Title: | Retrieval of Gene Expression Measurements with Probabilistic Models |
Author(s): | Faisal, Ali |
Date: | 2014 |
Language: | en |
Pages: | 99 + app. 156 |
Department: | Tietojenkäsittelytieteen laitos Department of Information and Computer Science |
ISBN: | 978-952-60-5781-1 (electronic) 978-952-60-5780-4 (printed) |
Series: | Aalto University publication series DOCTORAL DISSERTATIONS, 108/2014 |
ISSN: | 1799-4942 (electronic) 1799-4934 (printed) 1799-4934 (ISSN-L) |
Supervising professor(s): | Kaski, Samuel, Prof., Aalto University, Department of Information and Computer Science, Finland |
Thesis advisor(s): | Peltonen, Jaakko, Dr., Aalto University, Department of Information and Computer Science, Finland |
Subject: | Computer science |
Keywords: | machine learning, bioinformatics, probabilistic modeling, information retrieval, Bayesian generative models |
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Abstract:A crucial problem in current biological and medical research is how to utilize the diverse set of existing biological knowledge and heterogeneous measurement data in order to gain insights on new data. As datasets continue to be deposited in public repositories it is becoming important to develop search engines that can efficiently integrate existing data and search for relevant earlier studies given a new study. The search task is encountered in several biological applications including cancer genomics, pharmacokinetics, personalized medicine and meta-analysis of functional genomics.
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Parts:[Publication 1]: José Caldas, Nils Gehlenborg, Ali Faisal, Alvis Brazma and Samuel Kaski. Probabilistic retrieval and visualization of biologically relevant microarray experiments. Bioinformatics, 25(12):i145–i153, 2009. doi:10.1093/bioinformatics/btp215. View at Publisher [Publication 2]: Ali Faisal, Frank Dondelinger, Dirk Husmeier, Colin M. Beale. Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods. Ecological Informatics, 5(6):451–464, 2010. doi:10.1016/j.ecoinf.2010.06.005. View at Publisher [Publication 3]: José Caldas, Nils Gehlenborg, Eeva Kettunen, Ali Faisal, Mikko Rönty, Andrew G. Nicholson, Sakari Knuutila, Alvis Brazma and Samuel Kaski. Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma. Bioinformatics, 28(2):246–253, 2012. doi:10.1093/bioinformatics/btr634. View at Publisher [Publication 4]: Suleiman A Khan, Ali Faisal, John P. Mpindi, Juuso A. Parkkinen, Tuomo Kalliokoski, Antti Poso, Olli P. Kallioniemi, Krister Wennerberg and Samuel Kaski. Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs. BMC Bioinformatics, 13:112, 2012. doi:10.1186/1471-2105-13-112. View at Publisher [Publication 5]: Riku Louhimo, Viljami Aittomaki*, Ali Faisal*, Marko Laakso*, Ping Chen, Kristian Ovaska, Erkka Valo, Leo Lahti, Vladimir Rogojin, Samuel Kaski and Sampsa Hautaniemi. Systematic use of computational methods allows stratification of treatment responders in glioblastoma multiforme. Systems Biomedicine, 1(2):130–136, 2013. doi:10.4161/sysb.28904. View at Publisher [Publication 6]: Ali Faisal, Jussi Gillberg, Gayle Leen and Jaakko Peltonen. Transfer Learning using a Nonparametric Sparse Topic Model. Neurocomputing, 112:124–137, 2013. doi:10.1016/j.neucom.2012.12.038. View at Publisher [Publication 7]: Ali Faisal, Jaakko Peltonen, Elisabeth Georgii, Johan Rung and Samuel Kaski. Toward computational cumulative biology by combining models of biological datasets. Submitted to a journal, 6 pages, 2013. |
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