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dc.contributor.authorYin, Zhaoting
dc.contributor.authorLyu, Jianyi
dc.contributor.authorZhang, Guiyang
dc.contributor.authorHuang, Xiaohong
dc.contributor.authorMa, Qinghua
dc.contributor.authorJiang, Jinyun
dc.date.accessioned2024-12-09T10:07:53Z
dc.date.available2024-12-09T10:07:53Z
dc.date.issued2024
dc.identifier.citationYin, Z., Lyu, J., Zhang, G., Huang, X., Ma, Q., & Jiang, J. (2024). SoftVoting6mA : An improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes. <i>Mathematical Biosciences and Engineering</i>, <i>21</i>(3), 3798-3815. <a href="https://doi.org/10.3934/mbe.2024169" target="_blank">https://doi.org/10.3934/mbe.2024169</a>
dc.identifier.otherCONVID_213330738
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/98862
dc.description.abstractThe DNA N6-methyladenine (6mA) is an epigenetic modification, which plays a pivotal role in biological processes encompassing gene expression, DNA replication, repair, and recombination. Therefore, the precise identification of 6mA sites is fundamental for better understanding its function, but challenging. We proposed an improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes called SoftVoting6mA. The SoftVoting6mA selected four (electron–ion-interaction pseudo potential, One-hot encoding, Kmer, and pseudo dinucleotide composition) codes from 15 types of encoding to represent DNA sequences by comparing their performances. Similarly, the SoftVoting6mA combined four learning algorithms using the soft voting strategy. The 5-fold cross-validation and the independent tests showed that SoftVoting6mA reached the state-of-the-art performance. To enhance accessibility, a user-friendly web server is provided at http://www.biolscience.cn/SoftVoting6mA/.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherAmerican Institute of Mathematical Sciences
dc.relation.ispartofseriesMathematical Biosciences and Engineering
dc.rightsCC BY 4.0
dc.subject.otherDNA N6-methyladenine
dc.subject.otherconvolution neural network
dc.subject.othersoft voting
dc.subject.othercross-species
dc.subject.otherfeature fusion
dc.subject.otherwebserver
dc.titleSoftVoting6mA : An improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202412097676
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange3798-3815
dc.relation.issn1547-1063
dc.relation.numberinseries3
dc.relation.volume21
dc.type.versionpublishedVersion
dc.rights.copyright©2024 the Author(s), licensee AIMS Press.
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.subject.ysobioinformatiikka
dc.subject.ysokoneoppiminen
dc.subject.ysogeeniekspressio
dc.subject.ysoneuroverkot
dc.subject.ysoDNA
dc.subject.ysopalvelimet
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p15748
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
jyx.subject.urihttp://www.yso.fi/onto/yso/p25831
jyx.subject.urihttp://www.yso.fi/onto/yso/p7292
jyx.subject.urihttp://www.yso.fi/onto/yso/p7690
jyx.subject.urihttp://www.yso.fi/onto/yso/p638
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.datasethttps://github.com/yinzhaoting/Softvoting-6mA
dc.relation.doi10.3934/mbe.2024169
jyx.fundinginformationThe work was supported by Shaoyang University Innovation Foundation for Postgraduate (CX2022SY058).
dc.type.okmA1


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