A Meta-analysis of Sublethal Pesticide Exposure Effects on Gene Expression of Honey Bees

2020-2021 Summer
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 

The student will be involved in using coding and High Performance Computing to analyze RNAseq data generated from honey bee hives that have been selected for Varroa resistance and one that have not to identify biomarkers that can be used to selectively breed resistant honey bee hives in the future.
Vorroa mites are the number one most damaging pathogen/pest for honey bees worlwide.
This project will involve a bioinformatic systems biology analysis and will be completely online.

Related Areas of Project: 
Computer Science and Engineering
Molecular Biology, Genetics and Bioengineering

About Project Supervisors

Christopher Mayack
Faculty of Engineering and Natural Science
Uludağ Bee Journal Editor - http://dergipark.gov.tr/uluaricilik