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Meta-All: a system for managing metabolic pathway information

Overview of attention for article published in BMC Bioinformatics, October 2006
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Title
Meta-All: a system for managing metabolic pathway information
Published in
BMC Bioinformatics, October 2006
DOI 10.1186/1471-2105-7-465
Pubmed ID
Authors

Stephan Weise, Ivo Grosse, Christian Klukas, Dirk Koschützki, Uwe Scholz, Falk Schreiber, Björn H Junker

Abstract

Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 3%
Netherlands 1 3%
France 1 3%
Canada 1 3%
Russia 1 3%
United States 1 3%
Unknown 24 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 30%
Student > Ph. D. Student 7 23%
Student > Bachelor 3 10%
Professor > Associate Professor 3 10%
Student > Master 2 7%
Other 3 10%
Unknown 3 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 60%
Computer Science 4 13%
Biochemistry, Genetics and Molecular Biology 2 7%
Chemistry 2 7%
Medicine and Dentistry 1 3%
Other 1 3%
Unknown 2 7%
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 04 July 2014.
All research outputs
#15,302,478
of 22,758,248 outputs
Outputs from BMC Bioinformatics
#5,372
of 7,272 outputs
Outputs of similar age
#59,796
of 68,248 outputs
Outputs of similar age from BMC Bioinformatics
#40
of 48 outputs
Altmetric has tracked 22,758,248 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,272 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 68,248 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.