MODOMICS: a database of RNA modification pathways—2013 update

By M. Machnicka, Kaja Milanowska, Okan Osman Oglou, Elżbieta Purta, M. Kurkowska, Anna Olchowik, W. Januszewski, Sebastian Kalinowski, Stanislaw Dunin-Horkawicz, Kristian Rother and 3 more. Nucleic Acids Res., 2012

998 citations recorded by the source corpus.

MODOMICS is a database of RNA modifications that provides comprehensive information concerning the chemical structures of modified ribonucleosides, their biosynthetic pathways, RNA-modifying enzymes and location of modified residues in RNA sequences. In the current database version, accessible at http://modomics.genesilico.pl, we included new features: a census of human and yeast snoRNAs involved in RNA-guided RNA modification, a new section covering the 5′-end capping process, and a catalogue of ‘building blocks’ for chemical synthesis of a large variety of modified nucleosides. The MODOMICS collections of RNA modifications, RNA-modifying enzymes and modified RNAs have been also updated. A number of newly identified modified ribonucleosides and more than one hundred functionally and structurally characterized proteins from various organisms have been added. In the RNA sequences section, snRNAs and snoRNAs with experimentally mapped modified nucleosides have been added and the current collection of rRNA and tRNA sequences has been substantially enlarged. To facilitate literature searches, each record in MODOMICS has been cross-referenced to other databases and to selected key publications. New options for database searching and querying have been implemented, including a BLAST search of protein sequences and a PARALIGN search of the collected nucleic acid sequences.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c6804d16e1f4e3bde4d535384a699e65479634b6

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Citations in the corpus

MODOMICS: a database of RNA modification pathways. 2017 update (2017, background): “Since the previous release of MODOMICS (14), 19 new modifications were added to the database.”
SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features (2016, background): “Frequency (npi ) = C (npi ) W − d − 1 (2)”
Expanded microbial genome coverage and improved protein family annotation in the COG database (2014, background): “Although most of these newly recognized functions already have been recorded in UniProt and the MODOMICS database (34,65), not all of them have been propagated to the entire protein families and used in genome annotation.”
RNA N6-methyladenosine methylation in post-transcriptional gene expression regulation (2015, background): “To date, more than a hundred structurally distinct chemical modifications have been found in eukaryotic RNAs (Cantara et al. 2011; Machnicka et al. 2013); however, the enzymes responsible for each modification and the biological consequences of these modified RNAs are largely unknown.”
GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes (2015, methodology): “First, we integrated all available RNA modification data directly from the extremely valuable MODOMICS database (18), as tRNAs are densely modified and knowledge of these different modifications is critical for better understanding tRNA function.”
Transcriptome-wide mapping reveals widespread dynamic regulated pseudouridylation of ncRNA and mRNA (2014, positive): “…25, 2014 ª2014 Elsevier Inc. 159 immediately following ‘‘U.’’ To compare orthologous rRNA sites across species, we used ‘‘needle’’ (Rice et al., 2000) for pairwise alignments of rRNAs with lift over of known J sites (Machnicka et al., 2013) from human to mouse and from S. cerevisiae to C. albicans.”
m6A RNA Methylation Regulates the Self-Renewal and Tumorigenesis of Glioblastoma Stem Cells (2017, background): “More than 100 RNA modifications have been reported, including modifications within mRNAs (Machnicka et al., 2013), among which N6-methyladenosine (m6A) modification is the most prevalent internal modification in eukaryotic mRNAs (Wei et al.”
A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package. (2014, background): “MeRIP-Seq (more comprehensively detailed in [2]) in theory enabled the transcriptome-wide unbiased study of a large number of known post-transcriptional RNA modifications [5] at a high resolution, provided that the corresponding antibody is available.”