Evidence map›Paper›PMID 25346727›Full record

ReviewFrontiers in microbiology2014

Genetic resources for advanced biofuel production described with the Gene Ontology.

Trudy Torto-Alalibo, Endang Purwantini, Jane Lomax, João C Setubal, Biswarup Mukhopadhyay, Brett M Tyler

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
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

12 citing papers in PubMed, 28 citations in OpenAlex.

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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

6 authors at 3 institutions in 3 countries.

Trudy Torto-AlaliboDepartment of Biochemistry, Virginia Polytechnic Institute and State University Blacksburg, VA, USA ; Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.
Endang PurwantiniDepartment of Biochemistry, Virginia Polytechnic Institute and State University Blacksburg, VA, USA ; Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University Blacksburg, VA, USA.
Jane LomaxEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge, UK.
João C SetubalVirginia Bioinformatics Institute, Virginia Polytechnic Institute and State University Blacksburg, VA, USA ; Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo São Paulo, Brazil.
Biswarup MukhopadhyayDepartment of Biochemistry, Virginia Polytechnic Institute and State University Blacksburg, VA, USA ; Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University Blacksburg, VA, USA ; Department of Biological Sciences, Oregon State University Corvallis, OR, USA.
Brett M TylerVirginia Bioinformatics Institute, Virginia Polytechnic Institute and State University Blacksburg, VA, USA ; Center for Genome Research and Biocomputing, Oregon State University Corvallis, OR, USA.
Virginia Tech · USOregon State University · USEuropean Bioinformatics Institute · GB

Funding

Resource ProjectU41HG002273 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, PAUL D. · 2012 to 2021
$34.7M
NHGRI NIH HHS U41 HG002273
6 · The paper itself

Abstract

Dramatic increases in research in the area of microbial biofuel production coupled with high-throughput data generation on bioenergy-related microbes has led to a deluge of information in the scientific literature and in databases. Consolidating this information and making it easily accessible requires a unified vocabulary. The Gene Ontology (GO) fulfills that requirement, as it is a well-developed structured vocabulary that describes the activities and locations of gene products in a consistent manner across all kingdoms of life. The Microbial ENergy processes Gene Ontology () project is extending the GO to include new terms to describe microbial processes of interest to bioenergy production. Our effort has added over 600 bioenergy related terms to the Gene Ontology. These terms will aid in the comprehensive annotation of gene products from diverse energy-related microbial genomes. An area of microbial energy research that has received a lot of attention is microbial production of advanced biofuels. These include alcohols such as butanol, isopropanol, isobutanol, and fuels derived from fatty acids, isoprenoids, and polyhydroxyalkanoates. These fuels are superior to first generation biofuels (ethanol and biodiesel esterified from vegetable oil or animal fat), can be generated from non-food feedstock sources, can be used as supplements or substitutes for gasoline, diesel and jet fuels, and can be stored and distributed using existing infrastructure. Here we review the roles of genes associated with synthesis of advanced biofuels, and at the same time introduce the use of the GO to describe the functions of these genes in a standardized way.

Indexed as

advanced alcoholsadvanced biofuelscellulosomefatty acid-derived fuelGene Ontologyisoprenoid-derived fuelsynthetic biology

Identifiers

PMID25346727
PMCPMC4193338
OpenAlexW2031015245

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.