AIMC Topic: RNA, Transfer

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The first two mitochondrial genomes from Taeniopterygidae (Insecta: Plecoptera): Structural features and phylogenetic implications.

International journal of biological macromolecules
The complete mitochondrial genomes (mitogenomes) of Taeniopteryx ugola and Doddsia occidentalis (Plecoptera: Taeniopterygidae) were firstly sequenced from the family Taeniopterygidae. The 15,353-bp long mitogenome of T. ugola and the 16,020-bp long m...

An artificial intelligence approach fit for tRNA gene studies in the era of big sequence data.

Genes & genetic systems
Unsupervised data mining capable of extracting a wide range of knowledge from big data without prior knowledge or particular models is a timely application in the era of big sequence data accumulation in genome research. By handling oligonucleotide c...

A novel hierarchical selective ensemble classifier with bioinformatics application.

Artificial intelligence in medicine
Selective ensemble learning is a technique that selects a subset of diverse and accurate basic models in order to generate stronger generalization ability. In this paper, we proposed a novel learning algorithm that is based on parallel optimization a...

Improving tRNAscan-SE Annotation Results via Ensemble Classifiers.

Molecular informatics
tRNAScan-SE is a tRNA detection program that is widely used for tRNA annotation; however, the false positive rate of tRNAScan-SE is unacceptable for large sequences. Here, we used a machine learning method to try to improve the tRNAScan-SE results. A...

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

Bioinformatics (Oxford, England)
MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successf...