Literature DB >> 33532729

PhenoMapping: a protocol to map cellular phenotypes to metabolic bottlenecks, identify conditional essentiality, and curate metabolic models.

Anush Chiappino-Pepe1, Vassily Hatzimanikatis1.   

Abstract

Targeted identification of cellular processes responsible for a phenotype is of major importance in guiding efforts in bioengineering and medicine. Genome-scale metabolic models (GEMs) are widely used to integrate various types of omics data and study the cellular physiology under different conditions. Here, we present PhenoMapping, a protocol that uses GEMs, omics, and phenotypic data to map cellular processes and observed phenotypes. PhenoMapping also classifies genes as conditionally and unconditionally essential and guides a comprehensive curation of GEMs. For complete details on the use and execution of this protocol, please refer to Stanway et al. (2019) and Krishnan et al. (2020).
© 2020 The Author(s).

Entities:  

Keywords:  Bioinformatics; Metabolism

Mesh:

Year:  2021        PMID: 33532729      PMCID: PMC7829271          DOI: 10.1016/j.xpro.2020.100280

Source DB:  PubMed          Journal:  STAR Protoc        ISSN: 2666-1667


  53 in total

1.  The effects of alternate optimal solutions in constraint-based genome-scale metabolic models.

Authors:  R Mahadevan; C H Schilling
Journal:  Metab Eng       Date:  2003-10       Impact factor: 9.783

Review 2.  Heading in the right direction: thermodynamics-based network analysis and pathway engineering.

Authors:  Meric Ataman; Vassily Hatzimanikatis
Journal:  Curr Opin Biotechnol       Date:  2015-09-16       Impact factor: 9.740

3.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.

Authors:  Scott A Becker; Adam M Feist; Monica L Mo; Gregory Hannum; Bernhard Ø Palsson; Markus J Herrgard
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

Review 4.  Advances in gap-filling genome-scale metabolic models and model-driven experiments lead to novel metabolic discoveries.

Authors:  Shu Pan; Jennifer L Reed
Journal:  Curr Opin Biotechnol       Date:  2017-12-23       Impact factor: 9.740

5.  Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

Authors:  A Kiparissides; V Hatzimanikatis
Journal:  Metab Eng       Date:  2016-11-12       Impact factor: 9.783

6.  Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

Authors:  Laurent Heirendt; Sylvain Arreckx; Thomas Pfau; Sebastián N Mendoza; Anne Richelle; Almut Heinken; Hulda S Haraldsdóttir; Jacek Wachowiak; Sarah M Keating; Vanja Vlasov; Stefania Magnusdóttir; Chiam Yu Ng; German Preciat; Alise Žagare; Siu H J Chan; Maike K Aurich; Catherine M Clancy; Jennifer Modamio; John T Sauls; Alberto Noronha; Aarash Bordbar; Benjamin Cousins; Diana C El Assal; Luis V Valcarcel; Iñigo Apaolaza; Susan Ghaderi; Masoud Ahookhosh; Marouen Ben Guebila; Andrejs Kostromins; Nicolas Sompairac; Hoai M Le; Ding Ma; Yuekai Sun; Lin Wang; James T Yurkovich; Miguel A P Oliveira; Phan T Vuong; Lemmer P El Assal; Inna Kuperstein; Andrei Zinovyev; H Scott Hinton; William A Bryant; Francisco J Aragón Artacho; Francisco J Planes; Egils Stalidzans; Alejandro Maass; Santosh Vempala; Michael Hucka; Michael A Saunders; Costas D Maranas; Nathan E Lewis; Thomas Sauter; Bernhard Ø Palsson; Ines Thiele; Ronan M T Fleming
Journal:  Nat Protoc       Date:  2019-03       Impact factor: 13.491

7.  BRENDA in 2019: a European ELIXIR core data resource.

Authors:  Lisa Jeske; Sandra Placzek; Ida Schomburg; Antje Chang; Dietmar Schomburg
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

8.  A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism.

Authors:  Hongzhong Lu; Feiran Li; Benjamín J Sánchez; Zhengming Zhu; Gang Li; Iván Domenzain; Simonas Marcišauskas; Petre Mihail Anton; Dimitra Lappa; Christian Lieven; Moritz Emanuel Beber; Nikolaus Sonnenschein; Eduard J Kerkhoven; Jens Nielsen
Journal:  Nat Commun       Date:  2019-08-08       Impact factor: 14.919

9.  Transcriptome analysis of Plasmodium berghei during exo-erythrocytic development.

Authors:  Reto Caldelari; Sunil Dogga; Marc W Schmid; Blandine Franke-Fayard; Chris J Janse; Dominique Soldati-Favre; Volker Heussler
Journal:  Malar J       Date:  2019-09-24       Impact factor: 2.979

10.  The MetaCyc database of metabolic pathways and enzymes.

Authors:  Ron Caspi; Richard Billington; Carol A Fulcher; Ingrid M Keseler; Anamika Kothari; Markus Krummenacker; Mario Latendresse; Peter E Midford; Quang Ong; Wai Kit Ong; Suzanne Paley; Pallavi Subhraveti; Peter D Karp
Journal:  Nucleic Acids Res       Date:  2018-01-04       Impact factor: 16.971

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