNA基因分析算法的发展很感兴趣。特别是，我将研究如何通过将这些结构分解为简单的茎环子结构来比较它们。

The research program I propose focuses on the development of  non-trivial combinatorial  models and efficient algorithms for genomic data comparison and analysis. The main aspect of this project deals with the comparison, in terms of gene order, of whole genomes. In particular, I will study two aspects: (1) using the information given by the conservation of combinatorial structures, (2) extending the existing models to the case of genomes with multigenes families. In both problems, I will concentrate my efforts on the notion of common intervals. The precise problems that will be studied in a first time are the detection of rearranged gene clusters, the assignment of plausible evolutionary relations in multigenes families, and the computation of evolution scenarios. The resulting algorithms will be implemented and used to analyse several datasets of genomes, including prokaryotic genomes - essentially bacterial genomes, that are of primary importance from a biomedical point of view - and eukaryotic genomes - yeasts and vertebrates. I also plan to work on biological networks, in particuliar gene regulation networks. I will study the notion of conserved structures among a set of several networks and the reconstruction of possible ancestral networks. Finally, I am interested in the developement of algorithms for the analysis of noncoding RNA genes. In particular, I will study how to compare such structures by decomposing them into simple stem-loops substructures.