Teaching

On this page we provide information about lectures and seminars we are currently offering. In addition, we provide information about our textbook. 

Computational Diagnostics of Data - DATA.ML.390

The lecture Computational Diagnostics of Data is a 5 cr course offered at Tampere University. 

After completing the course, the student gained a basic understanding of the definition and the meaning of computational diagnostics and its utility for biomedical research. Case studies will be discussed illustrating the interplay between computational and statistical methods that are applied to large-scale and high-dimensional data sets from genomic and genetic experiments. Moreover, the student will learn how to practically approach such problems by using the statistical programming language R. In general, the course teaches statistical thinking in the context of biomedical problems, i.e., the adaptation of machine learning methods in a problem specific manner.

The next lecture in Computational Diagnostics of Data will be offered in term 4 2021/2022. 

Master thesis

We provide interesting projects for gifted students to perpare a Master thesis. Below we list some publications that resulted from such projects.

  • Smolander, Johannes, Matthias Dehmer, and Frank Emmert‐Streib. "Comparing deep belief networks with support vector machines for classifying gene expression data from complex disorders." FEBS open bio (2019).

  • Moore, D., de Matos Simoes, R., Dehmer, M., & Emmert-Streib, F. (2019). Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data. Current genomics, 20(1), 38-48.

  • Smolander, J., Stupnikov, A., Glazko, G., Dehmer, M., & Emmert-Streib, F. (2019). Comparing biological information contained in mRNA and non-coding RNAs for classification of lung cancer patients. BMC cancer, 19(1), 1176.

  • Yang, Z., Dehmer, M., Yli-Harja, O. and Emmert-Streib, F., 2020. Combining deep learning with token selection for patient phenotyping from electronic health records. Scientific Reports, 10(1), pp.1-18.

When you are interested in such a project, please contact us.

Textbook

For learning the mathematical basics of data science, we wrote a textbook: 
Mathematical Foundations of Data Science Using R, F. Emmert-Streib S. Moutari and M. Dehmer, De Gruyter (2020).

Publications

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© Frank Emmert-Streib