Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education, the Eurasia program, SiU-CPEA-LT-2016/10126
The Belanoda project aims at developing a multidisciplinary course in data sciences for life sciences. For the course, the project is developing a digital learning platform based on video and e-learning. The course concept is to teach students data analysis as experts in a multidisciplinary team, where physicists, data scientists and biologists work closely together and solve research problems. The first course was organized as a summer school at Ås, Norway in 2018, the second course will be organized as a summer school in Minsk, Belarus in 2019, the third course will be organized in Kazakhstan. The project involves six PhD and master students that work in interdisciplinary research labs. The project will establish a long-term collaboration between the Norwegian University of Life Sciences, the Belarusian State University, the National Academy of Sciences of Belarus and other potential Eurasian partners. The collaboration focuses on the MSc and PhD education in Data Sciences for Life Sciences.
Interdisciplinary summer school on mining of biological data, August 2019, Minsk, Belarus.
Norwegian University of Life Sciences, together with Belarusian State University and United Institute of Informatics Problems (National Academy of Sciences of Belarus), is organizing a summer school for Master and PhD students dedicated to analysis of biological data in infrared spectroscopy. Attendees will be introduced to the basics in molecular biology, machine learning and physics of infrared absorption, explained by renowned scientists in the corresponding fields. The main aim of summer school is to provide experience in solving a complex research problem in a multidisciplinary team. Students in biology, physics and computer science will work together on a two-day project culminating in a project defense and a presentation session for early-stage researchers to share their research findings with other participants.
Blazhko U., Shapaval V., Kovalev V., Kohlera A.
Comparison of augmentation and pre-processing for deep learning and chemometric classification of infrared spectra
Chemometrics and Intelligent Laboratory Systems 215 (2021) 104367
Smirnova M., Miamin U., Kohler A., Valentovich L., Akhremchuk A., Sidarenka A., Dolgikh A., Shapaval V.
Isolation and characterization of fast‐growing green snow bacteria from coastal East Antarctica.
MicrobiologyOpen, 10 (2021) e1152