Identification of RNA pseudouridine sites using deep learning approaches

Deep neural networks for human microRNA precursor detection

(2020) Xueming Zheng et al.   BMC BIOINFORMATICS

FactorNet: a deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data

(2019) Daniel Quang et al.   METHODS

Improving text classification with weighted word embeddings via a multi-channel TextCNN model

(2019) Bao Guo et al.   NEUROCOMPUTING

iPseU-CNN: Identifying RNA Pseudouridine Sites Using Convolutional Neural Networks

(2019) Muhammad Tahir et al.   Molecular Therapy-Nucleic Acids

XG-PseU: an eXtreme Gradient Boosting based method for identifying pseudouridine sites

(2019) Kewei Liu et al.   MOLECULAR GENETICS AND GENOMICS

mRNA structure determines modification by pseudouridine synthase 1

(2019) Thomas M. Carlile et al.   Nature Chemical Biology

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

(2018) Genta Aoki et al.   BIOINFORMATICS

pLoc_bal-mAnimal: predict subcellular localization of animal proteins by balancing training dataset and PseAAC

(2018) Xiang Cheng et al.   BIOINFORMATICS

iDNA6mA-PseKNC: Identifying DNA N 6 -methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC

(2018) Pengmian Feng et al.   GENOMICS

iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC

(2018) Hui Yang et al.   International Journal of Biological Sciences

iRNA(m6A)-PseDNC: Identifying N6-methyladenosine sites using pseudo dinucleotide composition

(2018) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

PseUI: Pseudouridine sites identification based on RNA sequence information

(2018) Jingjing He et al.   BMC BIOINFORMATICS

iKcr-PseEns: Identify lysine crotonylation sites in histone proteins with pseudo components and ensemble classifier

(2017) Wang-Ren Qiu et al.   GENOMICS

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences

(2016) Daniel Quang et al.   NUCLEIC ACIDS RESEARCH

PPUS: a web server to predict PUS-specific pseudouridine sites: Table 1.

(2015) Yan-Hui Li et al.   BIOINFORMATICS

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

RMBase: a resource for decoding the landscape of RNA modifications from high-throughput sequencing data

(2015) Wen-Ju Sun et al.   NUCLEIC ACIDS RESEARCH

The new era of RNA modification

(2015) John Karijolich et al.   RNA

iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition

(2014) Shou-Hui Guo et al.   BIOINFORMATICS

Transcriptome-wide Mapping Reveals Widespread Dynamic-Regulated Pseudouridylation of ncRNA and mRNA

(2014) Schraga Schwartz et al.   CELL

Pseudouridine profiling reveals regulated mRNA pseudouridylation in yeast and human cells

(2014) Thomas M. Carlile et al.   NATURE

Transcriptome-Wide Mapping of Pseudouridines: Pseudouridine Synthases Modify Specific mRNAs in S. cerevisiae

(2014) Alexander F. Lovejoy et al.   PLoS One

A Pseudouridine Residue in the Spliceosome Core Is Part of the Filamentous Growth Program in Yeast

(2014) Anindita Basak et al.   Cell Reports

Thermodynamic contribution and nearest-neighbor parameters of pseudouridine-adenosine base pairs in oligoribonucleotides

(2013) G. A. Hudson et al.   RNA

RNA pseudouridylation: new insights into an old modification

(2013) Junhui Ge et al.   TRENDS IN BIOCHEMICAL SCIENCES

The Vienna RNA Websuite

(2008) A. R. Gruber et al.   NUCLEIC ACIDS RESEARCH