ReviewWiley interdisciplinary reviews. Systems biology and medicine
Computational approaches for understanding energy metabolism.
Review in Wiley interdisciplinary reviews. Systems biology and medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Multi-scale computational study of the Warburg effect, reverse Warburg effect and glutamine addiction in solid tumors.PLoS computational biology · 2018Article
- Understanding metabolism with flux analysis: From theory to application.Metabolic engineering · 2017Review
- Metabolomics: A Primer.Trends in biochemical sciences · 2017Review
- A Flux Balance of Glucose Metabolism Clarifies the Requirements of the Warburg Effect.Biophysical journal · 2016Article
- Mitochondrial Respiration Chain Enzymatic Activities in the Human Brain: Methodological Implications for Tissue Sampling and Storage.Neurochemical research · 2016Article
- Bonded Cumomer Analysis of Human Melanoma Metabolism Monitored by 13C NMR Spectroscopy of Perfused Tumor Cells.The Journal of biological chemistry · 2016Article
- (13)C MRS and LC-MS Flux Analysis of Tumor Intermediary Metabolism.Frontiers in oncology · 2016Article
- A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data.Computational biology and chemistry · 2015Article
- Redox control of glutamine utilization in cancer.Cell death & disease · 2014Review
- Quantitative determinants of aerobic glycolysis identify flux through the enzyme GAPDH as a limiting step.eLife · 2014Article
- Systems biology of host-microbe metabolomics.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
There has been a surge of interest in understanding the regulation of metabolic networks involved in disease in recent years. Quantitative models are increasingly being used to interrogate the metabolic pathways that are contained within this complex disease biology. At the core of this effort is the mathematical modeling of central carbon metabolism involving glycolysis and the citric acid cycle (referred to as energy metabolism). Here, we discuss several approaches used to quantitatively model metabolic pathways relating to energy metabolism and discuss their formalisms, successes, and limitations.
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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.