Theoretical

Localization error calculations

Biological data is inherently noisy. On top of the noise generated by stochastical chemical processes, there are errors in the measurements themself. Knowing the precision by which we can identify, e.g., the location of a molecule is important to make a correct interpretation of the data. To this end, we have developed methods to determine the localization precision and, in turn, the downstream analysis of molecular localization data.

Selective charging of tRNA

The theory for selective charging of tRNA (Elf et al. Science 2003) explains how the genetic code is used under amino acid limitation. The theory has now been tested in a number of experimental studies (EMBO rep, 2005, EMBO rep, 2005 JMB, 2005).

Generalization of zero order kinetics

The generalization of zero order kinetics to several dimensions (Elf et al. Biophys J, 2003, Genome Res, 2003), that implies that the substrate pools to multi substrate reactions can display huge stochastic fluctuations and ultra sensitivity because the increase in one pool is compensated by the decrease in another so that the overall flux is conserved. The observation has consequences for the flux of amino acids in protein synthesis (Biophys J, 2005).

Time delays in gene regulation

New theoretical methods to analyze stochastic processes makes it possible to investigate the consequences of time delays in gene regulatory control circuits (Grönlund et al. PNAS 2009, Nature Communications 2010)

The next subvolume method

The Next Subvolume Method (Elf and Ehrenberg, IEE Systems Biology, 2004) is a very efficient method for simulating stochastic reaction diffusion kinetics. The algorithm is for instance implemented in our MesoRD software (Hattne et al. Bioinformatics, 2005, Fange et al. PNAS 2010).