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Interpreting and integrating big data in non-coding rna research

EMERGING TOPICS IN LIFE SCIENCES 2019年第4期3卷 343-355页

作者： Cantarella, Simona Di Nisio, Elena Carnevali, Davide Dieci, Giorgio Montanini, Barbara Univ Parma Dept Chem Life Sci & Environm Sustainabil I-43124 Parma Italy Univ Roma La Sapienza Dept Biol & Biotechnol Charles Darwin I-00185 Rome Italy BIST CRG Barcelona 08003 Spain

In the last two decades, we have witnessed an impressive crescendo of non-coding rna studies, due to both the development of high-throughput rna-sequencing strategies and an ever-increasing awareness of the involvement of newly discovered ncrna classes in complex regulatory networks. Together with excitement for the possibility to explore previously unknown layers of gene regulation, these advancements led to the realization of the need for shared criteria of data collection and analysis and for novel integrative perspectives and tools aimed at making biological sense of very large bodies of molecular information. In the last few years, efforts to respond to this need have been devoted mainly to the regulatory interactions involving ncrnas as direct or indirect regulators of protein-coding mrnas. Such efforts resulted in the development of new computational tools, allowing the exploitation of the information spread in numerous different ncrna data sets to interpret transcriptome changes under physiological and pathological cell responses. While experimental validation remains essential to identify key rna regulatory interactions, the integration of ncrna big data, in combination with systematic literature mining, is proving to be invaluable in identifying potential new players, biomarkers and therapeutic targets in cancer and other diseases.

关键词： bioinformatics cancer competing endogenous rnas database non-coding rna rna sequencing

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A domain ontology for the non-coding rna field

A domain ontology for the non-coding RNA field

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IEEE International Conference on Bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Huang, Jingshan Eilbeck, Karen Blake, Judith A. Dou, Dejing Natale, Darren A. Ruttenberg, Alan Smith, Barry Zimmermann, Michael T. Jiang, Guoqian Lin, Yu Wu, Bin He, Yongqun Zhang, Shaojie Wang, Xiaowei Zhang, He Liu, Zixing Tan, Ming Univ S Alabama Sch Comp South Biomed Informat Grp Mobile AL 36688 USA Univ Utah Sch Med Dept Biomed Informat Salt Lake City UT 84112 USA Jackson Lab Genome Informat Bar Harbor ME 04609 USA Univ Oregon CIS Dept Eugene OR 97403 USA Georgetown Univ Med Ctr Washington DC 20007 USA Univ Buffalo Buffalo NY 14214 USA Univ Buffalo Dept Philosophy Buffalo NY 14260 USA Mayo Clin Coll Med Rochester MN 55905 USA Univ Miami Miami FL 33146 USA Kunming Med Univ Affiliated Hosp 1 Kunming 650032 Yunnan Peoples R China Univ Michigan Ann Arbor MI 48109 USA Univ Cent Florida Orlando FL 32816 USA Washington Univ Sch Med St Louis MO 63108 USA Univ S Alabama Mobile AL 36688 USA Univ S Alabama MCI Mobile AL 36604 USA

ISBN: (纸本)9781467367981

Identification of non-coding rnas (ncrnas) has been significantly enhanced due to the rapid advancement in sequencing technologies. On the other hand, semantic annotation of ncrna data lag behind their identification, and there is a great need to effectively integrate discovery from relevant communities. To this end, the non-coding rna Ontology (NCRO) is being developed to provide a precisely defined ncrna controlled vocabulary, which can fill a specific and highly needed niche in unification of ncrna biology.

关键词： non-coding rna biological and biomedical ontologies domain ontology ontology development semantic data annotation and integration

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NCRR: A novel method for measuring disease similarity based on non-coding rna regulation

NCRR: A novel method for measuring disease similarity based ...

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IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM)

作者： Zhang, Ningyi Juan, Liran Zang, Tianyi Harbin Inst Technol Sch Comp Sci & Technol Harbin Peoples R China Harbin Inst Technol Sch Life Sci & Technol Harbin Peoples R China

ISBN: (纸本)9781728162157

Complex diseases are not simply caused by a single gene, single mrna transcript or single protein but the effect of their collaborations. Measuring similarity between complex diseases plays an important role in understanding the mechanism of the diseases, which can also support identifying potential therapeutic drugs for diseases. With the rapid development of technology, it has been consentaneous that functional associations between disease-related genes and semantic associations can be applied to calculate disease similarity. Recent years, more and more studies have demonstrated a profound involvement of the non-coding rna in the regulation of genome organization and gene expression. non-coding rna seem to operate at several biological levels such as epigenetic processes that control differentiation and development. Thus, taking non-coding rna into account can be useful in measuring disease similarities. However, existing methods ignore the regulation functions of non-coding rna in biological process. In this work, we proposed a novel method, NCRR (non-coding rna regulated based similarity measurement), to measure disease similarity integrating functional associations between disease-related genes, semantic associations between diseases and similarities between disease-related non-coding rnas. NCRR employs the Jaccard coefficient to measure the similarity between gene sets regulated by disease-related lncrnas and disease-related mirnas.

关键词： non-coding rna disease similarity semantic association gene functional network

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Learning Parameters for non-coding rna Sequence-Structure Alignment

Learning Parameters for Non-coding RNA Sequence-Structure Al...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBMW 2009)

作者： Song, Yinglei Liu, Chunmei Qu, Junfeng Univ MD Eastern Shore Dept Math & Comp Sci Princess Anne MD 21853 USA Howard Univ Dept Syst & Comp Sci Washington DC 20059 USA Clarion Univ Pennsylvania Dept Informat Technol Morrow GA USA

ISBN: (纸本)9781424451203

Sequence-structure alignment is the most important part for an algorithm that can search genomes and identify non-coding rnas. A model that can accurately describe the secondary structure of a noncoding rna faamily is crucial to the search accuracy of genome annotation. In this paper we develop a novel machine learning approach that can capture the crucial structure features of a noncoding rna family and estimate the parameters in its secondary structure Model. One advantage of this approach is that these estimated parameters contain structure features that are generally missing in the conventional Covariance Model (CM). Our experiments showed that compared with the conventional CM, structure models obtained with our approach can provide a more accurate description of the secondary structure in a noncoding rna family and thus significantly improve the accuracy of genome annotation.

关键词： non-coding rna Sequence-Structure Alignment Parameter Estimation Convex Optimization

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Transcriptional regulation of Oct4 by a long non-coding rna antisense to Oct4-pseudogene 5

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TRANSCRIPTION-AUSTIN 2010年第3期1卷 165-175页

作者： Hawkins, Peter G. Morris, Kevin, V Scripps Res Inst Dept Mol & Expt Med 10666 N Torrey Pines Rd La Jolla CA 92037 USA Scripps Res Inst Kellogg Sch Sci & Technol La Jolla CA USA

Long non-coding rnas (lncrnas) have been shown to epigenetically regulate certain genes in human cells. Here we report evidence for the involvement of an antisense lncrna in the transcriptional regulation of the pluripotency-associated factor Oct4. When an lncrna antisense to Oct4-pseudogene 5 was suppressed, transcription of Oct4 and Oct4 pseudogenes 4 and 5 was observed to increase. This increase correlated with a loss of silent state epigenetic marks and the histone methyltransferase Ezh2 at the Oct4 promoter. We observed this lncrna to interact with nucleolin and PURA, a 35 kD single-stranded DNA and rna binding protein, and found that these proteins may act to negatively regulate this antisense transcript.

关键词： Oct4 PURA nucleolin non-coding rna pseudogenes

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Deciphering the Far-Reaching Functions of non-coding rna in Colorectal Cancer

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CURRENT COLORECTAL CANCER REPORTS 2018年第4期14卷 115-127页

作者： Iacona, Joseph R. Marks, Daniel E. Monteleone, Nicholas J. Lutz, Carol S. Univ Med & Dent New Jersey Rutgers Biomed & Hlth Sci Dept Microbiol Biochem & Mol Genet Hlth Sci Campus Newark Newark NJ 07103 USA Sch Grad Studies Hlth Sci Campus Newark Newark NJ 07103 USA

Purpose of Review Colorectal cancer (CRC) is one of the deadliest forms of cancer worldwide, and researchers are continuously striving to discover novel therapeutic targets and treatment methods. Many of the molecular mechanisms central to CRC development and progression have yet to be elucidated. The goal of this review is to highlight the most recent findings and theories behind the role of non-coding rnas (ncrnas) in CRC. Recent Findings Recent work has indicated that ncrnas, rna molecules that are not translated into protein, play significant roles in cellular events directly affecting CRC cell proliferation, migration, invasion, and survival. These ncrnas include specific micrornas (mirnas), long non-coding rnas (lncrnas), and other types of rnas. Many of these molecules themselves are oncogenic or tumor suppressive in nature, and some have been suggested to be diagnostic and/or prognostic biomarkers in CRC. Ncrnas can impact gene expression and signal transduction through various mechanisms on epigenetic, transcriptional, post-transcriptional, translational, and post-translational levels. Summary Understanding the biological mechanisms governing CRC initiation and propagation may lead to novel therapeutics and biomarkers for treating this deadly disease.

关键词： Colorectal cancer non-coding rna microrna Gene expression Long non-coding rna Biomarker

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Cost-Sensitive Classification on Class-balanced Ensembles for Imbalanced non-coding rna Data

Cost-Sensitive Classification on Class-balanced Ensembles fo...

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IEEE EMBS International Student Conference (ISC)

作者： Elkarami, Bashier Alkhateeb, Abed Rueda, Luis Univ Windsor Dept Elect & Comp Engn 401 Sunset Ave Windsor ON Canada Univ Windsor Sch Comp Sci 401 Sunset Ave Windsor ON Canada

ISBN: (纸本)9781509009350

Many bioinformatics data sets have class imbalanced data, where the number of samples in each class is not equal. Since most of data sets contain usual versus unusual cases, e.g. cancer versus normal or mirnas versus other non-coding rna, where the minority class with the least number of samples is the interesting class that contains the unusual cases. The learning models based on the standard classifiers, such as the support vector machine (SVM), random forest and k-NN are usually biased towards the majority class, which means that the classifier is most likely to predict the samples from the interesting class inaccurately. Thus, handling class-imbalanced data set has gained the researchers interests recently. A combination of proper feature selection, a cost-sensitive classifier and ensembling based on random forest method (BCE-CSC-RF) is proposed to handle the class-imbalanced data. Random class-balanced ensembles are built individually. Then, each ensemble is used as a training pool to classify the rest of out-bagged samples. Samples in each ensemble will be classified using class-sensitive classifier that incorporates random forest. The sample will be classified by selecting the most often class has been voted-for in all samples appearances in all the formed ensembles. A set of performance measurements including a geometric measurement suggests that the model can improve the classification of the minority class samples.

关键词： Transcriptomatics class-imbalanced data non-coding rna mi-rna ensembles cost-sensitive classifier feature selections

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Identification of Long non-coding rna from inherent features using Machine Learning Techniques

Identification of Long Non-coding RNA from inherent features...

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International Conference on Bioinformatics and Systems Biology (BSB)

作者： Sreeshma, C. M. Manu, Madhavan Gopakumar, G. Natl Inst Technol Calicut Dept Comp Sci & Engn Kozhikode 673601 Kerala India

ISBN: (纸本)9781538664346

Long non-coding rnas are a distinctive class of non-coding rnas of length greater than 200 nucleotides and no protein coding potential. Lncrna plays an important role in genetic and epigenetic regulation. Major studies reveal that lncrnas are less conserved in their primary sequences and shows more functional characteristics at secondary structure level. The objective of this work is to identify an optimal sequencestructure combination for computational analysis of lncrnas. We also propose a novel secondary structure quantization which consider the existence of various structure elements. The feature combinations when used as input to classification of lncrnas from coding rnas, significant improvement in the results were obtained.

关键词： coding rna non-coding rna Long noncoding rna (lncrna) rna Secondary structure rnafold Support Vector Machine Random Forest

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Distinct rna degradation pathways and 3' extensions of yeast non-coding rna species

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TRANSCRIPTION-AUSTIN 2011年第3期2卷 145-154页

作者： Marquardt, Sebastian Hazelbaker, Dane Z. Buratowski, Stephen Harvard Med Sch Dept Biol Chem & Mol Pharmacol Boston MA 02115 USA

non coding transcripts originating from bidirectional promotershave been reported in a wide range of organisms. In yeast, these divergent transcripts can be subdivided into two classes. Some are designated Cryptic Unstable Transcripts (CUTs) because they are terminated by the Nrdl-Nab3-Sen1 pathway and then rapidly degraded by the nuclear exosome. This is the same processing pathway used by yeast snoRNIAs, Whereas CUTs are only easily observed in cells lacking the Rrp6 or Rrp47 subunits of the nuclear exosome, Stable Uncharacterized Transcripts (SUTs) are present even in wild-type cells. Here we show that SUTs are partially susceptible to the nuclear exosome, but are primarily degraded by cytoplasmic 5' to 3' degradation and nonsense-mediated decay (NMD). Therefore, SUTs may be processed similarly to rrirnas. Surprisingly, both CUTs and SUTs were found to produce 3' extended species that were also subject to cytoplasmic degradation. The functions, if any, of these extended CUTs and SUTs are unknown, but their discovery suggests that yeasts generate transcripts reminiscent of long non-coding rnas found in higher eukaryotes.

关键词： non-coding rna CUT SUT bidirectional promoter divergent transcription long non-coding rna Xrn1 non-coding transcript turnover NMD chromatin

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A fast approximate covariance-model-based database search method for non-coding rna

A fast approximate covariance-model-based database search me...

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3rd International Symposium on Bioinformatics Research and Applications

作者： Smith, Scott F. Boise State Univ Dept Elect & Comp Engn Boise ID 83725 USA

ISBN: (纸本)9783540720300

A covariance-model-based search method for non-coding rna genes is proposed which is much faster than dynamic programming, but which is shown to be very effective in experimental tests. The method incorporates secondary structure information in the entire first pass of the database, unlike the usual primary-sequence-only pre-filters applied when using dynamic programming. An iterative alignment refining algorithm which starts at an ungapped alignment and successively selects alignment breakpoints gives only an approximation to the optimal alignment, but appears to be sufficient for gene localization.

关键词： non-coding rna functional rna covariance models database search gene finding dynamic programming

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