Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

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Abstract

Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, for the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website including documentation, examples, and installation instructions can be found at http://cameo.bio. Users can also give cameo a try at http://try.cameo.bio.
Original languageEnglish
JournalA C S Synthetic Biology
Volume7
Issue number4
Pages (from-to)1163-1166
ISSN2161-5063
DOIs
Publication statusPublished - 2018

Bibliographical note

This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium,
provided the author and source are cited.

Keywords

  • Metabolic engineering
  • Genome-scale metabolic models
  • Heterologous pathway predictions
  • Computer-aided design
  • Software
  • Python

Cite this

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title = "Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories",
abstract = "Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, for the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website including documentation, examples, and installation instructions can be found at http://cameo.bio. Users can also give cameo a try at http://try.cameo.bio.",
keywords = "Metabolic engineering, Genome-scale metabolic models, Heterologous pathway predictions, Computer-aided design, Software, Python",
author = "Cardoso, {Joao G.R.} and Kristian Jensen and Christian Lieven and Hansen, {Anne Sofie L{\ae}rke} and Svetlana Galkina and Moritz Beber and Emre {\"O}zdemir and Herrg{\aa}rd, {Markus J.} and Henning Redestig and Nikolaus Sonnenschein",
note = "This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.",
year = "2018",
doi = "10.1021/acssynbio.7b00423",
language = "English",
volume = "7",
pages = "1163--1166",
journal = "A C S Synthetic Biology",
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publisher = "American Chemical Society",
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T1 - Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

AU - Cardoso, Joao G.R.

AU - Jensen, Kristian

AU - Lieven, Christian

AU - Hansen, Anne Sofie Lærke

AU - Galkina, Svetlana

AU - Beber, Moritz

AU - Özdemir, Emre

AU - Herrgård, Markus J.

AU - Redestig, Henning

AU - Sonnenschein, Nikolaus

N1 - This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.

PY - 2018

Y1 - 2018

N2 - Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, for the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website including documentation, examples, and installation instructions can be found at http://cameo.bio. Users can also give cameo a try at http://try.cameo.bio.

AB - Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, for the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website including documentation, examples, and installation instructions can be found at http://cameo.bio. Users can also give cameo a try at http://try.cameo.bio.

KW - Metabolic engineering

KW - Genome-scale metabolic models

KW - Heterologous pathway predictions

KW - Computer-aided design

KW - Software

KW - Python

U2 - 10.1021/acssynbio.7b00423

DO - 10.1021/acssynbio.7b00423

M3 - Journal article

VL - 7

SP - 1163

EP - 1166

JO - A C S Synthetic Biology

JF - A C S Synthetic Biology

SN - 2161-5063

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ER -