Trends in the development of miRNA bioinformatics tools

L Chen, L Heikkinen, C Wang, Y Yang… - Briefings in …, 2019 - academic.oup.com
MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via
recognition of cognate sequences and interference of transcriptional, translational or …

Approaches to microRNA discovery

E Berezikov, E Cuppen, RHA Plasterk - Nature genetics, 2006 - nature.com
MicroRNAs (miRNAs) are noncoding RNAs that can regulate gene expression. Several
hundred genes encoding miRNAs have been experimentally identified in animals, and …

BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches

B Liu - Briefings in bioinformatics, 2019 - academic.oup.com
With the avalanche of biological sequences generated in the post-genomic age, one of the
most challenging problems is how to computationally analyze their structures and functions …

A hybrid CNN-LSTM model for pre-miRNA classification

A Tasdelen, B Sen - Scientific reports, 2021 - nature.com
Abstract miRNAs (or microRNAs) are small, endogenous, and noncoding RNAs construct of
about 22 nucleotides. Cumulative evidence from biological experiments shows that miRNAs …

Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells

RD Morin, MD O'Connor, M Griffith… - Genome …, 2008 - genome.cshlp.org
MicroRNAs (miRNAs) are emerging as important, albeit poorly characterized, regulators of
biological processes. Key to further elucidation of their roles is the generation of more …

[HTML][HTML] Pse-in-One 2.0: an improved package of web servers for generating various modes of pseudo components of DNA, RNA, and protein sequences

B Liu, H Wu, KC Chou - Natural science, 2017 - scirp.org
Pse-in-One 2.0 is a package of web-servers evolved from Pse-in-One (Liu, B., Liu, F., Wang,
X., Chen, J. Fang, L. & Chou, KC Nucleic Acids Research, 2015, 43: W65-W71). In order to …

A novel hierarchical selective ensemble classifier with bioinformatics application

L Wei, S Wan, J Guo, KKL Wong - Artificial intelligence in medicine, 2017 - Elsevier
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 …

Active learning from imbalanced data: A solution of online weighted extreme learning machine

H Yu, X Yang, S Zheng, C Sun - IEEE transactions on neural …, 2018 - ieeexplore.ieee.org
It is well known that active learning can simultaneously improve the quality of the
classification model and decrease the complexity of training instances. However, several …

MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features

P Jiang, H Wu, W Wang, W Ma, X Sun… - Nucleic acids …, 2007 - academic.oup.com
To distinguish the real pre-miRNAs from other hairpin sequences with similar stem-loops
(pseudo pre-miRNAs), a hybrid feature which consists of local contiguous structure …

Identification of real microRNA precursors with a pseudo structure status composition approach

B Liu, L Fang, F Liu, X Wang, J Chen, KC Chou - PloS one, 2015 - journals.plos.org
Containing about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding
RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene …