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Bioprospecting metagenomes: glycosyl hydrolases for converting biomass

Overview of attention for article published in Biotechnology for Biofuels, May 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
1 tweeter
patent
1 patent
wikipedia
1 Wikipedia page

Citations

dimensions_citation
120 Dimensions

Readers on

mendeley
370 Mendeley
citeulike
3 CiteULike
connotea
1 Connotea
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Title
Bioprospecting metagenomes: glycosyl hydrolases for converting biomass
Published in
Biotechnology for Biofuels, May 2009
DOI 10.1186/1754-6834-2-10
Pubmed ID
Authors

Luen-Luen Li, Sean R McCorkle, Sebastien Monchy, Safiyh Taghavi, Daniel van der Lelie

Abstract

Throughout immeasurable time, microorganisms evolved and accumulated remarkable physiological and functional heterogeneity, and now constitute the major reserve for genetic diversity on earth. Using metagenomics, namely genetic material recovered directly from environmental samples, this biogenetic diversification can be accessed without the need to cultivate cells. Accordingly, microbial communities and their metagenomes, isolated from biotopes with high turnover rates of recalcitrant biomass, such as lignocellulosic plant cell walls, have become a major resource for bioprospecting; furthermore, this material is a major asset in the search for new biocatalytics (enzymes) for various industrial processes, including the production of biofuels from plant feedstocks. However, despite the contributions from metagenomics technologies consequent upon the discovery of novel enzymes, this relatively new enterprise requires major improvements. In this review, we compare function-based metagenome screening and sequence-based metagenome data mining, discussing the advantages and limitations of both methods. We also describe the unusual enzymes discovered via metagenomics approaches, and discuss the future prospects for metagenome technologies.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 370 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 10 3%
United States 5 1%
Sweden 3 <1%
United Kingdom 3 <1%
Spain 2 <1%
France 2 <1%
Malaysia 2 <1%
Indonesia 2 <1%
Mexico 2 <1%
Other 17 5%
Unknown 322 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 99 27%
Researcher 73 20%
Student > Master 48 13%
Student > Bachelor 36 10%
Student > Postgraduate 24 6%
Other 72 19%
Unknown 18 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 206 56%
Biochemistry, Genetics and Molecular Biology 58 16%
Environmental Science 26 7%
Chemistry 14 4%
Immunology and Microbiology 11 3%
Other 24 6%
Unknown 31 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 07 May 2015.
All research outputs
#2,036,528
of 12,880,184 outputs
Outputs from Biotechnology for Biofuels
#174
of 982 outputs
Outputs of similar age
#46,378
of 275,489 outputs
Outputs of similar age from Biotechnology for Biofuels
#9
of 73 outputs
Altmetric has tracked 12,880,184 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 982 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done well, scoring higher than 81% 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 275,489 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.