ArticleBiochemistry2013
Free energy rhythms in Saccharomyces cerevisiae: a dynamic perspective with implications for ribosomal biogenesis.
Article in Biochemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Transcriptome free energy can serve as a dynamic patient-specific biomarker in acute myeloid leukemia.NPJ systems biology and applications · 2024Article
- TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation.Entropy (Basel, Switzerland) · 2020Article
- Translational Components Contribute to Acclimation Responses to High Light, Heat, and Cold in Arabidopsis.iScience · 2020Article
- Statistical thermodynamics of transcription profiles in normal development and tumorigeneses in cohorts of patients.European biophysics journal : EBJ · 2015Article
- Surprisal analysis characterizes the free energy time course of cancer cells undergoing epithelial-to-mesenchymal transition.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- Computational surprisal analysis speeds-up genomic characterization of cancer processes.PloS one · 2014Article
- Thermodynamically inspired classifier for molecular phenotypes of health and disease.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- miRNA and mRNA cancer signatures determined by analysis of expression levels in large cohorts of patients.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
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Authors and funding
4 authors.
Funding
Abstract
To describe the time course of cellular systems, we integrate ideas from thermodynamics and information theory to discuss the work needed to change the state of the cell. The biological example analyzed is experimental microarray transcription level oscillations of yeast in the different phases as characterized by oxygen consumption. Surprisal analysis was applied to identify groups of transcripts that oscillate in concert and thereby to compute changes in free energy with time. Three dominant transcript groups were identified by surprisal analysis. The groups correspond to the respiratory, early, and late reductive phases. Genes involved in ribosome biogenesis peaked at the respiratory phase. The work to prepare the state is shown to be the sum of the contributions of these groups. We paid particular attention to work requirements during ribosomal building, and the correlation with ATP levels and dissolved oxygen. The suggestion that cells in the respiratory phase likely build ribosomes, an energy intensive process, in preparation for protein production during the S phase of the cell cycle is validated by an experiment. Surprisal analysis thereby provided a useful tool for determining the synchronization of transcription events and energetics in a cell in real time.
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Registered trials
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