arXiv subjects

Morten Kloster

Publications and source records attributed to Morten Kloster.

5 recordsLinked to original sources

arXiv2004

Pattern formation within Escherichia coli: diffusion, membrane attachment, and self-interaction of MinD molecules

In E. coli, accurate cell division depends upon the oscillation of Min proteins from pole to pole. We provide a model for the polar localization of MinD based only on diffusion, a delay for nucleotide exchange, and different rates of attachment to the bare membrane and the occupied membrane. We derive analytically the probability density, and correspondingly the length scale, for MinD attachment zones. Our simple analytical model illustrates the processes giving rise to the observed localization of cellular MinD zones.

q-bio.SC↗

arXiv2004

Analysis of evolution through competitive selection

Recent studies of in vitro evolution of DNA via protein binding indicate that the evolution behavior is qualitatively different in different parameter regimes. I here present a general theory that is valid for a wide range of parameters, and which reproduces and extends previous results. Specifically, the mean-field theory of a general translation-invariant model can be reduced to the basic diffusion equation with a dynamic boundary condition. The simple analytical form yields both quantitatively accurate predictions and valuable insight into the principles involved. In particular, I introduce a cutoff criterion for finite populations that illustrates both of these qualities.

q-bio.PE↗

arXiv2004

Finding regulatory modules through large-scale gene-expression data analysis

The use of gene microchips has enabled a rapid accumulation of gene-expression data. One of the major challenges of analyzing this data is the diversity, in both size and signal strength, of the various modules in the gene regulatory networks of organisms. Based on the Iterative Signature Algorithm [Bergmann, S., Ihmels, J. and Barkai, N. (2002) Phys. Rev. E 67, 031902], we present an algorithm - the Progressive Iterative Signature Algorithm (PISA) - that, by sequentially eliminating modules, allows unsupervised identification of both large and small regulatory modules. We applied PISA to a large set of yeast gene-expression data, and, using the Gene Ontology annotation database as a reference, found that our algorithm is much better able to identify regulatory modules than methods based on high-throughput transcription-factor binding experiments or on comparative genomics.

q-bio.QM↗

arXiv2003

Simulation and analysis of in vitro DNA evolution

We study theoretically the in vitro evolution of a DNA sequence by binding to a transcription factor. Using a simple model of protein-DNA binding and available binding constants for the Mnt protein, we perform large-scale, realistic simulations of evolution starting from a single DNA sequence. We identify different parameter regimes characterized by distinct evolutionary behaviors. For each regime we find analytical estimates which agree well with simulation results. For small population sizes, the DNA evolutional path is a random walk on a smooth landscape. While for large population sizes, the evolution dynamics can be well described by a mean-field theory. We also study how the details of the DNA-protein interaction affect the evolution.

cond-mat↗

arXiv2000

Exact solution of stochastic directed sandpile model

We introduce and analytically solve a directed sandpile model with stochastic toppling rules. The model clearly belongs to a different universality class from its counterpart with deterministic toppling rules, previously solved by Dhar and Ramaswamy. The critical exponents are D_||=7/4, τ=10/7 in two dimensions and D_||=3/2, τ=4/3 in one dimension. The upper critical dimension of the model is three, at which the exponents apart from logarithmic corrections reach their mean-field values D_||=2, τ=3/2.

cond-mat.stat-mech↗