KEY PUBLICATIONS

Alternative modes of client binding enable functional plasticity of Hsp70
Alireza Mashaghi et al. | Nature 539, 448-451 (2016) | pdf & DOI: 10.1038/nature20137
Stochasticity of metabolism and growth at the single-cell level
Daniel J. Kiviet et al. | Nature 514, 376-379 (2014) | pdf & DOI: 10.1038/nature13582
Reshaping of the conformational search of a protein by the chaperone trigger factor
Alireza Mashaghi et al. | Nature 500, 98-101 (2013) | pdf & DOI: 10.1038/nature12293
Tradeoffs and optimality in the evolution of gene regulation
Frank J. Poelwijk et al. | Cell 146, 462-470 (2011) | pdf & DOI:10.1016/j.cell.2011.06.035
Direct Observation of Chaperone-Induced Changes in a Protein Folding Pathway
Philipp Bechtluft, Ruud van Leeuwen et al. | Science 318:1458-1461 (2007) | pdf & DOI:10.1126/science.1144972
Empirical fitness landscapes reveal accessible evolutionary paths
Frank Poelwijk, Daan Kiviet et al. | Nature 445:383-386 (2007) | pdf & DOI:10.1038/nature05451
The bacteriophage phi29 portal motor can package DNA against a large internal force
Douglas E. Smith, Sander J. Tans et al. | Nature 413:748-52 (2001) | pdf & DOI:10.1038/35099581
Molecular transistors: Potential modulations along carbon nanotubes
Sander J. Tans, Cees Dekker. | Nature 404:834-35 (2000) | pdf & DOI:10.1038/35009026
Imaging electron wave functions of quantized energy levels in carbon nanotubes
Liesbeth C. Venema et al. | Science 283:52-55 (1999) | pdf & DOI:10.1126/science.283.5398.52
Electron-electron correlations in carbon nanotubes
Sander J. Tans et al. | Nature 394:761-64 (1998) | pdf & DOI:10.1038/29494
Room-temperature transistor based on a single carbon nanotube
Sander J. Tans, Alwin R. M. Verschueren & Cees Dekker | Nature 393:49-52 (1998) | pdf & DOI:10.1038/29954
Individual single-wall carbon nanotubes as quantum wires
Sander J. Tans et al. | Nature 386:474-77 (1997) | pdf & DOI:10.1038/386474a0
Fullerene 'crop circles'
Jie Liu et al. | Nature 385, 780-781 (1997) | pdf & DOI:10.1038/385780b0

Information-theoretic analysis of the directional influence between cellular processes

Lahiri, S.; Nghe, P.; Tans, S. J.; Rosinberg, M. L.; Lacoste, D.
Abstract:
Inferring the directionality of interactions between cellular processes is a major challenge in systems biology. Time-lagged correlations allow to discriminate between alternative models, but they still rely on assumed underlying interactions. Here, we use the transfer entropy (TE), an information-theoretic quantity that quantifies the directional influence between fluctuating variables in a model-free way. We present a theoretical approach to compute the transfer entropy, even when the noise has an extrinsic component or in the presence of feedback. We re-analyze the experimental data from Kiviet et al. (2014) where fluctuations in gene expression of metabolic enzymes and growth rate have been measured in single cells of E. coli. We confirm the formerly detected modes between growth and gene expression, while prescribing more stringent conditions on the structure of noise sources. We furthermore point out practical requirements in terms of length of time series and sampling time which must be satisfied in order to infer optimally transfer entropy from times series of fluctuations.
Year:
2017
Type of Publication:
Article
Journal:
PLoS ONE
Volume:
12
Number:
11
Pages:
e0187431
Note:
[PubMed Central:\href{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5679622}{PMC5679622}] [DOI:\href{https://dx.doi.org/10.1371/journal.pone.0187431}{10.1371/journal.pone.0187431}] [PubMed:\href{https://www.ncbi.nlm.nih.gov/pubmed/29121044}{29121044}]
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