Literature DB >> 31602621

Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human.

Tunahan Çakır1, Emel Kökrek1, Gülben Avşar1, Ecehan Abdik1, Pınar Pir2.   

Abstract

Genome-scale modelling in eukaryotes has been pioneered by the yeast Saccharomyces cerevisiae. Early metabolic networks have been reconstructed based on genome sequence and information accumulated in the literature on biochemical reactions. Protein-protein interaction networks have been constructed based on experimental observations such as yeast-2-hybrid method. Gene regulatory networks were based on a variety of data types, including information on TF-promoter binding and gene coexpression. The aforementioned networks have been improved gradually, and methods for their integration were developed. Incorporation of omics data including genomics, metabolomics, transcriptomics, fluxome, and phosphoproteome led to next-generation genome-scale models. The methods tested on yeast have later been implemented in human, further, cellular components found to be important in yeast physiology under (ab)normal conditions, and (dis)regulation mechanisms in yeast shed light to the healthy and disease states in human. This chapter provides a historical perspective on next-generation genome-scale models incorporating multilevel 'omics data, from yeast to human.

Entities:  

Keywords:  Data integration; Metabolic networks; Metabolomics; Protein–protein interaction networks; Proteomics; Transcriptional regulatory networks; Transcriptomics

Mesh:

Year:  2019        PMID: 31602621     DOI: 10.1007/978-1-4939-9736-7_20

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  54 in total

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Authors:  Tae-Min Kim; Peter J Park
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2011 Jan-Feb

Review 2.  Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models.

Authors:  Emanuel Gonçalves; Joachim Bucher; Anke Ryll; Jens Niklas; Klaus Mauch; Steffen Klamt; Miguel Rocha; Julio Saez-Rodriguez
Journal:  Mol Biosyst       Date:  2013-03-25

3.  Reconstruction of insulin signal flow from phosphoproteome and metabolome data.

Authors:  Katsuyuki Yugi; Hiroyuki Kubota; Yu Toyoshima; Rei Noguchi; Kentaro Kawata; Yasunori Komori; Shinsuke Uda; Katsuyuki Kunida; Yoko Tomizawa; Yosuke Funato; Hiroaki Miki; Masaki Matsumoto; Keiichi I Nakayama; Kasumi Kashikura; Keiko Endo; Kazutaka Ikeda; Tomoyoshi Soga; Shinya Kuroda
Journal:  Cell Rep       Date:  2014-08-14       Impact factor: 9.423

4.  A network of protein-protein interactions in yeast.

Authors:  B Schwikowski; P Uetz; S Fields
Journal:  Nat Biotechnol       Date:  2000-12       Impact factor: 54.908

Review 5.  Fifteen years of large scale metabolic modeling of yeast: developments and impacts.

Authors:  Tobias Osterlund; Intawat Nookaew; Jens Nielsen
Journal:  Biotechnol Adv       Date:  2011-08-06       Impact factor: 14.227

6.  Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network.

Authors:  Iman Famili; Jochen Forster; Jens Nielsen; Bernhard O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-24       Impact factor: 11.205

7.  Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network.

Authors:  Jochen Förster; Iman Famili; Patrick Fu; Bernhard Ø Palsson; Jens Nielsen
Journal:  Genome Res       Date:  2003-02       Impact factor: 9.043

8.  Transcriptional regulatory networks in Saccharomyces cerevisiae.

Authors:  Tong Ihn Lee; Nicola J Rinaldi; François Robert; Duncan T Odom; Ziv Bar-Joseph; Georg K Gerber; Nancy M Hannett; Christopher T Harbison; Craig M Thompson; Itamar Simon; Julia Zeitlinger; Ezra G Jennings; Heather L Murray; D Benjamin Gordon; Bing Ren; John J Wyrick; Jean-Bosco Tagne; Thomas L Volkert; Ernest Fraenkel; David K Gifford; Richard A Young
Journal:  Science       Date:  2002-10-25       Impact factor: 47.728

Review 9.  Network-based prediction of protein function.

Authors:  Roded Sharan; Igor Ulitsky; Ron Shamir
Journal:  Mol Syst Biol       Date:  2007-03-13       Impact factor: 11.429

10.  Scope and limitations of yeast as a model organism for studying human tissue-specific pathways.

Authors:  Shahin Mohammadi; Baharak Saberidokht; Shankar Subramaniam; Ananth Grama
Journal:  BMC Syst Biol       Date:  2015-12-29
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  1 in total

1.  Genome-Wide Analysis of Yeast Metabolic Cycle through Metabolic Network Models Reveals Superiority of Integrated ATAC-seq Data over RNA-seq Data.

Authors:  Müberra Fatma Cesur; Tunahan Çakır; Pınar Pir
Journal:  mSystems       Date:  2022-06-13       Impact factor: 7.324

  1 in total

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