Publications

1004 Publications visible to you, out of a total of 1004

Abstract (Expand)

The data produced by high-throughput bioanalytics is usually given as a feature matrix of dimension N x M (see Figure 1) where N is the number of features measured per sample and M is the number of samples referring, e.g., to different treatments, time points or individuals. As a convention, each row of the matrix will be termed profile of the respective feature. The columns on the other hand will be termed states referring to each of the conditions studied. In general, the number of features can range from several thousands to millions, depending on the experimental screening technique used. Typically, this number largely exceeds the number of states studied, i.e. N>>M. SOM machine learning aims at reducing the number of relevant features by grouping the input data into clusters of appropriate size, and thus to transform the matrix of input data into a matrix of so-called meta-data with a reduced number of meta-features, K<<N (Figure 1a and b). In other words, SOM aims at mapping the space of the high-dimensional input data onto meta-data space of reduced dimensionality.

Authors: Hans Binder, Henry Löffler-Wirth

Date Published: 2015

Publication Type: Not specified

Abstract (Expand)

Xenograft tumor models are widely studied in cancer research. Our aim was to establish and apply a model for aggressive CD20-positive B-cell non-Hodgkin lymphomas, enabling us to monitor tumor growth and shrinkage in a noninvasive manner. By stably transfecting a luciferase expression vector, we created two bioluminescent human non-Hodgkin lymphoma cell lines, Jeko1(luci) and OCI-Ly3(luci), that are CD20 positive, a prerequisite to studying rituximab, a chimeric anti-CD20 antibody. To investigate the therapy response in vivo, we established a disseminated xenograft tumor model injecting these cell lines in NOD/SCID mice. We observed a close correlation of bioluminescence intensity and tumor burden, allowing us to monitor therapy response in the living animal. Cyclophosphamide reduced tumor burden in mice injected with either cell line in a dose-dependent manner. Rituximab alone was effective in OCI-Ly3(luci)-injected mice and acted additively in combination with cyclophosphamide. In contrast, it improved the therapeutic outcome of Jeko1(luci)-injected mice only in combination with cyclophosphamide. We conclude that well-established bioluminescence imaging is a valuable tool in disseminated xenograft tumor models. Our model can be translated to other cell lines and used to examine new therapeutic agents and schedules.

Authors: Margarethe Köberle, Kristin Müller, Manja Kamprad, Friedemann Horn, Markus Scholz

Date Published: 2015

Publication Type: Journal article

Abstract

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Author: Jahn F Schaaf M

Date Published: 2015

Publication Type: InCollection

Abstract

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Authors: Sebastian Stäubert, Kirsti Meinel, Frank Meineke, Matthias Löbe, Alfred Winter

Date Published: 2015

Publication Type: InProceedings

Abstract

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Author: Martina Patrizia Neininger Sten Schubert

Date Published: 2015

Publication Type: Journal article

Abstract (Expand)

The demand for evidence-based health informatics and benchmarking of ’good’ information systems in health care gives an opportunity to continue reporting on recent papers in the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE) here. The publications in focus deal with a comparison of benchmarking initiatives in German-speaking countries, use of communication standards in telemonitoring scenarios, the estimation of national cancer incidence rates and modifications of parametric tests. Furthermore papers in this issue of MIM are introduced which originally have been presented at the Annual Conference of the German Society of Medical Informatics, Biometry and Epidemiology. They deal as well with evidence and evaluation of ’good’ information systems but also with data harmonization, surveillance in obstetrics, adaptive designs and parametrical testing in statistical analysis, patient registries and signal processing.   The demand for evidence-based health informatics and benchmarking of ’good’ information systems in health care gives an opportunity to continue reporting on recent papers in the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE) here. The publications in focus deal with a comparison of benchmarking initiatives in German-speaking countries, use of communication standards in telemonitoring scenarios, the estimation of national cancer incidence rates and modifications of parametric tests. Furthermore papers in this issue of MIM are introduced which originally have been presented at the Annual Conference of the German Society of Medical Informatics, Biometry and Epidemiology. They deal as well with evidence and evaluation of ’good’ information systems but also with data harmonization, surveillance in obstetrics, adaptive designs and parametrical testing in statistical analysis, patient registries and signal processing. //  The demand for evidence-based health informatics and benchmarking of ’good’ information systems in health care gives an opportunity to continue reporting on recent papers in the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE) here. The publications in focus deal with a comparison of benchmarking initiatives in German-speaking countries, use of communication standards in telemonitoring scenarios, the estimation of national cancer incidence rates and modifications of parametric tests. Furthermore papers in this issue of MIM are introduced which originally have been presented at the Annual Conference of the German Society of Medical Informatics, Biometry and Epidemiology. They deal as well with evidence and evaluation of ’good’ information systems but also with data harmonization, surveillance in obstetrics, adaptive designs and parametrical testing in statistical analysis, patient registries and signal processing.

Authors: Alfred Winter, R-D Hilgers, R. Hofestädt, Ursula Hübner, Petra Knaup-Gregori, C. Ose, C. Schmoor, A. Timmer, D. Wege

Date Published: 2015

Publication Type: Journal article

Abstract (Expand)

Einleitung: An der Universität Leipzig wird die Studienrichtung Medizinische Informatik als Schwerpunkt im Studiengang Informatik in Kooperation von Medizinischer Fakultät und der Fakultät für Mathematik und Informatik angeboten. Den Studierenden wird in diesem interdisziplinären[zum vollständigen Text gelangen Sie über die oben angegebene URL]

Authors: Sebastian Stäubert, Matthias Löbe, Franziska Jahn, Michael Schaaf, Alfred Winter

Date Published: 2015

Publication Type: Misc

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