Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.
Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorith...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-05-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC4447414?pdf=render |
| _version_ | 1819114379966152704 |
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| author | Jonathan R Karr Alex H Williams Jeremy D Zucker Andreas Raue Bernhard Steiert Jens Timmer Clemens Kreutz DREAM8 Parameter Estimation Challenge Consortium Simon Wilkinson Brandon A Allgood Brian M Bot Bruce R Hoff Michael R Kellen Markus W Covert Gustavo A Stolovitzky Pablo Meyer |
| author_facet | Jonathan R Karr Alex H Williams Jeremy D Zucker Andreas Raue Bernhard Steiert Jens Timmer Clemens Kreutz DREAM8 Parameter Estimation Challenge Consortium Simon Wilkinson Brandon A Allgood Brian M Bot Bruce R Hoff Michael R Kellen Markus W Covert Gustavo A Stolovitzky Pablo Meyer |
| author_sort | Jonathan R Karr |
| collection | DOAJ |
| description | Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. |
| first_indexed | 2024-12-22T04:44:22Z |
| format | Article |
| id | doaj.art-2a2eb868df8148ecaf650daab711d510 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-22T04:44:22Z |
| publishDate | 2015-05-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-2a2eb868df8148ecaf650daab711d5102022-12-21T18:38:39ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-05-01115e100409610.1371/journal.pcbi.1004096Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.Jonathan R KarrAlex H WilliamsJeremy D ZuckerAndreas RaueBernhard SteiertJens TimmerClemens KreutzDREAM8 Parameter Estimation Challenge ConsortiumSimon WilkinsonBrandon A AllgoodBrian M BotBruce R HoffMichael R KellenMarkus W CovertGustavo A StolovitzkyPablo MeyerWhole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.http://europepmc.org/articles/PMC4447414?pdf=render |
| spellingShingle | Jonathan R Karr Alex H Williams Jeremy D Zucker Andreas Raue Bernhard Steiert Jens Timmer Clemens Kreutz DREAM8 Parameter Estimation Challenge Consortium Simon Wilkinson Brandon A Allgood Brian M Bot Bruce R Hoff Michael R Kellen Markus W Covert Gustavo A Stolovitzky Pablo Meyer Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. PLoS Computational Biology |
| title | Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. |
| title_full | Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. |
| title_fullStr | Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. |
| title_full_unstemmed | Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. |
| title_short | Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. |
| title_sort | summary of the dream8 parameter estimation challenge toward parameter identification for whole cell models |
| url | http://europepmc.org/articles/PMC4447414?pdf=render |
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