Biotechnology

Obesity and type 2 diabetes are associated with changes in gut microbiota and disturbed energy metabolism. We hypothesize that there is a crosstalk between gut bacteria and host energy metabolism.

This research group is concerned with diseases and disorders that have a clear correlation to environmental factors both biotic and abiotic in origin.

Skeletal muscle is an active secretory organ. We are working on the role of extracellular vesicles (EVs) as secreting factors from skeletal muscle, what the EVs contain, and whether they can affect neighboring and distant cells.

We spend much of our lives indoors where we interact with building microbiomes. We have developed methodologies to identify the microbes to which target groups are routinely exposed.

This research group applies genomics to study the evolution, adaptability and resilience of pathogenic viruses and bacteria.

An overall aim of the project is to define immuno-microbial signatures that can be used for non-invasive detection of colorectal cancer and pre-cancer stages.

No effective treatment exists for severe forms of dry eye disease (DED). We are developing the protein lacritin, which is found in tears, to become a medicine for dry eye disease.

Infections involving biofilms are very difficult to treat effectively. We are developing nanoparticles that can act as carriers for new antibiotics to better treat biofilm-based infections.

We are performing in-depth characterizations of the ocular microbiota of dry eye disease sufferers, with the aim of identifying microbial risk profiles for disease development and severity.

The project seeks to develop drug formulations of novel antimicrobials, so-called bacteriocins, by applying nanotechnology and artificial intelligence.

This group's research areas are within male reproductive biology, with emphasis on semen quality, testicular cancer, and assisted reproduction. Artificial intelligence is used to develop improved methods for semen analysis.

At OsloMet we work on developing algorithms and models using machine learning tailored towards applications in medical research that will help to solve the challenges in the healthcare sector.

Assistive technology, or in the Nordic context often called welfare technology, refers to tools and services that aim to improve quality of life and wellbeing.

OsloMet researchers and research groups apply different omics-technologies to study the molecules of life, how their variation affects their functions, how they are generated and decay.

Sensors are devices that react and respond to various stimuli, such as biochemical, electrical, or mechanical signals. OsloMet uses and develops sensors to gather health related data.

Through collaborating across disciplines and sectors, we will ensure that research and innovation within health and technology remains user- and problem-oriented.