- About
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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
Showing 11 to 20 of 121 (0.01 seconds)| 11 |
Mathematical models and statistics for evolutionary inferenceParks, Sarah Louise January 2015 (has links)
No description available.
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| 12 |
Transcriptome sequencing analysis with application to embryonic stem cell self-renewalSteijger, Tamara January 2014 (has links)
No description available.
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| 13 |
Biological network evaluation and relation discovery from scientific literatureLi, Chen January 2014 (has links)
No description available.
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| 14 |
Spatial and stochastic modeling of TrkB mediated signaling pathways involved in long term potentation in the dendritic spineSeeliger, Christine January 2014 (has links)
No description available.
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| 15 |
Using natural language processing methods to support curation of a chemical ontologyBernard, Adam Simon January 2014 (has links)
No description available.
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| 16 |
Differential drug response as a function of ageMoita Santos, Rita January 2015 (has links)
No description available.
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| 17 |
Spatial analysis of complex biological tissues from single cell gene expression dataPettit, Jean-Baptiste Olivier Georges January 2015 (has links)
No description available.
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| 18 |
A novel framework for integrating a priori domain knowledge into traditional data analysis in the context of bioinformaticsDenaxas, Spiridon Christoforos January 2008 (has links)
Recent advances in experimental technology have given scientists the ability to perform large-scale multidimensional experiments involving large data sets. As a direct implication, the amount of data that is being generated is rising in an exponential manner. However, in order to fully scrutinize and comprehend the results obtained from traditional data analysis approaches, it has been proven that a priori domain knowledge must be taken into consideration. Infusing existing knowledge into data analysis operations however is a non-trivial task which presents a number of challenges. This research is concerned into utilizing a structured ontology representing the individual elements composing such large data sets for assessing the results obtained. More specifically, statistical natural language processing and information retrieval methodologies are used in order to provide a seamless integration of existing domain knowledge in the context of cluster analysis experiments on gene product expression patterns. The aim of this research is to produce a framework for integrating a priori domain knowledge into traditional data analysis approaches. This is done in the context of DNA microarrays and gene expression experiments. The value added by the framework to the existing body of research is twofold. First, the framework provides a figure of merit score for assessing and quantifying the biological relatedness between individual gene products. Second, it proposes a mechanism for evaluating the results of data clustering algorithms from a biological point of view.
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Markov models for protein sequence evolutionKosiol, Carolin January 2006 (has links)
No description available.
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Computational analysis of gene regulatory sites in two yeastsKivinen, Katja Johanna January 2004 (has links)
No description available.
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