@article{b4c43e639cf9474497019b9555b357bb,
title = "MTGIpick allows robust identification of genomic islands from a single genome",
abstract = "Genomic islands (GIs) that are associated with microbial adaptations and carry sequence patterns different from that of the host are sporadically distributed among closely related species. This bias can dominate the signal of interest in GI detection. However, variations still exist among the segments of the host, although no uniform standard exists regarding the best methods of discriminating GIs from the rest of the genome in terms of compositional bias. In the present work, we proposed a robust software, MTGIpick, which used regions with pattern bias showingmultiscale difference levels to identify GIs from the host. MTGIpick can identify GIs from a single genome without annotated information of genomes or prior knowledge from other data sets. When real biological data were used, MTGIpick demonstrated better performance than existing methods, as well as revealed potential GIs with accurate sizesmissed by existingmethods because of a uniform standard. Software and supplementary are freely available at http://bioinfo.zstu.edu.cn/MTGI or https://github.com/bioinfo0706/MTGIpick.",
keywords = "Boundary detection, Feature selection, Genomic island detection, Genomic signature, Multiscale statistical test",
author = "Qi Dai and Chaohui Bao and Yabing Hai and Sheng Ma and Tao Zhou and Cong Wang and Yunfei Wang and Wenwen Huo and Xiaoqing Liu and Yuhua Yao and Zhenyu Xuan and Min Chen and Zhang, {Michael Q.}",
note = "Funding Information: The authors thank Prof. Kamil S. Jaron, Jiri C. Moravec and Natalia Martinkova for providing data sets and technical help for SigHunt; Prof. Sharmila S. Mande for providing the software of centroid and INDeGenIUS; and Prof. Wei Wen for providing the technical help and prediction results of other tools on L-data set. The National Natural Science Foundation of China (grant number 61370015), the National Basic Research Program of China (grant number 2012CB316503), Zhejiang Provincial Natural Science Foundation of China (grant number LY14F020046), Public Projects of Zhejiang Province (grant number 2015C33141) and 521 Talent Cultivation Plan of Zhejiang Sci-Tech University. Funding for open access charge: National Natural Science Foundation of China. The NIH/NIAID (grant number AI116610 to M.Q.Z.). Funding Information: The National Natural Science Foundation of China (grant number 61370015), the National Basic Research Program of China (grant number 2012CB316503), Zhejiang Provincial Natural Science Foundation of China (grant number LY14F020046), Public Projects of Zhejiang Province (grant number 2015C33141) and 521 Talent Cultivation Plan of Zhejiang Sci-Tech University. Funding for open access charge: National Natural Science Foundation of China. The NIH/NIAID (grant number AI116610 to M.Q.Z.). Publisher Copyright: {\textcopyright} The Author 2017. Published by Oxford University Press. All rights reserved.",
year = "2018",
month = may,
day = "1",
doi = "10.1093/bib/bbw118",
language = "English (US)",
volume = "19",
pages = "361--373",
journal = "Briefings in Bioinformatics",
issn = "1467-5463",
publisher = "Oxford University Press",
number = "3",
}