The Wide and Deep Flexible Neural Tree and Its Ensemble in Predicting Long Non-coding RNA Subcellular Localization

The long non-coding RNA (lncRNA) is a hot research topic among researchers in the field of biology. Recent studies have illustrated that the subcellular localizations carry salient information to understand the complex biological functions. However, the experimental setup cost and the computational cost to identify the subcellular localization of lncRNA is too high. Therefore, there is a need of some efficient and effective methods to predict the lncRNA subcellular locations. In this paper, a wide and deep flexible neural tree (FNT) is proposed to predict the subcellular localization of lncRNA. The wide component has ability to memorize the original input features, while the deep component has ability to automatically extract hidden features. To fully exploit lncRNA sequence information, we have extracted seven features which are further fed to four wide and deep FNT classifiers respectively. By ensemble four classifiers, it can predict 5 subcellular localizations of lncRNA, including cytoplasm, nucleus, cytosol, ribosome and exosome.

[1]  Liuqing Yang,et al.  A lincRNA switch for embryonic stem cell fate , 2011, Cell Research.

[2]  Adam Krzyżak,et al.  Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..

[3]  Bo Yang,et al.  Flexible neural trees ensemble for stock index modeling , 2007, Neurocomputing.

[4]  D. Cacchiarelli,et al.  A Long Noncoding RNA Controls Muscle Differentiation by Functioning as a Competing Endogenous RNA , 2011, Cell.

[5]  David G. Knowles,et al.  The GENCODE v7 catalog of human long noncoding RNAs: Analysis of their gene structure, evolution, and expression , 2012, Genome research.

[6]  C. L. Philip Chen,et al.  Broad learning system: A new learning paradigm and system without going deep , 2017, 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC).

[7]  Wenqiang Yu,et al.  Genome-wide expression of non-coding RNA and global chromatin modification. , 2012, Acta biochimica et biophysica Sinica.

[8]  C. L. Philip Chen,et al.  Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[9]  Alexander R. Pico,et al.  Dynamic and Coordinated Epigenetic Regulation of Developmental Transitions in the Cardiac Lineage , 2012, Cell.

[10]  Heng-Tze Cheng,et al.  Wide & Deep Learning for Recommender Systems , 2016, DLRS@RecSys.

[11]  Peng Cui,et al.  Dynamic regulation of genome-wide pre-mRNA splicing and stress tolerance by the Sm-like protein LSm5 in Arabidopsis , 2014, Genome Biology.

[12]  M. Muers,et al.  RNA: Genome-wide views of long non-coding RNAs , 2011, Nature Reviews Genetics.

[13]  Yuehui Chen,et al.  Small-time scale network traffic prediction based on flexible neural tree , 2012, Appl. Soft Comput..

[14]  J. Mattick,et al.  Long noncoding RNAs are generated from the mitochondrial genome and regulated by nuclear-encoded proteins. , 2011, RNA.

[15]  Liming Chen,et al.  Discriminative Transfer Learning Using Similarities and Dissimilarities , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[16]  B. Blencowe,et al.  The nuclear-retained noncoding RNA MALAT1 regulates alternative splicing by modulating SR splicing factor phosphorylation. , 2010, Molecular cell.

[17]  Rui Liu,et al.  The lncRNA DEANR1 facilitates human endoderm differentiation by activating FOXA2 expression. , 2015, Cell reports.

[18]  Giorgio Valentini,et al.  Ensembles of Learning Machines , 2002, WIRN.

[19]  Jiwen Dong,et al.  Time-series forecasting using flexible neural tree model , 2005, Inf. Sci..

[20]  Thomas G. Dietterich.  Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[21]  Fred Winston,et al.  Intergenic transcription is required to repress the Saccharomyces cerevisiae SER3 gene , 2004, Nature.

[22]  E. Cuppen,et al.  Extensive localization of long noncoding RNAs to the cytosol and mono- and polyribosomal complexes , 2014, Genome Biology.

[23]  O. Dereure,et al.  Rôle de l’ARN non codant ANRIL dans les neurofibromes plexiformes de la neurofibromatose de type 1 , 2012 .

[24]  Carolyn J. Brown,et al.  The functional role of long non-coding RNA in human carcinomas , 2011, Molecular Cancer.

[25]  Kiejung Park,et al.  Genetic factors underlying discordance in chromatin accessibility between monozygotic twins , 2014, Genome Biology.

[26]  T. Morgan,et al.  Expression of a noncoding RNA is elevated in Alzheimer's disease and drives rapid feed-forward regulation of β-secretase , 2008, Nature Medicine.