{"title":"Metabolic Pathway Alignment (M-Pal) Reveals Diversity and Alternatives in Conserved Networks","authors":"Yunlei Li, D. Ridder, M. D. Groot, M. Reinders","doi":"10.1142/9781848161092_0029","DOIUrl":null,"url":null,"abstract":"We introduce a comparative analysis of metabolic reaction networks between different species. Our method systematically investigates full metabolic networks of multiple species at the same time, with the goal of identifying highly similar yet non-identical pathways which execute the same metabolic function, i.e. the transformation of a specific substrate into a certain end product via similar reactions. We present a clear framework for matching metabolic pathways, and propose a scoring scheme which combines enzyme functional similarity with protein sequence similarity. This analysis helps to gain insight in the biological differences between species and provides comprehensive information on diversity in pathways between species and alternative pathways within species, which is useful for pharmaceutical and industrial bioengineering targets. The results also generate hypotheses for improving current metabolic networks or constructing such networks for currently unannotated species.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"474 1","pages":"273-286"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... Asia-Pacific bioinformatics conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/9781848161092_0029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
We introduce a comparative analysis of metabolic reaction networks between different species. Our method systematically investigates full metabolic networks of multiple species at the same time, with the goal of identifying highly similar yet non-identical pathways which execute the same metabolic function, i.e. the transformation of a specific substrate into a certain end product via similar reactions. We present a clear framework for matching metabolic pathways, and propose a scoring scheme which combines enzyme functional similarity with protein sequence similarity. This analysis helps to gain insight in the biological differences between species and provides comprehensive information on diversity in pathways between species and alternative pathways within species, which is useful for pharmaceutical and industrial bioengineering targets. The results also generate hypotheses for improving current metabolic networks or constructing such networks for currently unannotated species.