NONCODE 2016: an informative and valuable data source of long non-coding RNAs
By Yi Zhao, Shuangsang Fang, Yue-hu Kang, Wei Wu, Yajing Hao, Ziyang Li, Dechao Bu, Ninghui Sun, Michael Q. Zhang, Runsheng Chen. Nucleic Acids Res., 2015
565 citations recorded by the source corpus.
NONCODE (http://www.bioinfo.org/noncode/) is an interactive database that aims to present the most complete collection and annotation of non-coding RNAs, especially long non-coding RNAs (lncRNAs). The recently reduced cost of RNA sequencing has produced an explosion of newly identified data. Revolutionary third-generation sequencing methods have also contributed to more accurate annotations. Accumulative experimental data also provides more comprehensive knowledge of lncRNA functions. In this update, NONCODE has added six new species, bringing the total to 16 species altogether. The lncRNAs in NONCODE have increased from 210 831 to 527,336. For human and mouse, the lncRNA numbers are 167,150 and 130,558, respectively. NONCODE 2016 has also introduced three important new features: (i) conservation annotation; (ii) the relationships between lncRNAs and diseases; and (iii) an interface to choose high-quality datasets through predicted scores, literature support and long-read sequencing method support. NONCODE is also accessible through http://www.noncode.org/.
Subfields: Cancer Research, Endocrinology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/9b86844c375695d2ccb1a04c79cf7aa91a50bc3a
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In Cancer Research
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Citations in the corpus
- The BIG Data Center: from deposition to integration to translation (2016, background): “As of September 2016, LncRNAWiki houses a total of 105 824 non-redundant lncRNAs that are integrated from GENCODE (42), NONCODE (43) and LNCi-pedia (44).”
- NONCODEV5: a comprehensive annotation database for long non-coding RNAs (2017, methodology): “The data sources for NONCODEv5 include the previous versions of NONCODE (18–20), public literature and lncRNA databases.”
- FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome (2017, methodology): “We benchmarked FEELnc and five existing programs (PhyloCSF (14), CPC (15), CPAT (16), PLEK (17) and CNCI (18)) using known sets of lncRNAs annotated in multiple organisms (GENCODE for human and mouse (27) and NONCODE for other species (28)), and showed that FEELnc performance metrics outperformed or”
- Gene co-expression analysis for functional classification and gene–disease predictions (2017, background): “One of the major benefits of RNA-seq is that it quantifies the expression of the over 70 000 non-coding RNAs not usually measured with microarrays [1], including recently annotated lincRNAs, many of which are thought to have regulatory roles [41] and to play a role in disease [42, 43].”
- Long non-coding RNAs and complex diseases: from experimental results to computational models (2016, methodology): “The lncRNA sequences and annotation information in it are collected from three databases: GENCODE (version 19; 23 898 human lncRNA transcripts) [11, 12], NONCODE (version 4.0; 95 135 human lncRNA transcripts) [48–52] and LNCipedia (version 2.1; 32 181 human lncRNA transcripts) [37, 38].”