Data Science Research Group for Health and Life Sciences
Many biological databases have become used in the field of life sciences. These databases are heterogeneous and distributed. In addition, especially in the field of healthcare, there is a large amount of unstructured and mostly textual data. The research topics of the Data Science for Healthcare and Life Sciences working group are:
- Creating and/or analyzing structural databases from non-structured data with text mining methods
- Integration of data from different sources with connected data and semantic network technologies
- Analyzing the resulting big data with machine and/or deep learning methods
With these studies, it is aimed to reveal new or hybrid approaches based on prediction for the solution of many important problems in the field of bioinformatics and biomedicine.
Persons:
- Asst. Prof. Dr. Özgür GÜMÜŞ
- Prof. Dr. Oguz DIKENELLI
- Res. Asst. Erkan YAŞAR
- Res. Asst. Beste Kaysi
- Res. Asst. Hüseyin UYAR (PhD student and 100-2000 scholarship holder)
- Engin AYBEY (Health Bioinformatics PhD student and 100-2000 fellow)
Ongoing BAP Project:
- Integration of Open Biomedical Data with Semantic Network Technologies and Analysis with Graph Mining, December 2016 – December 2019
Completed BAP Project:
- Comparison of Different Data Mining Methods for Geographical Classification of Olive Oils in Turkey, December 2014 – August 2017
