New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.
New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.
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DOI：
10.3389/fgene.2017.00165
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发表时间：
2017
影响因子：
3.7
通讯作者：
Raittz RT
中科院分区：
文献类型：
--
作者：
Nichio BTL;Marchaukoski JN;Raittz RT
如今，序列之间的同源性关系对于同源性的生物学研究至关重要。大型生物数据库，研究人员已经开始分析旨在在直系同源群体预测中选择最有前途的计算机方法和工具。研究领域的文献描述了大多数可用工具所显示的问题，例如准确性，分析所需的时间（尤其是鉴于提交的数据量的增加，需要更快的技术）和自动化的自动化问题。该过程不需要手动干预。我们开发的最新技术和工具可以解决矫形器检测中仍然存在的大多数问题。工具并指出每个人试图解决的问题。哪些限制，例如有限数量的查询，计算成本和高度处理时间来完成分析。其算法或proteinortho（改善了直源组的准确性）； （使用用于处理大量生物学数据的算法来最小化处理时间）和蛋白质。对研究人员有用，并将帮助他们选择最合适的工具，用于在矫正领域。
Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST “all-against-all” methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing time); and proteinOrtho (developed for dealing with large amounts of biological data). We made a comparison among the main features of four tool and tested them using four for prokaryotic genomas. We hope that our review can be useful for researchers and will help them in selecting the most appropriate tool for their work in the field of orthology.
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影响因子：
4.3
作者：
Altenhoff, Adrian M.;Dessimoz, Christophe
通讯作者：
Dessimoz, Christophe
影响因子：
4.4
作者：
Rane RV;Oakeshott JG;Nguyen T;Hoffmann AA;Lee SF
通讯作者：
Lee SF
影响因子：
3
作者：
Lassmann T;Sonnhammer EL
通讯作者：
Sonnhammer EL
DOI：
10.1073/pnas.0904673106
发表时间：
2009-09-22
影响因子：
11.1
作者：
Novo, Maite;Bigey, Frederic;Dequin, Sylvie
通讯作者：
Dequin, Sylvie
影响因子：
5.8
作者：
Söding, J
通讯作者：
Söding, J