Special Issue "Metabolic Network Models"
A special issue of Metabolites (ISSN 2218-1989).
Deadline for manuscript submissions: closed (31 August 2012)
Dr. Kyongbum Lee
Department of Chemical and Biological Engineering, Tufts University, Room 142, 4 Colby Street, Medford, MA 02155, USA
Interests: adipose tissue metabolism; liver drug transformation; dynamic models of metabolic networks; targeted metabolomics
Network models have been instrumental in advancing quantitative knowledge of cellular metabolism by characterizing the systems-level features and properties that arise from the biochemical interactions between metabolites, enzymes and regulatory molecules. Network models are now widely used in both basic and applied studies, ranging from investigations on the evolutionary origins of hierarchical modularity in metabolism to design of synthetic pathways for the overproduction of commercially useful molecules. By exploiting parallel advances in genomics, proteomics and bioinformatics, significant progress has been achieved in modeling metabolic networks, especially in the reconstruction and characterization of whole cell metabolic networks.
Many challenges remain, however, in developing dynamic models capable of predicting the response of cellular metabolism to environmental perturbations or genetic modifications. Given the size and complexity of metabolic networks, new modeling approaches are needed to incorporate existing and new knowledge on regulation, account for uncertainty, and systematically construct an identifiable model whose parameters can be robustly estimated from data. Therefore, this special issue of Metabolites will be dedicated for publishing current advances on dynamic metabolic network models, multi-scale and multi-resolution models, transcriptional and allosteric regulation, integration with signaling and other biochemical networks, parameter estimation from metabolomics data, and modeling of noise and uncertainty.
Prof. Kyongbum Lee
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 300 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
- metabolic network
- dynamic model
- model reduction
- transcriptional regulation
- allosteric regulation
- metabolomics data
- parameter estimation
- network flexibility
- robust design
Metabolites 2012, 2(1), 221-241; doi:10.3390/metabo2010221
Received: 30 December 2011; in revised form: 8 February 2012 / Accepted: 10 February 2012 / Published: 27 February 2012| Download PDF Full-text (360 KB) | Download XML Full-text
Metabolites 2012, 2(1), 242-253; doi:10.3390/metabo2010242
Received: 30 January 2012; in revised form: 18 February 2012 / Accepted: 27 February 2012 / Published: 2 March 2012| Download PDF Full-text (371 KB) | Download XML Full-text
Review: Stoichiometry Based Steady-State Hepatic Flux Analysis: Computational and Experimental Aspects
Metabolites 2012, 2(1), 268-291; doi:10.3390/metabo2010268
Received: 15 February 2012; in revised form: 5 March 2012 / Accepted: 6 March 2012 / Published: 14 March 2012| Download PDF Full-text (247 KB) | Download XML Full-text
Review: Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory
Metabolites 2012, 2(3), 429-457; doi:10.3390/metabo2030429
Received: 24 May 2012; in revised form: 26 June 2012 / Accepted: 9 July 2012 / Published: 12 July 2012| Download PDF Full-text (428 KB) | Download XML Full-text
Metabolites 2012, 2(3), 632-647; doi:10.3390/metabo2030632
Received: 1 August 2012; in revised form: 28 August 2012 / Accepted: 12 September 2012 / Published: 24 September 2012| Download PDF Full-text (5037 KB) | Download XML Full-text |
Article: From Cycling Between Coupled Reactions to the Cross-Bridge Cycle: Mechanical Power Output as an Integral Part of Energy Metabolism
Metabolites 2012, 2(4), 667-700; doi:10.3390/metabo2040667
Received: 20 July 2012; in revised form: 7 September 2012 / Accepted: 24 September 2012 / Published: 8 October 2012| Download PDF Full-text (364 KB) | Download XML Full-text
Metabolites 2012, 2(4), 891-912; doi:10.3390/metabo2040891
Received: 14 September 2012; in revised form: 2 November 2012 / Accepted: 5 November 2012 / Published: 12 November 2012| Download PDF Full-text (558 KB) | Download XML Full-text |
Article: Metabolic Consequences of TGFb Stimulation in CulturedPrimary Mouse Hepatocytes Screened from Transcript Data with ModeScore
Metabolites 2012, 2(4), 983-1003; doi:10.3390/metabo2040983
Received: 29 August 2012; in revised form: 18 October 2012 / Accepted: 7 November 2012 / Published: 21 November 2012| Download PDF Full-text (1195 KB) | Download XML Full-text |
Metabolites 2012, 2(4), 1031-1059; doi:10.3390/metabo2041031
Received: 18 September 2012; in revised form: 30 October 2012 / Accepted: 31 October 2012 / Published: 21 November 2012| Download PDF Full-text (1583 KB) | Download XML Full-text
Metabolites 2013, 3(1), 1-23; doi:10.3390/metabo3010001
Received: 8 October 2012; in revised form: 18 December 2012 / Accepted: 31 December 2012 / Published: 8 January 2013| Download PDF Full-text (904 KB) | Download XML Full-text |
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Development of Metabolic Indicators of Hypermetabolism: VLDL and Acetoacetate Are Highly Correlated to Severity of Burn Injury in Rats
Authors: Maria-Louisa Izamis1, Korkut Uygun1, Nripen S. Sharma2 Basak Uygun1, Martin L. Yarmush1,2 and Francois Berthiaume2
Affiliations: 1 Center for Engineering in Medicine, Massachusetts General Hospital, Harvard Medical School, and the Shriners Hospitals for Children, Boston, MA, USA; E-Mail: firstname.lastname@example.org
2 Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, USA
Abstract: Hypermetabolism is a significant sequela to severe trauma such as burns, as well as critical illnesses such as cancer. It persists in parallel to, or beyond, the original pathology for many months as an often-fatal comorbidity. Currently, diagnosis is based solely on clinical observations of increased energy expenditure, severe muscle wasting and progressive organ dysfunction. In a rat model of burn injury-induced hypermetabolism, we utilized data mining approaches to identify the metabolic variables that strongly correlate to the level of hypermetabolism. A clustering based algorithm to identify the minimum number of variables necessary was introduced, and applied to develop a regression model of burn injury level. As a result, a neural network model which employs VLDL and acetoacetate levels was demonstrated to predict the level of hypermetabolism with 76% accuracy in the rat model. The physiological importance of the identified variables in the context of hypermetabolism, and necessary steps in extension of this preliminary model to a clinically utilizable index of hypermetabolism are outlined.
Keywords: Hypermetabolism, metabonomics, flux analysis, index of hypermetabolism
Last update: 12 October 2012