ReviewFrontiers in bioengineering and biotechnology2014
Metabolic network discovery by top-down and bottom-up approaches and paths for reconciliation.
Review in Frontiers in bioengineering and biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- FastKnock: an efficient next-generation approach to identify all knockout strategies for strain optimization.Microbial cell factories · 2024Article
- Article
- Free Amino Acid Alterations in Patients with Gynecological and Breast Cancer: A Review.Pharmaceuticals (Basel, Switzerland) · 2021Review
- Stoichiometric gene-to-reaction associations enhance model-driven analysis performance: Metabolic response to chronic exposure to Aldrin in prostate cancer.BMC genomics · 2019Article
- Article
- The best models of metabolism.Wiley interdisciplinary reviews. Systems biology and medicine · 2017Review
- A kidney-specific genome-scale metabolic network model for analyzing focal segmental glomerulosclerosis.Mammalian genome : official journal of the International Mammalian Genome Society · 2016Article
- Current advances in biomarkers for targeted therapy in triple-negative breast cancer.Breast cancer (Dove Medical Press) · 2016Review
- A review on computational systems biology of pathogen-host interactions.Frontiers in microbiology · 2015Review
- Editorial: Current Challenges in Modeling Cellular Metabolism.Frontiers in bioengineering and biotechnology · 2015Article
- Systems Medicine: The Application of Systems Biology Approaches for Modern Medical Research and Drug Development.Molecular biology international · 2015Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.