Thesis supervisor: Bálint Antal
Location of studies (in Hungarian): Debreceni Egyetem Informatikai Kar Abbreviation of location of studies: DE IK
Description of the research topic:
The aim of functional genomics is to discover the role of certain genes in organisms. However, biologcal experiments only investigate only a small set of possibl biological functions. The aim of this reserch subject is to establish an algorithm to re-analiyse microscope screens and predict possible gene functions by using other publicly available databases of other modalities. Creating a common representation for the different modalities will enable the development of a novel machine learning algorithm.
Bibliography
Y. Bengio: Learning Deep Architectures for AI, Foundations & Trends in Machine Learning, 2009.
Alberts et al.: Molecular Biology of the Cell 5E, 2008.
J. Schmidhuber, K. R. Thorisson, M. Looks (editors): Artificial General Intelligence. Proceedings of the 4th International Conference, AGI 2011, Mountain View, CA, USA, August 3-6, 2011, Lecture Notes in Computer Science, Volume 6830, 2011, Springer, DOI: 10.1007/978-3-642-22887-2.
Recommended language skills (in Hungarian): angol Number of students who can be accepted: 1
Deadline for application: 2018-11-15
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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