A Multi-Processor Linux Farm for Bioinformatics and Functional Genomics

用于生物信息学和功能基因组学的多处理器 Linux 农场

• 批准号: BB/E012868/1
• 负责人: Simon Lovell
• 金额: $ 19.98万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FE012868%2F1
• 关键词: Multi; Processor; Linux; Farm; Bioinformatics

There are currently unprecedented amounts of biological data that need to be analysed to advance our understanding of the biological sciences. This is due to the increase in large-scale, high-throughput research projects in genomics and post-genomics, of which the Human Genome Project is the best known. This leads to an increase in data volumes that need to be stored, analysed and curated. Consequently, greater computing capacity is required for research at the forefront of international research. The types of questions we now wish to address involve wide-scale comparisons, such as comparing genomes from different organisms and require considerable computing infrastructure. Naturally, the limits of what can be addressed are dependent on computing support. As a group of researchers, we propose to develop and apply new computational methods to study a whole range of biological problems. We will study how DNA is organised in the cell, and how it gives rise to cellular functions. We aim to understand how the agents of action in a cell (proteins) interact to give rise to complex biological systems, and how these interactions and other functions are dependent on the three-dimensional shapes of each of the interacting molecular components. We will compare cellular components and systems from different organisms to understand how they evolve. Only through comparison of many sets of data, often from several organisms, can a new understanding of general trends and characteristics of biological organisms be obtained.

目前有前所未有的大量生物数据需要分析，以促进我们对生物科学的理解。这是由于基因组学和后基因组学的大规模、高通量研究项目的增加，其中人类基因组计划最为著名。这导致需要存储、分析和管理的数据量增加。因此，处于国际研究前沿的研究需要更大的计算能力。我们现在希望解决的问题类型涉及大规模的比较，例如比较来自不同生物体的基因组，并且需要相当大的计算基础设施。当然，可以解决的限制取决于计算支持。作为一个研究小组，我们建议开发和应用新的计算方法来研究一系列生物学问题。我们将研究DNA如何在细胞中组织，以及它如何产生细胞功能。我们的目标是了解细胞（蛋白质）中的作用剂如何相互作用以产生复杂的生物系统，以及这些相互作用和其他功能如何依赖于每个相互作用分子组分的三维形状。我们将比较不同生物体的细胞成分和系统，以了解它们是如何进化的。只有通过比较往往来自几种生物的多组数据，才能对生物有机体的一般趋势和特点有新的认识。

项目成果

Population genomics of the Wolbachia endosymbiont in Drosophila melanogaster.

• DOI: 10.1371/journal.pgen.1003129
• 发表时间: 2012
• 期刊: PLoS genetics
• 影响因子: 4.5
• 作者: Richardson MF;Weinert LA;Welch JJ;Linheiro RS;Magwire MM;Jiggins FM;Bergman CM
• 通讯作者: Bergman CM

Whole genome resequencing reveals natural target site preferences of transposable elements in Drosophila melanogaster.

• DOI: 10.1371/journal.pone.0030008
• 发表时间: 2012
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Linheiro RS;Bergman CM
• 通讯作者: Bergman CM

Annotating genes and genomes with DNA sequences extracted from biomedical articles.

• DOI: 10.1093/bioinformatics/btr043
• 发表时间: 2011-04-01
• 期刊: Bioinformatics (Oxford, England)
• 作者: Haeussler M;Gerner M;Bergman CM
• 通讯作者: Bergman CM

BioContext: an integrated text mining system for large-scale extraction and contextualization of biomolecular events.

• DOI: 10.1093/bioinformatics/bts332
• 发表时间: 2012-08-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Gerner M;Sarafraz F;Bergman CM;Nenadic G
• 通讯作者: Nenadic G