Hamdalla Mai A, Ammar Reda A, Rajasekaran Sanguthevar
BMC Bioinformatics. 2015;16 Suppl 5(Suppl 5):S11. doi: 10.1186/1471-2105-16-S5-S11. Epub 2015 Mar 18.
Metabolomics is the study of small molecules, called metabolites, of a cell, tissue or organism. It is of particular interest as endogenous metabolites represent the phenotype resulting from gene expression. A major challenge in metabolomics research is the structural identification of unknown biochemical compounds in complex biofluids. In this paper we present an efficient cheminformatics tool, BioSMXpress that uses known endogenous mammalian biochemicals and graph matching methods to identify endogenous mammalian biochemical structures in chemical structure space. The results of a comprehensive set of empirical experiments suggest that BioSMXpress identifies endogenous mammalian biochemical structures with high accuracy. BioSMXpress is 8 times faster than our previous work BioSM without compromising the accuracy of the predictions made. BioSMXpress is freely available at http://engr.uconn.edu/~rajasek/BioSMXpress.zip.
代谢组学是对细胞、组织或生物体中称为代谢物的小分子的研究。它特别引人关注，因为内源性代谢物代表了基因表达产生的表型。代谢组学研究中的一个主要挑战是复杂生物流体中未知生化化合物的结构鉴定。在本文中，我们提出了一种高效的化学信息学工具BioSMXpress，它使用已知的内源性哺乳动物生化物质和图形匹配方法来识别化学结构空间中的内源性哺乳动物生化结构。一组全面的实证实验结果表明，BioSMXpress能够高精度地识别内源性哺乳动物生化结构。BioSMXpress比我们之前的工作BioSM快8倍，同时不影响预测的准确性。可从http://engr.uconn.edu/~rajasek/BioSMXpress.zip免费获取BioSMXpress。
