Metabolic Network Analysis Demystified

15th Annual International Conference, RECOMB 2011, Vancouver, BC, Canada, March 28-31, 2011. Proceedings

Bibliographic Details
Main Authors: Chindelevitch, Leonid, Regev, Aviv, Berger Leighton, Bonnie
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Springer-Verlag 2013
Online Access:http://hdl.handle.net/1721.1/80278
https://orcid.org/0000-0001-8567-2049
https://orcid.org/0000-0002-2724-7228
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author Chindelevitch, Leonid
Regev, Aviv
Berger Leighton, Bonnie
author2 Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
author_facet Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Chindelevitch, Leonid
Regev, Aviv
Berger Leighton, Bonnie
author_sort Chindelevitch, Leonid
collection MIT
description 15th Annual International Conference, RECOMB 2011, Vancouver, BC, Canada, March 28-31, 2011. Proceedings
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institution Massachusetts Institute of Technology
language en_US
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spelling mit-1721.1/802782022-09-28T16:09:01Z Metabolic Network Analysis Demystified Chindelevitch, Leonid Regev, Aviv Berger Leighton, Bonnie Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Biology Massachusetts Institute of Technology. Department of Mathematics Berger, Bonnie Chindelevitch, Leonid Regev, Aviv Berger, Bonnie 15th Annual International Conference, RECOMB 2011, Vancouver, BC, Canada, March 28-31, 2011. Proceedings Metabolic networks are a representation of current knowledge about the metabolic reactions available to a given organism. These networks can be placed into various mathematical frameworks, of which the constraintbased framework [1] has received the most attention over the past 15 years. This results in a predictive model of metabolism. Metabolic models can yield predictions of two types: quantitative, such as the growth rate of an organism under given experimental conditions [2], and qualitative, such as the viability of a mutant [3] or minimal media required for growth [4]. Qualitative predictions, on which we focus, tend to be more robust and reliable than quantitative ones, while remaining experimentally testable and biologically relevant. 2013-08-26T19:09:44Z 2013-08-26T19:09:44Z 2011 2011-03 Article http://purl.org/eprint/type/ConferencePaper 978-3-642-20035-9 978-3-642-20036-6 0302-9743 1611-3349 http://hdl.handle.net/1721.1/80278 Chindelevitch, Leonid, Aviv Regev, and Bonnie Berger. Metabolic Network Analysis Demystified. Ed. Vineet Bafna, S. Cenk Shinalp. LNCS Sublibrary: SL 8 - Bioinformatics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. 31-33 https://orcid.org/0000-0001-8567-2049 https://orcid.org/0000-0002-2724-7228 en_US http://dx.doi.org/10.1007/978-3-642-20036-6_3 Research in Computational Molecular Biology Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Springer-Verlag Berger via Michael Noga
spellingShingle Chindelevitch, Leonid
Regev, Aviv
Berger Leighton, Bonnie
Metabolic Network Analysis Demystified
title Metabolic Network Analysis Demystified
title_full Metabolic Network Analysis Demystified
title_fullStr Metabolic Network Analysis Demystified
title_full_unstemmed Metabolic Network Analysis Demystified
title_short Metabolic Network Analysis Demystified
title_sort metabolic network analysis demystified
url http://hdl.handle.net/1721.1/80278
https://orcid.org/0000-0001-8567-2049
https://orcid.org/0000-0002-2724-7228
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