Saarland University

About: Saarland University is a education organization based out in Saarbrücken, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 19555 authors who have published 39678 publications receiving 1109295 citations. The organization is also known as: University of the Saarland & Universität des Saarlandes.

antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

Abstract: Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.

Evidence for a lack of DNA double-strand break repair in human cells exposed to very low x-ray doses

Abstract: DNA double-strand breaks (DSBs) are generally accepted to be the most biologically significant lesion by which ionizing radiation causes cancer and hereditary disease. However, no information on the induction and processing of DSBs after physiologically relevant radiation doses is available. Many of the methods used to measure DSB repair inadvertently introduce this form of damage as part of the methodology, and hence are limited in their sensitivity. Here we present evidence that foci of γ-H2AX (a phosphorylated histone), detected by immunofluorescence, are quantitatively the same as DSBs and are capable of quantifying the repair of individual DSBs. This finding allows the investigation of DSB repair after radiation doses as low as 1 mGy, an improvement by several orders of magnitude over current methods. Surprisingly, DSBs induced in cultures of nondividing primary human fibroblasts by very low radiation doses (≈1 mGy) remain unrepaired for many days, in strong contrast to efficient DSB repair that is observed at higher doses. However, the level of DSBs in irradiated cultures decreases to that of unirradiated cell cultures if the cells are allowed to proliferate after irradiation, and we present evidence that this effect may be caused by an elimination of the cells carrying unrepaired DSBs. The results presented are in contrast to current models of risk assessment that assume that cellular responses are equally efficient at low and high doses, and provide the opportunity to employ γ-H2AX foci formation as a direct biomarker for human exposure to low quantities of ionizing radiation.

TnT - A Statistical Part-of-Speech Tagger

Abstract: Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison has even shown that TnT performs significantly better for the tested corpora. We describe the basic model of TnT, the techniques used for smoothing and for handling unknown words. Furthermore, we present evaluations on two corpora.