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Prediction of protein-RNA residue-base contacts using two-dimensional conditional random field with the lasso

Overview of attention for article published in BMC Systems Biology, December 2013
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Title
Prediction of protein-RNA residue-base contacts using two-dimensional conditional random field with the lasso
Published in
BMC Systems Biology, December 2013
DOI 10.1186/1752-0509-7-s2-s15
Pubmed ID
Authors

Morihiro Hayashida, Mayumi Kamada, Jiangning Song, Tatsuya Akutsu

Abstract

To uncover molecular functions and networks in biological cellular systems, it is important to dissect interactions between proteins and RNAs. Many studies have been performed to investigate and analyze interactions between protein amino acid residues and RNA bases. In terms of interactions between residues in proteins, it is generally accepted that an amino acid residue at interacting sites has coevolved together with the partner residue in order to keep the interaction between residues in proteins. Based on this hypothesis, in our previous study to identify residue-residue contact pairs in interacting proteins, we made calculations of mutual information (M I) between amino acid residues from some multiple sequence alignment of homologous proteins, and combined it with a discriminative random field (DRF) approach, which is a special type of conditional random fields (CRFs) and has been proved useful for the purpose of extracting distinguishing areas from a photograph in the image processing field. Recently, the evolutionary correlation of interactions between residues and DNA bases has also been found in certain transcription factors and the DNA-binding sites.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 29%
Researcher 3 21%
Student > Bachelor 1 7%
Student > Master 1 7%
Student > Postgraduate 1 7%
Other 0 0%
Unknown 4 29%
Readers by discipline Count As %
Computer Science 3 21%
Biochemistry, Genetics and Molecular Biology 2 14%
Agricultural and Biological Sciences 1 7%
Environmental Science 1 7%
Psychology 1 7%
Other 1 7%
Unknown 5 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 December 2013.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from BMC Systems Biology
#1,004
of 1,132 outputs
Outputs of similar age
#270,495
of 307,722 outputs
Outputs of similar age from BMC Systems Biology
#42
of 44 outputs
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So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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