University of Freiburg

About: University of Freiburg is a education organization based out in Freiburg, Baden-Württemberg, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 41992 authors who have published 77296 publications receiving 2896269 citations. The organization is also known as: alberto-ludoviciana & Albert-Ludwigs-Universität Freiburg.

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Abstract: In this paper we present a method for learning a discriminative classifier from unlabeled or partially labeled data. Our approach is based on an objective function that trades-off mutual information between observed examples and their predicted categorical class distribution, against robustness of the classifier to an adversarial generative model. The resulting algorithm can either be interpreted as a natural generalization of the generative adversarial networks (GAN) framework or as an extension of the regularized information maximization (RIM) framework to robust classification against an optimal adversary. We empirically evaluate our method - which we dub categorical generative adversarial networks (or CatGAN) - on synthetic data as well as on challenging image classification tasks, demonstrating the robustness of the learned classifiers. We further qualitatively assess the fidelity of samples generated by the adversarial generator that is learned alongside the discriminative classifier, and identify links between the CatGAN objective and discriminative clustering algorithms (such as RIM).

IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions

Abstract: Motivation: During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand. Many existing target prediction programs neglect the accessibility of target sites and the existence of a seed, while other approaches are either specialized to certain types of RNAs or too slow for genome-wide searches. Results: We introduce INTARNA, a new general and fast approach to the prediction of RNA–RNA interactions incorporating accessibility of target sites as well as the existence of a user-definable seed. We successfully applied INTARNA to the prediction of bacterial sRNA targets and determined the exact locations of the interactions with a higher accuracy than competing programs. Availability: http://www.bioinf.uni-freiburg.de/Software/ Contact: IntaRNA@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Patterns and Implications of Gene Gain and Loss in the Evolution of Prochlorococcus

Abstract: Prochlorococcus is a marine cyanobacterium that numerically dominates the mid-latitude oceans and is the smallest known oxygenic phototroph. Numerous isolates from diverse areas of the world’s oceans have been studied and shown to be physiologically and genetically distinct. All isolates described thus far can be assigned to either a tightly clustered high-light (HL)-adapted clade, or a more divergent low-light (LL)-adapted group. The 16S rRNA sequences of the entire Prochlorococcus group differ by at most 3%, and the four initially published genomes revealed patterns of genetic differentiation that help explain physiological differences among the isolates. Here we describe the genomes of eight newly sequenced isolates and combine them with the first four genomes for a comprehensive analysis of the core (shared by all isolates) and flexible genes of the Prochlorococcus group, and the patterns of loss and gain of the flexible genes over the course of evolution. There are 1,273 genes that represent the core shared by all 12 genomes. They are apparently sufficient, according to metabolic reconstruction, to encode a functional cell. We describe a phylogeny for all 12 isolates by subjecting their complete proteomes to three different phylogenetic analyses. For each non-core gene, we used a maximum parsimony method to estimate which ancestor likely first acquired or lost each gene. Many of the genetic differences among isolates, especially for genes involved in outer membrane synthesis and nutrient transport, are found within the same clade. Nevertheless, we identified some genes defining HL and LL ecotypes, and clades within these broad ecotypes, helping to demonstrate the basis of HL and LL adaptations in Prochlorococcus. Furthermore, our estimates of gene gain events allow us to identify highly variable genomic islands that are not apparent through simple pairwise comparisons. These results emphasize the functional roles, especially those connected to outer membrane synthesis and transport that dominate the flexible genome and set it apart from the core. Besides identifying islands and demonstrating their role throughout the history of Prochlorococcus, reconstruction of past gene gains and losses shows that much of the variability exists at the ‘‘leaves of the tree,’’ between the most closely related strains. Finally, the identification of core and flexible genes from this 12-genome comparison is largely consistent with the relative frequency of Prochlorococcus genes found in global ocean metagenomic databases, further closing the gap between our understanding of these organisms in the lab and the wild.

Irregular variations in the melting point of size-selected atomic clusters

Abstract: Small particles have a lower melting point than bulk material1. The physical cause lies in the fact that small particles have a higher proportion of surface atoms than larger particles—surface atoms have fewer nearest neighbours and are thus more weakly bound and less constrained in their thermal motion2,3 than atoms in the body of a material. The reduction in the melting point has been studied extensively for small particles or clusters on supporting surfaces. One typically observes a linear reduction of the melting point as a function of the inverse cluster radius2,4,5. Recently, the melting point of a very small cluster, containing exactly 139 atoms, has been measured in a vacuum using a technique in which the cluster acts as its own nanometre-scale calorimeter6,7. Here we use the same technique to study ionized sodium clusters containing 70 to 200 atoms. The melting points of these clusters are on average 33% (120 K) lower than the bulk material; furthermore, we observe surprisingly large variations in the melting point (of ±30 K) with changing cluster size, rather than any gradual trend. These variations cannot yet be fully explained theoretically.