Evidence map›Paper›PMID 20202206›Full record

ArticleBMC microbiology2010

GASdb: a large-scale and comparative exploration database of glycosyl hydrolysis systems.

Fengfeng Zhou, Huiling Chen, Ying Xu

Abstract read
In one paragraph

Article in BMC microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fengfeng ZhouComputational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.
Huiling Chen
Ying Xu

Funding

Structure Prediction of Helical Transmembrane ProteinsR01GM075331 · NIGMS · UNIVERSITY OF GEORGIA · PI XU, YING · 2007 to 2010
$1.2M
High-Accuracy Models of Proteins from Remote HomologyR01GM081682 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE · 2007 to 2009
$824k
NIGMS NIH HHS 1R01GM075331NIGMS NIH HHS 1R01GM081682
6 · The paper itself

Abstract

backgroundThe genomes of numerous cellulolytic organisms have been recently sequenced or in the pipeline of being sequenced. Analyses of these genomes as well as the recently sequenced metagenomes in a systematic manner could possibly lead to discoveries of novel biomass-degradation systems in nature. DESCRIPTION: We have identified 4,679 and 49,099 free acting glycosyl hydrolases with or without carbohydrate binding domains, respectively, by scanning through all the proteins in the UniProt Knowledgebase and the JGI Metagenome database. Cellulosome components were observed only in bacterial genomes, and 166 cellulosome-dependent glycosyl hydrolases were identified. We observed, from our analysis data, unexpected wide distributions of two less well-studied bacterial glycosyl hydrolysis systems in which glycosyl hydrolases may bind to the cell surface directly rather than through linking to surface anchoring proteins, or cellulosome complexes may bind to the cell surface by novel mechanisms other than the other used SLH domains. In addition, we found that animal-gut metagenomes are substantially enriched with novel glycosyl hydrolases.

conclusionsThe identified biomass degradation systems through our large-scale search are organized into an easy-to-use database GASdb at http://csbl.bmb.uga.edu/~ffzhou/GASdb/, which should be useful to both experimental and computational biofuel researchers.

Indexed as

Databases, GeneticArchaeaBacteriaBiomassDatabase Management SystemsData MiningEukaryotaGlycoside HydrolasesMetabolic Networks and PathwaysMetagenomicsModels, GeneticModels, MolecularUser-Computer InterfaceGlycoside Hydrolases

Identifiers

PMID20202206
PMCPMC2838879

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.