دورية أكاديمية
IIMLP: integrated information-entropy-based method for LncRNA prediction
| العنوان: | IIMLP: integrated information-entropy-based method for LncRNA prediction |
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| المؤلفون: | Junyi Li, Huinian Li, Xiao Ye, Li Zhang, Qingzhe Xu, Yuan Ping, Xiaozhu Jing, Wei Jiang, Qing Liao, Bo Liu, Yadong Wang |
| المصدر: | BMC Bioinformatics, Vol 22, Iss S3, Pp 1-12 (2021) |
| بيانات النشر: | BMC, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| مصطلحات موضوعية: | Long non-coding RNA, Information entropy, Generalized topological entropy, Machine learning, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| الوصف: | Abstract Background The prediction of long non-coding RNA (lncRNA) has attracted great attention from researchers, as more and more evidence indicate that various complex human diseases are closely related to lncRNAs. In the era of bio-med big data, in addition to the prediction of lncRNAs by biological experimental methods, many computational methods based on machine learning have been proposed to make better use of the sequence resources of lncRNAs. Results We developed the lncRNA prediction method by integrating information-entropy-based features and machine learning algorithms. We calculate generalized topological entropy and generate 6 novel features for lncRNA sequences. By employing these 6 features and other features such as open reading frame, we apply supporting vector machine, XGBoost and random forest algorithms to distinguish human lncRNAs. We compare our method with the one which has more K-mer features and results show that our method has higher area under the curve up to 99.7905%. Conclusions We develop an accurate and efficient method which has novel information entropy features to analyze and classify lncRNAs. Our method is also extendable for research on the other functional elements in DNA sequences. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1471-2105 |
| Relation: | https://doaj.org/toc/1471-2105 |
| DOI: | 10.1186/s12859-020-03884-w |
| URL الوصول: | https://doaj.org/article/edb4331fd50e4bb3a04827e65f243c33 |
| رقم الأكسشن: | edsdoj.b4331fd50e4bb3a04827e65f243c33 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 14712105 |
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| DOI: | 10.1186/s12859-020-03884-w |