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Cited by 389

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Advanced biofuel production in microbes

Open access
Peralta‐Yahya, Pamela P., Keasling, Jay D.·2010·Biotechnology Journal

Abstract

The cost‐effective production of biofuels from renewable materials will begin to address energy security and climate change concerns. Ethanol, naturally produced by microorganisms, is currently the major biofuel in the transportation sector. However, its low energy content and incompatibility with existing fuel distribution and storage infrastructure limits its economic use in the future. Advanced biofuels, such as long chain alcohols and isoprenoid‐ and fatty acid‐based biofuels, have physical properties that more closely resemble petroleum‐derived fuels, and as such are an attractive alternative for the future supplementation or replacement of petroleum‐derived fuels. Here, we review recent developments in the engineering of metabolic pathways for the production of known and potential advanced biofuels by microorganisms. We concentrate on the metabolic engineering of genetically tractable organisms such as Escherichia coli and Saccharomyces cerevisiae for the production of these advanced biofuels.

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Crossref · 10.1002/biot.200900220

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Metadata

Authors
Peralta‐Yahya, P. P., & Keasling, J. D.
Venue
Biotechnology Journal
Publisher
Wiley
Published
2010-02
Volume
5
Issue
2
Pages
147-162
ISSN
  • 1860-6768 (ISSN-L)
  • 1860-7314
OpenAlex
W2109910682
Cited by
389
References
8
FWCI
14.89
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Advanced biofuel production in microbes. https://app.cochat.ai/papers/10.1002/biot.200900220
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Peralta‐Yahya, P. P., & Keasling, J. D. (2010). Advanced biofuel production in microbes. Biotechnology Journal. https://doi.org/10.1002/biot.200900220

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.