BioKnow Health Informatics Lab, College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China.
BioKnow Health Informatics Lab, College of Life Sciences, Jilin University, Changchun 130012, China.
Bioinformatics. 2020 Jan 1;36(1):49-55. doi: 10.1093/bioinformatics/btz506.
Cell divisions start from replicating the double-stranded DNA, and the DNA replication process needs to be precisely regulated both spatially and temporally. The DNA is replicated starting from the DNA replication origins. A few successful prediction models were generated based on the assumption that the DNA replication origin regions have sequence level features like physicochemical properties significantly different from the other DNA regions.
This study proposed a feature selection procedure to further refine the classification model of the DNA replication origins. The experimental data demonstrated that as large as 26% improvement in the prediction accuracy may be achieved on the yeast Saccharomyces cerevisiae. Moreover, the prediction accuracies of the DNA replication origins were improved for all the four yeast genomes investigated in this study.
The software sefOri version 1.0 was available at http://www.healthinformaticslab.org/supp/resources.php. An online server was also provided for the convenience of the users, and its web link may be found in the above-mentioned web page.
Supplementary data are available at Bioinformatics online.
细胞分裂始于复制双链 DNA,而 DNA 复制过程需要在空间和时间上进行精确调控。DNA 从 DNA 复制起始点开始复制。一些成功的预测模型是基于这样的假设生成的,即 DNA 复制起始区域具有序列水平的特征,如物理化学性质与其他 DNA 区域有显著差异。
本研究提出了一种特征选择程序,以进一步完善 DNA 复制起始点的分类模型。实验数据表明,在酵母酿酒酵母中,预测准确性可提高高达 26%。此外,本研究中研究的所有四个酵母基因组的 DNA 复制起始点的预测准确性都得到了提高。
软件 sefOri 版本 1.0 可在 http://www.healthinformaticslab.org/supp/resources.php 获得。还为用户提供了一个在线服务器,其网络链接可在上述网页中找到。
补充数据可在生物信息学在线获得。