@misc{BenteleSaffertRauscheretal.2013,
  author    = {Bentele, Kajetan and Saffert, Paul and Rauscher, Robert and Ignatova, Zoya and Bluethgen, Nils},
  title     = {Efficient translation initiation dictates codon usage at gene start},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {912},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-44133},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441337},
  pages     = {12},
  year      = {2013},
  abstract  = {The genetic code is degenerate; thus, protein evolution does not uniquely determine the coding sequence. One of the puzzles in evolutionary genetics is therefore to uncover evolutionary driving forces that result in specific codon choice. In many bacteria, the first 5-10 codons of protein-coding genes are often codons that are less frequently used in the rest of the genome, an effect that has been argued to arise from selection for slowed early elongation to reduce ribosome traffic jams. However, genome analysis across many species has demonstrated that the region shows reduced mRNA folding consistent with pressure for efficient translation initiation. This raises the possibility that unusual codon usage is a side effect of selection for reduced mRNA structure. Here we discriminate between these two competing hypotheses, and show that in bacteria selection favours codons that reduce mRNA folding around the translation start, regardless of whether these codons are frequent or rare. Experiments confirm that primarily mRNA structure, and not codon usage, at the beginning of genes determines the translation rate.},
  language  = {en}
}
@misc{ThomasMatuschekGrima2013,
  author    = {Thomas, Philipp and Matuschek, Hannes and Grima, Ramon},
  title     = {How reliable is the linear noise approximation of gene regulatory networks?},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {876},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43502},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-435028},
  pages     = {17},
  year      = {2013},
  abstract  = {Background: The linear noise approximation (LNA) is commonly used to predict how noise is regulated and exploited at the cellular level. These predictions are exact for reaction networks composed exclusively of first order reactions or for networks involving bimolecular reactions and large numbers of molecules. It is however well known that gene regulation involves bimolecular interactions with molecule numbers as small as a single copy of a particular gene. It is therefore questionable how reliable are the LNA predictions for these systems. Results: We implement in the software package intrinsic Noise Analyzer (iNA), a system size expansion based method which calculates the mean concentrations and the variances of the fluctuations to an order of accuracy higher than the LNA. We then use iNA to explore the parametric dependence of the Fano factors and of the coefficients of variation of the mRNA and protein fluctuations in models of genetic networks involving nonlinear protein degradation, post-transcriptional, post-translational and negative feedback regulation. We find that the LNA can significantly underestimate the amplitude and period of noise-induced oscillations in genetic oscillators. We also identify cases where the LNA predicts that noise levels can be optimized by tuning a bimolecular rate constant whereas our method shows that no such regulation is possible. All our results are confirmed by stochastic simulations. Conclusion: The software iNA allows the investigation of parameter regimes where the LNA fares well and where it does not. We have shown that the parametric dependence of the coefficients of variation and Fano factors for common gene regulatory networks is better described by including terms of higher order than LNA in the system size expansion. This analysis is considerably faster than stochastic simulations due to the extensive ensemble averaging needed to obtain statistically meaningful results. Hence iNA is well suited for performing computationally efficient and quantitative studies of intrinsic noise in gene regulatory networks.},
  language  = {en}
}
@misc{VanBelProostVanNesteetal.2013,
  author    = {Van Bel, Michiel and Proost, Sebastian and Van Neste, Christophe and Deforce, Dieter and Van de Peer, Yves and Vandepoele, Klaas},
  title     = {TRAPID},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {900},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43640},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-436409},
  pages     = {12},
  year      = {2013},
  abstract  = {Transcriptome analysis through next-generation sequencing technologies allows the generation of detailed gene catalogs for non-model species, at the cost of new challenges with regards to computational requirements and bioinformatics expertise. Here, we present TRAPID, an online tool for the fast and efficient processing of assembled RNA-Seq transcriptome data, developed to mitigate these challenges. TRAPID offers high-throughput open reading frame detection, frameshift correction and includes a functional, comparative and phylogenetic toolbox, making use of 175 reference proteomes. Benchmarking and comparison against state-of-the-art transcript analysis tools reveals the efficiency and unique features of the TRAPID system. TRAPID is freely available at http://bioinformatics.psb.ugent.be/webtools/trapid/.},
  language  = {en}
}