Title: | Probabilistic analysis of the human transcriptome with side information |
Author(s): | Lahti, Leo |
Date: | 2010 |
Language: | en |
Pages: | Verkkokirja (1673 KB, 92 s.) |
Department: | Tietojenkäsittelytieteen laitos Department of Information and Computer Science |
ISBN: | 978-952-60-3368-6 (PDF) 978-952-60-3367-9 (printed) |
Series: | TKK dissertations in information science and technology, 19 |
ISSN: | 1797-5069 |
Supervising professor(s): | Kaski, Samuel, Prof. |
Subject: | Computer science, Biotechnology |
Keywords: | data integration, exploratory data analysis, functional genomics, probabilistic modeling, transcriptomics |
OEVS yes | |
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Abstract:Recent advances in high-throughput measurement technologies and efficient sharing of biomedical data through community databases have made it possible to investigate the complete collection of genetic material, the genome, which encodes the heritable genetic program of an organism. This has opened up new views to the study of living organisms with a profound impact on biological research.
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Parts:[Publication 1]: Laura L. Elo, Leo Lahti, Heli Skottman, Minna Kyläniemi, Riitta Lahesmaa, and Tero Aittokallio. 2005. Integrating probe-level expression changes across generations of Affymetrix arrays. Nucleic Acids Research, volume 33, number 22, e193, 10 pages. © 2005 by authors.[Publication 2]: Leo Lahti, Laura L. Elo, Tero Aittokallio, and Samuel Kaski. 2011. Probabilistic analysis of probe reliability in differential gene expression studies with short oligonucleotide arrays. IEEE/ACM Transactions on Computational Biology and Bioinformatics, volume 8, number 1, pages 217-225. © 2011 Institute of Electrical and Electronics Engineers (IEEE). By permission.[Publication 3]: Leo Lahti, Juha E. A. Knuuttila, and Samuel Kaski. 2010. Global modeling of transcriptional responses in interaction networks. Bioinformatics, volume 26, number 21, pages 2713-2720. © 2010 by authors.[Publication 4]: Leo Lahti, Samuel Myllykangas, Sakari Knuutila, and Samuel Kaski. 2009. Dependency detection with similarity constraints. In: Tülay Adali, Jocelyn Chanussot, Christian Jutten, and Jan Larsen (editors). Proceedings of the 19th IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2009). Grenoble, France. 1-4 September 2009. Piscataway, NJ, USA. IEEE. Pages 89-94. ISBN 978-1-4244-4947-7. © 2009 Institute of Electrical and Electronics Engineers (IEEE). By permission.[Publication 5]: Janne Sinkkonen, Janne Nikkilä, Leo Lahti, and Samuel Kaski. 2004. Associative clustering. In: Jean-François Boulicaut, Floriana Esposito, Fosca Giannotti, and Dino Pedreschi (editors). Proceedings of the 15th European Conference on Machine Learning (ECML 2004). Pisa, Italy. 20-24 September 2004. Berlin, Heidelberg, Germany. Springer. Lecture Notes in Computer Science, volume 3201, pages 396-406. ISBN 3-540-23105-6. © 2004 by authors and © 2004 Springer Science+Business Media. By permission.[Publication 6]: Samuel Kaski, Janne Nikkilä, Janne Sinkkonen, Leo Lahti, Juha E. A. Knuuttila, and Christophe Roos. 2005. Associative clustering for exploring dependencies between functional genomics data sets. IEEE/ACM Transactions on Computational Biology and Bioinformatics: Special Issue on Machine Learning for Bioinformatics - Part 2, volume 2, number 3, pages 203-216. © 2005 Institute of Electrical and Electronics Engineers (IEEE). By permission. |
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