LIFT: lncRNA identification and function-prediction tool
نویسندگان
چکیده
Long non-coding RNAs (lncRNAs) are a class of which play significant role in several biological processes. Accurate identification and sub-classification lncRNAs is crucial for exploring their characteristic functions the genome as most coding potential computation (CPC) tools fail to accurately identify, classify predict plant species. In this study, novel computational framework called LncRNA function prediction tool (LIFT) has been developed, implements least absolute shrinkage selection operator (LASSO) optimisation iterative random forests classification optimal features, position-based (PBC) method sub-classifying into different classes, Bayesian-based approach annotating lncRNA transcripts. Using LASSO, LIFT selected 31 features achieved 15-30% improvement accuracy on species when evaluated against state-of-the-art CPC tools. PBC, successfully identified intergenic antisense transcripts with greater A. thaliana Z. mays datasets.
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ژورنال
عنوان ژورنال: International Journal of Bioinformatics Research and Applications
سال: 2021
ISSN: ['1744-5485', '1744-5493']
DOI: https://doi.org/10.1504/ijbra.2021.10044394