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Functional classification of long non-coding RNAs by k-mer content
by
Wang, Shuo
, Weeks, Kevin M.
, Baker, Allison R.
, Sprague, Daniel
, Collins, David W.
, Kim, Susan O.
, Kirk, Jessime M.
, Lee, David M.
, Schertzer, Megan D.
, Inoue, Kaoru
, Mucha, Peter J.
, Wooten, Joshua S.
, Chen, Qidi
, Smola, Matthew J.
, Calabrese, J. Mauro
, Horning, Christopher R.
in
13/109
/ 45/44
/ 45/70
/ 631/114/2184
/ 631/208/200
/ 631/208/212/2019
/ 631/337/176
/ 64/60
/ Agriculture
/ Algorithms
/ Animal Genetics and Genomics
/ Animals
/ Base Sequence
/ Binding sites
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ Chromosomes
/ Classification
/ Cluster Analysis
/ Coding
/ Conserved Sequence
/ Databases, Genetic
/ Functional analysis (Mathematics)
/ Gene expression
/ Gene Function
/ Genomes
/ Hep G2 Cells
/ Homology
/ Human Genetics
/ Humans
/ Hypotheses
/ K562 Cells
/ Localization
/ Mice
/ Molecular Sequence Annotation
/ Nucleic Acid Conformation
/ Nucleotide Motifs - genetics
/ Potassium Channels, Voltage-Gated - genetics
/ Protein binding
/ Proteins
/ RNA
/ RNA, Long Noncoding - chemistry
/ RNA, Long Noncoding - classification
/ RNA, Long Noncoding - genetics
/ Sequence Alignment
/ Sequence Analysis, RNA - methods
2018
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Functional classification of long non-coding RNAs by k-mer content
by
Wang, Shuo
, Weeks, Kevin M.
, Baker, Allison R.
, Sprague, Daniel
, Collins, David W.
, Kim, Susan O.
, Kirk, Jessime M.
, Lee, David M.
, Schertzer, Megan D.
, Inoue, Kaoru
, Mucha, Peter J.
, Wooten, Joshua S.
, Chen, Qidi
, Smola, Matthew J.
, Calabrese, J. Mauro
, Horning, Christopher R.
in
13/109
/ 45/44
/ 45/70
/ 631/114/2184
/ 631/208/200
/ 631/208/212/2019
/ 631/337/176
/ 64/60
/ Agriculture
/ Algorithms
/ Animal Genetics and Genomics
/ Animals
/ Base Sequence
/ Binding sites
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ Chromosomes
/ Classification
/ Cluster Analysis
/ Coding
/ Conserved Sequence
/ Databases, Genetic
/ Functional analysis (Mathematics)
/ Gene expression
/ Gene Function
/ Genomes
/ Hep G2 Cells
/ Homology
/ Human Genetics
/ Humans
/ Hypotheses
/ K562 Cells
/ Localization
/ Mice
/ Molecular Sequence Annotation
/ Nucleic Acid Conformation
/ Nucleotide Motifs - genetics
/ Potassium Channels, Voltage-Gated - genetics
/ Protein binding
/ Proteins
/ RNA
/ RNA, Long Noncoding - chemistry
/ RNA, Long Noncoding - classification
/ RNA, Long Noncoding - genetics
/ Sequence Alignment
/ Sequence Analysis, RNA - methods
2018
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Functional classification of long non-coding RNAs by k-mer content
by
Wang, Shuo
, Weeks, Kevin M.
, Baker, Allison R.
, Sprague, Daniel
, Collins, David W.
, Kim, Susan O.
, Kirk, Jessime M.
, Lee, David M.
, Schertzer, Megan D.
, Inoue, Kaoru
, Mucha, Peter J.
, Wooten, Joshua S.
, Chen, Qidi
, Smola, Matthew J.
, Calabrese, J. Mauro
, Horning, Christopher R.
in
13/109
/ 45/44
/ 45/70
/ 631/114/2184
/ 631/208/200
/ 631/208/212/2019
/ 631/337/176
/ 64/60
/ Agriculture
/ Algorithms
/ Animal Genetics and Genomics
/ Animals
/ Base Sequence
/ Binding sites
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ Chromosomes
/ Classification
/ Cluster Analysis
/ Coding
/ Conserved Sequence
/ Databases, Genetic
/ Functional analysis (Mathematics)
/ Gene expression
/ Gene Function
/ Genomes
/ Hep G2 Cells
/ Homology
/ Human Genetics
/ Humans
/ Hypotheses
/ K562 Cells
/ Localization
/ Mice
/ Molecular Sequence Annotation
/ Nucleic Acid Conformation
/ Nucleotide Motifs - genetics
/ Potassium Channels, Voltage-Gated - genetics
/ Protein binding
/ Proteins
/ RNA
/ RNA, Long Noncoding - chemistry
/ RNA, Long Noncoding - classification
/ RNA, Long Noncoding - genetics
/ Sequence Alignment
/ Sequence Analysis, RNA - methods
2018
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Functional classification of long non-coding RNAs by k-mer content
Journal Article
Functional classification of long non-coding RNAs by k-mer content
2018
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Overview
The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.
SEEKR is a method that deconstructs linear sequence relationships between lncRNAs and evaluates similarity on the basis of abundance of short motifs called k-mers. LncRNAs of related function often have similar k-mer profiles despite lacking linear homology.
Publisher
Nature Publishing Group US,Nature Publishing Group
Subject
/ 45/44
/ 45/70
/ 64/60
/ Animal Genetics and Genomics
/ Animals
/ Biomedical and Life Sciences
/ Coding
/ Functional analysis (Mathematics)
/ Genomes
/ Homology
/ Humans
/ Mice
/ Molecular Sequence Annotation
/ Nucleotide Motifs - genetics
/ Potassium Channels, Voltage-Gated - genetics
/ Proteins
/ RNA
/ RNA, Long Noncoding - chemistry
/ RNA, Long Noncoding - classification
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