Literature DB >> 26115539

The principles of whole-cell modeling.

Jonathan R Karr1, Koichi Takahashi2, Akira Funahashi3.   

Abstract

Whole-cell models which comprehensively predict how phenotypes emerge from genotype promise to enable rational bioengineering and precision medicine. Here, we outline the key principles of whole-cell modeling which have emerged from our work developing bacterial whole-cell models: single-cellularity; functional, genetic, molecular, and temporal completeness; biophysical realism including temporal dynamics and stochastic variation; species-specificity; and model integration and reproducibility. We also outline the whole-cell model construction process, highlighting existing resources. Numerous challenges remain to achieving fully complete models including developing new experimental tools to more completely characterize cells and developing a strong theoretical understanding of hybrid mathematics. Solving these challenges requires collaboration among computational and experimental biologists, biophysicists, biochemists, applied mathematicians, computer scientists, and software engineers.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2015        PMID: 26115539     DOI: 10.1016/j.mib.2015.06.004

Source DB:  PubMed          Journal:  Curr Opin Microbiol        ISSN: 1369-5274            Impact factor:   7.934


  18 in total

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Review 2.  Whole-Cell Models and Simulations in Molecular Detail.

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Review 3.  How to deal with parameters for whole-cell modelling.

Authors:  Ann C Babtie; Michael P H Stumpf
Journal:  J R Soc Interface       Date:  2017-08-02       Impact factor: 4.118

4.  A blueprint for human whole-cell modeling.

Authors:  Balázs Szigeti; Yosef D Roth; John A P Sekar; Arthur P Goldberg; Saahith C Pochiraju; Jonathan R Karr
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5.  Simulating single-cell metabolism using a stochastic flux-balance analysis algorithm.

Authors:  David S Tourigny; Arthur P Goldberg; Jonathan R Karr
Journal:  Biophys J       Date:  2021-10-30       Impact factor: 4.033

Review 6.  Genome-scale metabolic network models: from first-generation to next-generation.

Authors:  Chao Ye; Xinyu Wei; Tianqiong Shi; Xiaoman Sun; Nan Xu; Cong Gao; Wei Zou
Journal:  Appl Microbiol Biotechnol       Date:  2022-07-13       Impact factor: 5.560

7.  A multiscale model of the regulation of aquaporin 2 recycling.

Authors:  Christoph Leberecht; Michael Schroeder; Dirk Labudde
Journal:  NPJ Syst Biol Appl       Date:  2022-05-09

8.  Guidelines for Reproducibly Building and Simulating Systems Biology Models.

Authors:  J Kyle Medley; Arthur P Goldberg; Jonathan R Karr
Journal:  IEEE Trans Biomed Eng       Date:  2016-07-18       Impact factor: 4.538

Review 9.  Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

Authors:  Laurence Loewe; Katherine S Scheuer; Seth A Keel; Vaibhav Vyas; Ben Liblit; Bret Hanlon; Michael C Ferris; John Yin; Inês Dutra; Anthony Pietsch; Christine G Javid; Cecilia L Moog; Jocelyn Meyer; Jerdon Dresel; Brian McLoone; Sonya Loberger; Arezoo Movaghar; Morgaine Gilchrist-Scott; Yazeed Sabri; Dave Sescleifer; Ivan Pereda-Zorrilla; Andrew Zietlow; Rodrigo Smith; Samantha Pietenpol; Jacob Goldfinger; Sarah L Atzen; Erika Freiberg; Noah P Waters; Claire Nusbaum; Erik Nolan; Alyssa Hotz; Richard M Kliman; Ayalew Mentewab; Nathan Fregien; Martha Loewe
Journal:  Ann N Y Acad Sci       Date:  2016-12-05       Impact factor: 5.691

10.  Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices.

Authors:  Gopal P Sarma; Victor Faundez
Journal:  Cell Logist       Date:  2017-11-29
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