Baker Erich J, Galloway Leslie, Jackson Barbara, Schmoyer Denise, Snoddy Jay
Department of Computer Science, Baylor University, Waco, USA.
BMC Bioinformatics. 2004 Feb 3;5:11. doi: 10.1186/1471-2105-5-11.
Modern biological research makes possible the comprehensive study and development of heritable mutations in the mouse model at high-throughput. Using techniques spanning genetics, molecular biology, histology, and behavioral science, researchers may examine, with varying degrees of granularity, numerous phenotypic aspects of mutant mouse strains directly pertinent to human disease states. Success of these and other genome-wide endeavors relies on a well-structured bioinformatics core that brings together investigators from widely dispersed institutions and enables them to seamlessly integrate data, observations and discussions.
MuTrack was developed as the bioinformatics core for a large mouse phenotype screening effort. It is a comprehensive collection of on-line computational tools and tracks thousands of mutagenized mice from birth through senescence and death. It identifies the physical location of mice during an intensive phenotype screening process at several locations throughout the state of Tennessee and collects raw and processed experimental data from each domain. MuTrack's statistical package allows researchers to access a real-time analysis of mouse pedigrees for aberrant behavior, and subsequent recirculation and retesting. The end result is the classification of potential and actual heritable mutant mouse strains that become immediately available to outside researchers who have expressed interest in the mutant phenotype.
MuTrack demonstrates the effectiveness of using bioinformatics techniques in data collection, integration and analysis to identify unique result sets that are beyond the capacity of a solitary laboratory. By employing the research expertise of investigators at several institutions for a broad-ranging study, the TMGC has amplified the effectiveness of any one consortium member. The bioinformatics strategy presented here lends future collaborative efforts a template for a comprehensive approach to large-scale analysis.
现代生物学研究使得在小鼠模型中高通量地全面研究和开发可遗传突变成为可能。通过运用涵盖遗传学、分子生物学、组织学和行为科学的技术,研究人员能够以不同程度的精细度,直接研究与人类疾病状态相关的突变小鼠品系的众多表型特征。这些以及其他全基因组研究的成功依赖于一个结构完善的生物信息学核心,该核心汇聚了来自广泛分散机构的研究人员,并使他们能够无缝整合数据、观察结果和讨论。
MuTrack被开发为一项大型小鼠表型筛选工作的生物信息学核心。它是一个全面的在线计算工具集合,追踪数千只诱变小鼠从出生到衰老和死亡的全过程。在田纳西州各地的多个地点进行密集表型筛选过程中,它能确定小鼠的实际位置,并从每个区域收集原始和经过处理的实验数据。MuTrack的统计软件包使研究人员能够对小鼠谱系进行实时异常行为分析,以及后续的再循环和重新测试。最终结果是对潜在和实际的可遗传突变小鼠品系进行分类,这些品系可供对突变表型感兴趣的外部研究人员立即使用。
MuTrack证明了利用生物信息学技术进行数据收集、整合和分析以识别单个实验室无法完成的独特结果集的有效性。通过利用多个机构研究人员的专业知识进行广泛研究,田纳西小鼠基因组联盟(TMGC)放大了任何一个联盟成员的效能。这里提出的生物信息学策略为未来的合作努力提供了一个大规模分析综合方法的模板。