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RNA Splice Sites

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Markovian encoding models in human splice site recognition using SVM.

Computational biology and chemistry
Splice site recognition is among the most significant and challenging tasks in bioinformatics due to its key role in gene annotation. Effective prediction of splice site requires nucleotide encoding methods that reveal the characteristics of DNA sequ...

Human Splice-Site Prediction with Deep Neural Networks.

Journal of computational biology : a journal of computational molecular cell biology
Accurate splice-site prediction is essential to delineate gene structures from sequence data. Several computational techniques have been applied to create a system to predict canonical splice sites. For classification tasks, deep neural networks (DNN...

COSSMO: predicting competitive alternative splice site selection using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Alternative splice site selection is inherently competitive and the probability of a given splice site to be used also depends on the strength of neighboring sites. Here, we present a new model named the competitive splice site model (COS...

DeepDSSR: Deep Learning Structure for Human Donor Splice Sites Recognition.

Studies in health technology and informatics
Human genes often, through alternative splicing of pre-messenger RNAs, produce multiple mRNAs and protein isoforms that may have similar or completely different functions. Identification of splice sites is, therefore, crucial to understand the gene s...

Using the Chou's 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks.

Computers in biology and medicine
Neural models have been able to obtain state-of-the-art performances on several genome sequence-based prediction tasks. Such models take only nucleotide sequences as input and learn relevant features on their own. However, extracting the interpretabl...

Splice sites detection using chaos game representation and neural network.

Genomics
A novel method is proposed to detect the acceptor and donor splice sites using chaos game representation and artificial neural network. In order to achieve high accuracy, inputs to the neural network, or feature vector, shall reflect the true nature ...

SpliceFinder: ab initio prediction of splice sites using convolutional neural network.

BMC bioinformatics
BACKGROUND: Identifying splice sites is a necessary step to analyze the location and structure of genes. Two dinucleotides, GT and AG, are highly frequent on splice sites, and many other patterns are also on splice sites with important biological fun...

Biogenesis mechanisms of circular RNA can be categorized through feature extraction of a machine learning model.

Bioinformatics (Oxford, England)
MOTIVATION: In recent years, multiple circular RNAs (circRNA) biogenesis mechanisms have been discovered. Although each reported mechanism has been experimentally verified in different circRNAs, no single biogenesis mechanism has been proposed that c...