Central projection of auditory receptors in the prothoracic ganglion of the bushcricket Psorodonotus illyricus (tettigoniidae): Computer-aided analysis of the end branch pattern

The projection patterns of morphologically and functionally identified auditory and auditory-vibratory receptor cells of receptor organs (the crista acustica and the intermediate organ) in the foreleg of the tettigoniid Psorodonotus illyricus, were investigated with combined recording and staining techniques, and subsequent histological examination and morphometric measurements. With the application of a computer program (AutoCAD), three-dimensional reconstructions of the axon end branches of receptor cells within the neuropile of the anterior Ring Tract (aRT) were made, in order to determine, the entire shape of each, the pattern and density of the end branches, and the positions of the target areas within the auditory neuropile. Clear differences for different functional types of receptors were found. 1994 John Wiley & Sons, Inc.     

Detection and correction of probe-level artefacts on microarrays

ABSTRACT: BACKGROUND: A recent large-scale analysis of Gene Expression Omnibus (GEO) data found frequent evidence for spatial defects in a substantial fraction of Affymetrix microarrays in the GEO. Nevertheless, in contrast to quality assessment, artefact detection is not widely used in standard gene expression analysis pipelines. Furthermore, although approaches have been proposed to detect diverse types of spatial noise on arrays, the correction of these artefacts is mostly left to either summarization methods or the corresponding arrays are completely discarded. RESULTS: We show that state-of-the-art robust summarization procedures are vulnerable to artefacts on arrays and cannot appropriately correct for these. To address this problem, we present a simple approach to detect artefacts with high recall and precision, which we further improve by taking into account the spatial layout of arrays. Finally, we propose two correction methods for these artefacts that either substitute values of defective probes using probeset information or filter corrupted probes. We show that our approach can identify and correct defective probe measurements appropriately and outperforms existing tools. CONCLUSIONS: While summarization is insufficient to correct for defective probes, this problem can be addressed in a straightforward way by the methods we present for identification and correction of defective probes. As these methods output CEL files with corrected probe values that serve as input to standard normalization and summarization procedures, they can be easily integrated into existing microarray analysis pipelines as an additional pre-processing step. An R package is freely available from http://www.bio.ifi.lmu.de/artefact-correction.     

Influence of degree correlations on network structure and stability in protein-protein interaction networks

Background  

The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI) network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs.