Literature DB >> 25730289

Reconstruction of genome-scale human metabolic models using omics data.

Jae Yong Ryu1, Hyun Uk Kim, Sang Yup Lee.   

Abstract

The impact of genome-scale human metabolic models on human systems biology and medical sciences is becoming greater, thanks to increasing volumes of model building platforms and publicly available omics data. The genome-scale human metabolic models started with Recon 1 in 2007, and have since been used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic models. Integration of tissue/cell type-specific omics data with the generic human metabolic models is the key step, and we discuss omics data and their integration methods to achieve this task. The initial version of the tissue/cell type-specific human metabolic models can further be computationally refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model.

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Year:  2015        PMID: 25730289     DOI: 10.1039/c5ib00002e

Source DB:  PubMed          Journal:  Integr Biol (Camb)        ISSN: 1757-9694            Impact factor:   2.192


  18 in total

1.  Reconstruction and validation of a constraint-based metabolic network model for bone marrow-derived mesenchymal stem cells.

Authors:  H Fouladiha; S-A Marashi; M A Shokrgozar
Journal:  Cell Prolif       Date:  2015-07-01       Impact factor: 6.831

2.  A kidney-specific genome-scale metabolic network model for analyzing focal segmental glomerulosclerosis.

Authors:  Salma Sohrabi-Jahromi; Sayed-Amir Marashi; Shiva Kalantari
Journal:  Mamm Genome       Date:  2016-02-29       Impact factor: 2.957

3.  Framework and resource for more than 11,000 gene-transcript-protein-reaction associations in human metabolism.

Authors:  Jae Yong Ryu; Hyun Uk Kim; Sang Yup Lee
Journal:  Proc Natl Acad Sci U S A       Date:  2017-10-24       Impact factor: 11.205

4.  Machine learning-guided evaluation of extraction and simulation methods for cancer patient-specific metabolic models.

Authors:  Sang Mi Lee; GaRyoung Lee; Hyun Uk Kim
Journal:  Comput Struct Biotechnol J       Date:  2022-06-15       Impact factor: 6.155

5.  A pipeline for the reconstruction and evaluation of context-specific human metabolic models at a large-scale.

Authors:  Vítor Vieira; Jorge Ferreira; Miguel Rocha
Journal:  PLoS Comput Biol       Date:  2022-06-24       Impact factor: 4.779

Review 6.  Personalized Cardiovascular Disease Prediction and Treatment-A Review of Existing Strategies and Novel Systems Medicine Tools.

Authors:  Elias Björnson; Jan Borén; Adil Mardinoglu
Journal:  Front Physiol       Date:  2016-01-26       Impact factor: 4.566

Review 7.  Constraint Based Modeling Going Multicellular.

Authors:  Patricia do Rosario Martins Conde; Thomas Sauter; Thomas Pfau
Journal:  Front Mol Biosci       Date:  2016-02-10

8.  Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies.

Authors:  Alan J Mueller; Mandy J Peffers; Carole J Proctor; Peter D Clegg
Journal:  J Orthop Res       Date:  2017-04-24       Impact factor: 3.494

9.  Reconstruction of Tissue-Specific Metabolic Networks Using CORDA.

Authors:  André Schultz; Amina A Qutub
Journal:  PLoS Comput Biol       Date:  2016-03-04       Impact factor: 4.475

10.  Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms.

Authors:  Maria P Pacheco; Thomas Pfau; Thomas Sauter
Journal:  Front Physiol       Date:  2016-01-22       Impact factor: 4.566

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