Design powerful predictor for mRNA subcellular location prediction in Homo sapiens
Abstract Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of mRNA might provide spatial and temporal regulation of mRNA and protein functions. The situ hybridization and quantitative transcriptom...
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| Published in | Briefings in bioinformatics Vol. 22; no. 1; pp. 526 - 535 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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England
Oxford University Press
18.01.2021
Oxford Publishing Limited (England) |
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| Abstract | Abstract
Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of mRNA might provide spatial and temporal regulation of mRNA and protein functions. The situ hybridization and quantitative transcriptomics analysis could provide detail information about mRNA subcellular localization; however, they are time consuming and expensive. It is highly desired to develop computational tools for timely and effectively predicting mRNA subcellular location. In this work, by using binomial distribution and one-way analysis of variance, the optimal nonamer composition was obtained to represent mRNA sequences. Subsequently, a predictor based on support vector machine was developed to identify the mRNA subcellular localization. In 5-fold cross-validation, results showed that the accuracy is 90.12% for Homo sapiens (H. sapiens). The predictor may provide a reference for the study of mRNA localization mechanisms and mRNA translocation strategies. An online web server was established based on our models, which is available at http://lin-group.cn/server/iLoc-mRNA/. |
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| AbstractList | Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of mRNA might provide spatial and temporal regulation of mRNA and protein functions. The situ hybridization and quantitative transcriptomics analysis could provide detail information about mRNA subcellular localization; however, they are time consuming and expensive. It is highly desired to develop computational tools for timely and effectively predicting mRNA subcellular location. In this work, by using binomial distribution and one-way analysis of variance, the optimal nonamer composition was obtained to represent mRNA sequences. Subsequently, a predictor based on support vector machine was developed to identify the mRNA subcellular localization. In 5-fold cross-validation, results showed that the accuracy is 90.12% for Homo sapiens (H. sapiens). The predictor may provide a reference for the study of mRNA localization mechanisms and mRNA translocation strategies. An online web server was established based on our models, which is available at http://lin-group.cn/server/iLoc-mRNA/.Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of mRNA might provide spatial and temporal regulation of mRNA and protein functions. The situ hybridization and quantitative transcriptomics analysis could provide detail information about mRNA subcellular localization; however, they are time consuming and expensive. It is highly desired to develop computational tools for timely and effectively predicting mRNA subcellular location. In this work, by using binomial distribution and one-way analysis of variance, the optimal nonamer composition was obtained to represent mRNA sequences. Subsequently, a predictor based on support vector machine was developed to identify the mRNA subcellular localization. In 5-fold cross-validation, results showed that the accuracy is 90.12% for Homo sapiens (H. sapiens). The predictor may provide a reference for the study of mRNA localization mechanisms and mRNA translocation strategies. An online web server was established based on our models, which is available at http://lin-group.cn/server/iLoc-mRNA/. Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of mRNA might provide spatial and temporal regulation of mRNA and protein functions. The situ hybridization and quantitative transcriptomics analysis could provide detail information about mRNA subcellular localization; however, they are time consuming and expensive. It is highly desired to develop computational tools for timely and effectively predicting mRNA subcellular location. In this work, by using binomial distribution and one-way analysis of variance, the optimal nonamer composition was obtained to represent mRNA sequences. Subsequently, a predictor based on support vector machine was developed to identify the mRNA subcellular localization. In 5-fold cross-validation, results showed that the accuracy is 90.12% for Homo sapiens (H. sapiens). The predictor may provide a reference for the study of mRNA localization mechanisms and mRNA translocation strategies. An online web server was established based on our models, which is available at http://lin-group.cn/server/iLoc-mRNA/. Abstract Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of mRNA might provide spatial and temporal regulation of mRNA and protein functions. The situ hybridization and quantitative transcriptomics analysis could provide detail information about mRNA subcellular localization; however, they are time consuming and expensive. It is highly desired to develop computational tools for timely and effectively predicting mRNA subcellular location. In this work, by using binomial distribution and one-way analysis of variance, the optimal nonamer composition was obtained to represent mRNA sequences. Subsequently, a predictor based on support vector machine was developed to identify the mRNA subcellular localization. In 5-fold cross-validation, results showed that the accuracy is 90.12% for Homo sapiens (H. sapiens). The predictor may provide a reference for the study of mRNA localization mechanisms and mRNA translocation strategies. An online web server was established based on our models, which is available at http://lin-group.cn/server/iLoc-mRNA/. |
| Author | Chen, Wei Yang, Yu-He Lin, Hao Zhang, Zhao-Yue Wang, Dong Ding, Hui |
| Author_xml | – sequence: 1 givenname: Zhao-Yue surname: Zhang fullname: Zhang, Zhao-Yue organization: Center for Informational Biology at University of Electronic Science and Technology of China – sequence: 2 givenname: Yu-He surname: Yang fullname: Yang, Yu-He organization: Center for Informational Biology at University of Electronic Science and Technology of China – sequence: 3 givenname: Hui surname: Ding fullname: Ding, Hui organization: Center for Informational Biology at University of Electronic Science and Technology of China – sequence: 4 givenname: Dong surname: Wang fullname: Wang, Dong email: wangdong79@smu.edu.cn organization: Department of Bioinformatics at Southern Medical University – sequence: 5 givenname: Wei surname: Chen fullname: Chen, Wei email: chenweiimu@gmail.com organization: Innovative Institute of Chinese Medicine and Pharmacy at Chengdu University of Traditional Chinese Medicine – sequence: 6 givenname: Hao surname: Lin fullname: Lin, Hao email: hlin@uestc.edu.cn organization: Center for Informational Biology at University of Electronic Science and Technology of China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31994694$$D View this record in MEDLINE/PubMed |
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| Keywords | mRNA subcellular location statistical analysis feature selection web server |
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| Snippet | Abstract
Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating... Messenger RNAs (mRNAs) shoulder special responsibilities that transmit genetic code from DNA to discrete locations in the cytoplasm. The locating process of... |
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| SubjectTerms | Binomial distribution Computer applications Cytoplasm Deoxyribonucleic acid DNA Gene sequencing Genetic code Homo sapiens Hybridization Localization Servers Software Support vector machines Transcriptomics Translocation Variance analysis |
| Title | Design powerful predictor for mRNA subcellular location prediction in Homo sapiens |
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