Department of Computational Biology, University of Lausanne, Biophore, 1015 Lausanne, Switzerland.
Department of Integrative Biology, University of California, 3060 Valley Life Sciences Bldg, Berkeley, CA 94720-3140, USA.
Nucleic Acids Res. 2019 Jan 8;47(D1):D50-D54. doi: 10.1093/nar/gky986.
The study of molecular coevolution, due to its potential to identify gene regions under functional or structural constraints, has recently been subject to numerous scientific inquiries. Particular efforts have been conducted to develop methods predicting the presence of coevolution in molecular sequences. Among these methods, a few aim to model the underlying evolutionary process of coevolution, which enable to differentiate the shared history of genes to coevolution and thus improve their accuracy. However, the usage of such methods remains sparse due to their expensive computational cost and the lack of resources alleviating this issue. Here we present CoevDB (http://phylodb.unil.ch/CoevDB), a database containing the result of a large-scale analysis of intramolecular coevolution of 8201 protein-coding genes of bony vertebrates. The web interface of CoevDB gives access to the results to 800 millions of statistical tests corresponding to all the pairs of sites analyzed. Several type of queries enable users to explore the database by either targeting specific genes or by discovering genes having promising estimations of coevolution.
由于分子共进化研究有可能识别受功能或结构约束的基因区域，因此最近受到了众多科学研究的关注。人们特别努力开发预测分子序列中存在共进化的方法。在这些方法中，有一些旨在模拟共进化的潜在进化过程，从而区分基因共进化的共同历史，从而提高其准确性。然而，由于其昂贵的计算成本和缺乏缓解此问题的资源，因此这些方法的使用仍然很少。
在这里，我们介绍了 CoevDB（http://phylodb.unil.ch/CoevDB），这是一个包含对 8201 个骨鱼类蛋白编码基因的分子内共进化进行大规模分析的结果的数据库。CoevDB 的 Web 界面可以访问对应于所有分析的位点对的 8 亿次统计测试的结果。用户可以通过针对特定基因或发现具有共进化估计值的有希望的基因，通过几种类型的查询来探索数据库。
