Discovery and annotation of long noncoding RNAs
By John S. Mattick, Johannes Rinn. Nature Structural &Molecular Biology, 2015
596 citations recorded by the source corpus.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/831f8ed6b59ff80c663f00d68d3fa684fefa093a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cancer Research
- Maria-Teresa Piccoli
- Kerstin Lindblad-Toh
- C. V. Dang
- J. Beermann
- J. Viereck
- Anil Sood
- Thomas Thum
- G. Semenza
In Molecular Biology
- Maria-Teresa Piccoli
- Thomas Derrien
- Kerstin Lindblad-Toh
- Yiling Lu
- C. V. Dang
- J. Beermann
- Gordon B. Mills
- J. Viereck
Citations in the corpus
- FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome (2017, methodology): “This naturally leads to the annotation of two high-confident classes of lncRNAs and mRNAs and also to the definition of a third class of ambiguous transcripts (i.e. transcripts whose the CPS is between the two cut-offs) that are named TUCp (34,40) for Transcripts of Unknown Coding potential (Figure ”
- Comprehensive Genomic Characterization of Long Non-Coding RNAs across Human Cancers (2015, background): “, 2014), whereas up to 70% of the human genome is transcribed into RNA, yielding many thousands of non-coding RNAs (Derrien et al., 2012; Mattick and Rinn, 2015).”
- Non-coding RNAs in Development and Disease: Background, Mechanisms, and Therapeutic Approaches. (2016, background): “This length threshold is a simple but convenient biophysical cut-off that separates lncRNAs from smaller ncRNA species such as miRNAs, siRNAs, and others (184, 197).”