Prof. Dr. Mehmet Gültas

RESEARCH FOCUS

1. Algorithmic Methods for Smart-/Precision-Farming

• Machine Learning and Deep Learning
• Information theory
• Probabilistic data models
• Algorithmic methods for Smart/Precision Farming
• Algorithmic methods of statistical learning

2. Data Management and Data Analysis

• Statistical analysis and interpretation of big data in plant/animal breeding, bioinformatics and livestock husbandry
• Big data analyses in agriculture in general
• Development of machine learning algorithms to identify and classify specific behavioural patterns in livestock
• Development of new data management systems with regard to collection, storage and administration of data relevant to agriculture
• Establishment of unsupervised machine learning algorithms (e.g. clustering methods) to analyse agricultural data
• Development of statistical data models and machine learning methods to establish digital technologies within the field of agriculture
• Understanding complex biological processes like epistatic interactions among genotypic markers by applying statistical methods

3. Bioinformatics and Breeding Informatics

• Analysis and interpretation of multi-omics data (Next-Generation Sequencing(NGS), RNA-seq, etc.)
• Understanding of complex biological processes and networks, e.g. the research on epistatic interactions among genotypic markers
• Analysis of transcription factors concerning their functions as well as interactions
• Pathway analyses (upstream, downstream and masterregulator analyses) for the understanding of biological activities of regulatory processes on many levels (RNA, proteins, metabolites, etc.)
• Information theory and its applications in bioinformatics and computational biology
• Machine Learning approaches and evolutionary algorithms in bioinformatics and computational biology
• Gene regulatory network analysis
• Clustering approaches in bioinformatics (Markov Cluster Algorithm)

Teaching

Winter term

• Applied Machine Learning in Agriculture with R (MSc)
• Data Analysis with R (MSc)
• Applied Bioinformatics with R (MSc)
• Scientific Project: scientific methods, procedures and practical skills in animal and plant breeding (MSc)
• Forschungspraktikum Biometrie mit R (BSc)

Summer term

• Data Analysis with R (MSc)
• Forschungspraktikum Biometrie mit R (BSc)
• Anwendungsgebiete der Data Science (BSc)
• Bioinformatik (BSc)
• Scientific Project: scientific methods, procedures and practical skills in animal and plant breeding (MSc)

On-going and past projects, student related works and theses