929 research outputs found
Automatische Auswertung von Mikroarraybildern
No full textKatzer M, Kummert F, Sagerer G. Automatische Auswertung von Mikroarraybildern. In: Workshop Bildverarbeitung für die Medizin. Leipzig; 2002.Wir beschreiben ein Verfahren, das die automatische Segmentierung von Mikroarraybildern in unkalibrierten Umgebungen ermöglicht. Insbesondere behandeln wir die als Adressierung oder in der englischsprachigen Literatur als "Gridding" bezeichnete Segmentierung der Messpunktgitter. Wir verwenden klassische Regionensegmentierung, Häufigkeitsverteilungen der Abstäande zum nächsten Nachbarn, Achsenprojektionen und optimierte Segmentierung durch dynamische Programmierung. Das Verfahren ist für die automatisierte Segmentierung von Bildserien aus umfangreicheren Experimenten besonders geeignet
Automatic segmentation of microarray images
No full textKatzer M. Automatisches Segmentieren von Mikroarraybildern. Bielefeld (Germany): Bielefeld University; 2003.Gene expression experiments using microarray hybridisation have become a widespread method in scientific as well as industrial research. Analysis of microarray images is a bottleneck of array data analysis pipelines, as it is usually performed using interactive computer programs. Apart from practical concerns, automation of microarray gridding and feature segmentation is most important to achieve constant data quality, which is a precondition to the integration of different expression data sets. Therefore, image processing methods that are applicable regardless of the employed array design and laboratory protocols are highly useful.
In this work a Markov random field (MRF) based approach to high level grid segmentation is proposed, which is robust to common problems encountered with array images and does not require calibration. The MRF framework allows to separate the heuristic modeling of spot grid layouts from the segmentation algorithm itself.
Also proposed is an active contour method for spot signal segmentation. Active contour models describe objects in images by local properties of their boundaries and thereby enable robust segmentation of irregularly shaped array spots. The traditional active contour model must be generalized for successful application to microarray spot segmentation.
The methods proposed in this work are implemented in the AIM (Automatic Image processing for Microarray experiments) system. The results of the system evaluation using a sample of 23 different types of microarray images show the usefulness of the MRF grid segmentation approach. The evaluation of quantitative image analysis is much more difficult since it seems hardly possible to produce authoritative as well as biologically relevant calibration data. The quantitative analysis of array spots using the active contour model reproduces the results of a fine tuned interactive image analysis with a commercial image processing tool (Imagene). Active contour segmentation is less sensitive to variations of grid segmentation than the well known Mann-Whitney segmentation
mPER1‐mediated nuclear export of mCRY1/2 is an important element in establishing circadian rhythm
No full textReceptor-mediated nucleocytoplasmic transport of clock proteins is an important, conserved element of the core mechanism for circadian rhythmicity. A systematic analysis of the nuclear export characteristics for the different murine period (mPER) and cryptochrome (mCRY) proteins using Xenopus oocytes as an experimental system demonstrates that all three mPER proteins, but neither mCRY1 nor mCRY2, are exported if injected individually. However, nuclear injection of heterodimeric complexes that contain combinations of mPER and mCRY proteins shows that mPER1 serves as an export adaptor for mCRY1 and mCRY2. Functional analysis of dominant-negative mPER1 variants designed either to sequester mPER3 to the cytoplasm or to inhibit nuclear export of mCRY1/2 in synchronized, stably transfected fibroblasts suggests that mPER1-mediated export of mCRY1/2 defines an important new element of the core clock machinery in vertebrates
Mauersegler weiter Wege. Mathias Enard: Kompass
No full textAnalysis of the peculiar scientific narrative in the novel of the Prix-Goncourt winning author Mathias Enard
Xenopus Dead end mRNA is a localized maternal determinant that serves a conserved function in germ cell development
No full textAbstractGerm plasm formation is considered to define the first step in germ cell development. Xenopus Dead end represents a germ plasm specific transcript that is homologous to the previously characterized zebrafish dead end, which is required for germ cell migration and survival. XDead end mRNA localizes to the vegetal pole of Xenopus oocytes; in contrast to all other known germ plasm associated transcripts in Xenopus, XDead end is transported via the late transport pathway, suggesting a different mode of germ plasm restriction. Vegetal localization in the oocyte is achieved via a localization element mapping to a 251 nucleotide element in the 3′-UTR. This RNA sequence binds to a set of proteins characteristic for the late localization pathway and to one additional protein of 38 kDa. Inhibition of XDead end translation in Xenopus embryos results in a loss of primordial germ cells at tadpole stages of development. Early specification events do not seem to be affected, but the primordial germ cells fail to migrate dorsally and eventually disappear. This phenotype is very similar to what has been observed in the zebrafish, indicating that the role of XDead end in germ cell development has been conserved in evolution
A Markov Random Field Model of Microarray Gridding
No full textKatzer M, Kummert F, Sagerer G. A Markov Random Field Model of Microarray Gridding. In: Proc. 18th ACM Symposium on Applied Computing. 2003.DNA microarray hybridisation is a popular high throughput technique in academic as well as industrial functional genomics research. In this paper we present a new approach to automatic grid segmentation of the raw fluorescence microarray images by Markov Random Field (MRF) techniques. The main objectives are applicability to various types of array designs and robustness to the typical problems encountered in microarray images, which are contaminations and weak signal. We briefly introduce microarray technology and give some background on MRFs. Our MRF model of microarray gridding is designed to integrate different application specific constraints and heuristic criteria into a robust and flexible segmentation algorithm. We show how to compute the model components efficiently and state our deterministic MRF energy minimization algorithm that was derived from the ’Highest Confidence First’ algorithm by Chou et al. Since MRF segmentation may fail due to the properties of the data and the minimization algorithm, we use supplied or estimated print layouts to validate results. Finally we present results of tests on several series of microarray images from different sources, some of them test sets published with other microarray gridding software. Our MRF grid segmentation requires weaker assumptions about the array printing process than previously published methods and produces excellent results on many real datasets. An implementation of the described methods is available upon request from the authors
Les commissions électorales en Afrique de l'Ouest
No full text[author: Mathias Hounkpe ; Ismaila Madior Fall]Electronic ed.: Abuja ; Bonn : FES, 201
Methods for automatic microarray image segmentation
No full textKatzer M, Kummert F, Sagerer G. Methods for automatic microarray image segmentation. IEEE Transactions on Nanobioscience. 2003;2(4):202-214.This paper describes image processing methods for automatic spotted microarray image analysis. Automatic gridding is important to achieve constant data quality and is, therefore, especially interesting for large-scale experiments as well as for integration of microarray expression data from different sources. We propose a Markov random field (MRF) based approach to high-level grid segmentation, which is robust to common problems encountered with array images and does not require calibration. We also propose an active contour method for single-spot segmentation. Active contour models describe objects in images by properties of their boundaries. Both MRFs and active contour models have been used in various other computer vision applications. The traditional active contour model must be generalized for successful application to microarray spot segmentation. Our active contour model is employed for spot detection in the MRF score functions as well as for spot signal segmentation in quantitative array image analysis. An evaluation using several image series from different sources shows the robustness of our methods
Robust Automatic Microarray Image Analysis
No full textKatzer M, Kummert F, Sagerer G. Robust Automatic Microarray Image Analysis. In: Proceedings of the International Conference on Bioinformatics:North-South Networking. Bangkok; 2002.Parallel expression analysis of many genes by microarray hybridisation is one of the most promising techniques in functional genomics. The method has been successfully applied many times in medical and biological research. Our work is about automatic methods for the first stages of a microarray data analysis pipeline. Expression analysis by microarray hybridisation is a high throughput technique. While interactive, semi-automatic software is still frequently used for the analysis of scanned array images, it is highly desirable to have automatic procedures which yield better repeatability and constant quality of the expression data for later cluster analyses. Automatic methods must handle noise and the frequently occurring contaminations on microarrays. In large scale microarray experiments, automatic image analysis can save substantial amounts of work. We describe robust image processing methods that find the printed grids of spots in the scanned microarray images without the requirement of special guide spots or specially calibrated equipment. Processing of many slides from the same print batch helps to minimize the need for human intervention. We derive our method of spot intensity ratio computation from the biochemical model of differential gene expression experiments and finally discuss how different ratio computation methods can be compared. We compare results of our method to results of manual analyses using the well-known Scanalyze (M. Eisen, LBNL Berkeley) as well as recently published methods (Brown et al. (2001), PNAS 92, 8944-8949). Our automatic method yields comparable or even more accurate results than standard methods under poor hybridisation and scan quality conditions
Paul Bourget, écrivain engagé
No full textPaul Bourget, A committed writer, Yehoshua Mathias.
In the France of the early twentieth century, Paul Bourget's figure is that of a successful novelist who became gradually a «committed author». A monarchist, deeply conservative, passionate defender of religion and the family as the vital bases of the social order, he thus became the bard of the bourgeois ethic faced with the destabilization of modernity.Mathias Yehoshua. Paul Bourget, écrivain engagé. In: Vingtième Siècle, revue d'histoire, n°45, janvier-mars 1995. pp. 14-29
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