Data Synthesis and Tool Development for Exploring Imaging Genomic Patterns.

IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology proceedings. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Pub Date : 2009-03-30 DOI:10.1109/CIBCB.2009.4925742

Sungeun Kim, Li Shen, Andrew J Saykin, John D West

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引用次数: 3

Abstract

Recent advances in brain imaging and high throughput genotyping techniques enable new approaches to study the influence of genetic variation on brain structure and function. However, major computational challenges are bottlenecks for comprehensive joint analysis of these high-dimensional image and genomic data. We report our initial progress in developing an imaging genomic browsing system for integrated exploration of neuroimaging and genomic data. We describe a method for synthesizing a set of realistic neuroimaging and genomic data, where the relationships between imaging phenotypes and genotypes are known. This data set is used to demonstrate the functionality of our system, which is designed for effectively exploring the neuroanatomical distribution of statistical results that measure the associations between brain imaging phenotypes and genotypes on a genome-wide scale. The proposed system has substantial potential for enabling discovery of important imaging genomic associations through visual evaluation and can be extended towards several directions.

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探索成像基因组模式的数据综合和工具开发。

脑成像和高通量基因分型技术的最新进展为研究遗传变异对脑结构和功能的影响提供了新的途径。然而，主要的计算挑战是这些高维图像和基因组数据的综合联合分析的瓶颈。我们报告了我们在开发成像基因组浏览系统的初步进展，该系统用于神经成像和基因组数据的综合探索。我们描述了一种方法来合成一组现实的神经成像和基因组数据，其中成像表型和基因型之间的关系是已知的。该数据集用于展示我们系统的功能，该系统旨在有效地探索统计结果的神经解剖学分布，这些统计结果可在全基因组范围内测量脑成像表型和基因型之间的关联。所提出的系统具有通过视觉评估发现重要成像基因组关联的巨大潜力，并且可以向几个方向扩展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology proceedings. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

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