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After Fukushima: The precautionary principle revisited
Wolfgang Huber
Verbum et Ecclesia , 2012,
Abstract: Etienne de Villiers, more than other theologians, elaborates on basic elements of a Christian ethics of responsibility. He distinguishes between retrospective and prospective responsibility. The prospective aspect attracted awareness after the nuclear accident in the Fukushima reactors on 11 March 2011. The question on how to respond in an ethically responsible manner to catastrophic risks was put back on the agenda. The article takes up this question and discusses the answer given in the international debate by the introduction of the ‘precautionary principle’. The principle is described with its background in the ‘heuristics of fear’, proposed by the philosopher Hans Jonas. Four criticisms are discussed in detail relating to the problems of scientific uncertainty, the burden of proof, the weight of damages and the perils of precaution. That leads to a reformulation of the precautionary principle as a concrete element within an ethics of responsibility.
Analyzing ChIP-chip Data Using Bioconductor
Joern Toedling ,Wolfgang Huber
PLOS Computational Biology , 2008, DOI: 10.1371/journal.pcbi.1000227
Differential expression analysis for sequence count data
Simon Anders, Wolfgang Huber
Genome Biology , 2010, DOI: 10.1186/gb-2010-11-10-r106
Abstract: High-throughput sequencing of DNA fragments is used in a range of quantitative assays. A common feature between these assays is that they sequence large amounts of DNA fragments that reflect, for example, a biological system's repertoire of RNA molecules (RNA-Seq [1,2]) or the DNA or RNA interaction regions of nucleotide binding molecules (ChIP-Seq [3], HITS-CLIP [4]). Typically, these reads are assigned to a class based on their mapping to a common region of the target genome, where each class represents a target transcript, in the case of RNA-Seq, or a binding region, in the case of ChIP-Seq. An important summary statistic is the number of reads in a class; for RNA-Seq, this read count has been found to be (to good approximation) linearly related to the abundance of the target transcript [2]. Interest lies in comparing read counts between different biological conditions. In the simplest case, the comparison is done separately, class by class. We will use the term gene synonymously to class, even though a class may also refer to, for example, a transcription factor binding site, or even a barcode [5].We would like to use statistical testing to decide whether, for a given gene, an observed difference in read counts is significant, that is, whether it is greater than what would be expected just due to natural random variation.If reads were independently sampled from a population with given, fixed fractions of genes, the read counts would follow a multinomial distribution, which can be approximated by the Poisson distribution.Consequently, the Poisson distribution has been used to test for differential expression [6,7]. The Poisson distribution has a single parameter, which is uniquely determined by its mean; its variance and all other properties follow from it; in particular, the variance is equal to the mean. However, it has been noted [1,8] that the assumption of Poisson distribution is too restrictive: it predicts smaller variations than what is seen in the data.
Comparing natural volume forms on GL_n
Huber Annette,Soergel Wolfgang
Mathematics , 2010,
Abstract: There are two natural choices for a volume form on the algebraic group Gl_n over Q: the first is the integral form (unique up to sign), the other is the product of the primitive classes in algebraic de Rham cohomology. We work out the explicit comparision factor between the two.
Ringo – an R/Bioconductor package for analyzing ChIP-chip readouts
Joern Toedling, Oleg Sklyar, Wolfgang Huber
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-221
Abstract: We present a free, open-source R package Ringo that facilitates the analysis of ChIP-chip experiments by providing functionality for data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions.Ringo integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It facilitates the construction of programmed analysis workflows, offers benefits in scalability, reproducibility and methodical scope of the analyses and opens up a broad selection of follow-up statistical and bioinformatic methods.Chromatin immunoprecipitation followed by DNA microarray hybridization (ChIP-chip) is a powerful technology for the systematic identification of genomic sites at which transcription factors bind or histone proteins bear post-translational modifications [1]. The raw microarray intensity readings themselves are not immediately useful to researchers, though. Through a number of bioinformatic analysis steps, one can obtain from the raw data a processed list of genomic sites and quantitative measures such as strength of evidence for a site, its extent, and estimates of relative occupancy.We provide a freely available, open-source software module Ringo for the import of the raw microarray data, their quality assessment, normalization, visualization, and for the detection and quantitation of ChIP-enriched regions. Its functionality covers the complete primary analysis for ChIP-chip tiling microarrays, especially those from the company NimbleGen. Ringo is integrated with the Bioconductor [2] project of bioinformatic extension packages to the R statistical software. This design makes it easy for users to construct sophisticated analyses approaches that also leverage other R/Bioconductor functionality, for example additional normalization methods from the affy [3] and oligo packages, or wavelet analysis methods from R's signal processing packages.Ringo is
Safety and Efficacy of Argatroban in the Management of Heparin-Induced Thrombocytopenia
Bernd Saugel, Roland M. Schmid and Wolfgang Huber
Clinical Medicine Insights: Blood Disorders , 2012, DOI: 10.4137/CMBD.S5118
Abstract: Heparin-induced thrombocytopenia (HIT) is a life-threatening adverse reaction to heparin therapy that is characterized by thrombocytopenia and an increased risk of venous and arterial thrombosis. According to guidelines, in patients with strongly suspected or confirmed HIT all sources of heparin have to be discontinued and an alternative, nonheparin anticoagulant for HIT treatment must immediately be started. For both the prophylaxis of thrombembolic events in HIT and the treatment of HIT with thrombosis the direct thrombin inhibitor argatroban is approved in the United States. The objective of this review is to describe the mechanism of action and the pharmacokinetic profile of argatroban, to characterize argatroban regarding its safety and therapeutic efficacy and to discuss its place in therapy in HIT.
Safety and Efficacy of Argatroban in the Management of Heparin-Induced Thrombocytopenia
Bernd Saugel,Rol,M. Schmid,Wolfgang Huber
Clinical Medicine Insights: Blood Disorders , 2011,
Is supra-ventricular arrhythmia a reason for the bad performance of the FlowTrac device?
Andreas Umgelter, Wolfgang Reindl, Roland M Schmid, Wolfgang Huber
Critical Care , 2007, DOI: 10.1186/cc5154
Abstract: We recently treated a septic patient with atrial fibrillation who, in addition to monitoring with the FlowTrac device, received a pulmonary artery catheter because of a suspicion of right ventricular failure. The patient was on pressure-controlled mechanical ventilation. We found no significant correlation between simultaneous measurements performed with the pulmonary artery catheter and measurements performed with the FlowTrac device (r = 0.297, P = 0.405). Bland-Altman analysis showed a mean bias of -0.43 l/min and limits of agreement of -4.5 and 3.6 l/min (Figure 1). This finding is in keeping with the results of a pilot study assessing the FloTrac system, which found worse correlations between waveform-based measurements of CO and thermodilution-derived CO for patients with atrial fibrillation, as compared to patients with sinus rhythm [2].In Sanders and colleagues' study, sinus rhythm is not mentioned among the prerequisites for measurements to be included in the analysis. We wonder whether the FloTrac device could provide meaningful data in patients with regular rhythms. Given the scarce and unfavourable data on the validity of this system, we believe that it should not be used at present, especially not in a medical intensive care unit setting where supra-ventricular arrhythmia is common.Michael Sander, Claudia D Spies, Achim Foer and Christian von HeymannWe read with interest that Umgelter and colleagues confirmed our data regarding the validity of the uncalibrated arterial waveform analysis cardiac output (COWave) in a medical intensive care unit patient. In our study we found a good correlation of aortic transpulmonary thermodilution cardiac output (COTranspulm) and pulmonary artery catheter thermodilution cardiac output (COPAC) measurements prior to, during, and after coronary artery bypass graft surgery surgery [1]. We found an overall mean bias and a limit opf agreement (LOA) of -0.1 l/min and from -1.8 to +1.6 l/min, respectively, for COPAC versus COTr
Genome-wide survey of post-meiotic segregation during yeast recombination
Eugenio Mancera, Richard Bourgon, Wolfgang Huber, Lars M Steinmetz
Genome Biology , 2011, DOI: 10.1186/gb-2011-12-4-r36
Abstract: By genotyping tens of thousands of genetic markers in yeast segregants and their clonal progeny, we analyzed post-meiotic segregation at a genome-wide scale. We show that post-meiotic segregation occurs in close to 10% of recombination events. Although the overall number of markers affected in a single meiosis is small, the rate of post-meiotic segregation is more than five orders of magnitude larger than the base substitution mutation rate. Post-meiotic segregation took place with equal relative frequency in crossovers and non-crossovers, and usually at the edges of gene conversion tracts. Furthermore, post-meiotic segregation tended to occur in markers that are isolated from other heterozygosities and preferentially at polymorphism types that are relatively uncommon in the yeast species.Overall, our survey reveals the genome-wide characteristics of post-meiotic segregation. The results show that post-meiotic segregation is widespread in meiotic recombination and could be a significant determinant of allelic inheritance and allele frequencies at the population level.In sexually reproducing organisms, homologous chromosomes exchange genetic information through meiotic recombination. This process, which occurs in most eukaryotes, is an important determinant of allelic variation [1,2]. Recombination is triggered by the formation of programmed double-strand breaks (DSBs), which are typically repaired using the homologous chromosome as a template. Meiotic DSB repair often produces regions of gene conversion, which may or may not be accompanied by a reciprocal exchange of homologous chromosomal arms, thereby producing crossovers (COs) and non-crossovers (NCOs), respectively [3]. The pairing of a single strand from one homolog with the complementary strand from the other produces heteroduplex DNA with mismatches at heterozygous positions. Repair of these mismatches results in either gene conversion or restoration of the original genotype. If the mismatches are not repaire
Analysis of cell-based RNAi screens
Michael Boutros, Lígia P Brás, Wolfgang Huber
Genome Biology , 2006, DOI: 10.1186/gb-2006-7-7-r66
Abstract: RNA interference (RNAi) is a conserved biological mechanism to silence gene expression on the level of individual transcripts. RNAi was discovered in Caenorhabditis elegans when Fire and Mello [1] observed that injecting long double-stranded (ds) RNAs into worms led to efficient silencing of homologous endogenous RNAs. Subsequent studies showed that the RNAi pathway is conserved in Drosophila and vertebrates, and can be used as a tool to downregulate the expression of genes in a sequence specific manner [2,3]. Long dsRNAs are commonly used in Drosophila and C. elegans. In mammalian cells, long dsRNAs induce an interferon response, and therefore short 21 mer RNA duplexes (small interfering RNAs [siRNAs]) are effective in silencing target mRNAs [4,5].Cell-based RNAi screens open new avenues for the systematic analysis of genomes. Traditionally, genetic screens by random mutagenesis have been successful in identifying and characterizing genes in model organisms that are required for specific biological processes [6]. These led to the discovery of many pathways that were later implicated in human disease. However, the identification of genes whose mutation leads to an altered phenotype can be cumbersome and slow. Rapid reverse genetics by RNAi allows the systematic screening of a whole genome whereby every single transcript is depleted by siRNAs or dsRNAs. Genes with unknown functions can then be classified according to their phenotype. The speed of reverse genetic screens using high-throughput technologies promises to accelerate significantly the functional characterization of genes [7]. RNAi screens have been successfully used in C. elegans to elucidate whole organism phenotypes and for cell-based assays in fly, mouse, and human cells [8-17]. Figure 1 outlines the main steps in cell-based high-throughput screening (HTS) experiments.The analysis of data sets generated by high-throughput phenotypic screens poses new methodological challenges. The richness of phenotypic
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