Metabolic Network Analysis Demystified
15th Annual International Conference, RECOMB 2011, Vancouver, BC, Canada, March 28-31, 2011. Proceedings
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Format: | Article |
Language: | en_US |
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Springer-Verlag
2013
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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 |
first_indexed | 2024-09-23T13:47:16Z |
format | Article |
id | mit-1721.1/80278 |
institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T13:47:16Z |
publishDate | 2013 |
publisher | Springer-Verlag |
record_format | dspace |
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 |
work_keys_str_mv | AT chindelevitchleonid metabolicnetworkanalysisdemystified AT regevaviv metabolicnetworkanalysisdemystified AT bergerleightonbonnie metabolicnetworkanalysisdemystified |