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Identification of NAD interacting residues in proteins

Overview of attention for article published in BMC Bioinformatics, March 2010
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1 Wikipedia page

Citations

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67 Dimensions

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91 Mendeley
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2 CiteULike
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Title
Identification of NAD interacting residues in proteins
Published in
BMC Bioinformatics, March 2010
DOI 10.1186/1471-2105-11-160
Pubmed ID
Authors

Hifzur R Ansari, Gajendra PS Raghava

Abstract

Small molecular cofactors or ligands play a crucial role in the proper functioning of cells. Accurate annotation of their target proteins and binding sites is required for the complete understanding of reaction mechanisms. Nicotinamide adenine dinucleotide (NAD+ or NAD) is one of the most commonly used organic cofactors in living cells, which plays a critical role in cellular metabolism, storage and regulatory processes. In the past, several NAD binding proteins (NADBP) have been reported in the literature, which are responsible for a wide-range of activities in the cell. Attempts have been made to derive a rule for the binding of NAD+ to its target proteins. However, so far an efficient model could not be derived due to the time consuming process of structure determination, and limitations of similarity based approaches. Thus a sequence and non-similarity based method is needed to characterize the NAD binding sites to help in the annotation. In this study attempts have been made to predict NAD binding proteins and their interacting residues (NIRs) from amino acid sequence using bioinformatics tools.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 2%
Indonesia 1 1%
United States 1 1%
Unknown 87 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 33%
Researcher 17 19%
Student > Master 11 12%
Professor 3 3%
Lecturer 3 3%
Other 10 11%
Unknown 17 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 27 30%
Agricultural and Biological Sciences 21 23%
Immunology and Microbiology 5 5%
Computer Science 4 4%
Engineering 4 4%
Other 8 9%
Unknown 22 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 October 2010.
All research outputs
#7,454,427
of 22,789,566 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,280 outputs
Outputs of similar age
#34,575
of 95,095 outputs
Outputs of similar age from BMC Bioinformatics
#29
of 65 outputs
Altmetric has tracked 22,789,566 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 95,095 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.