Finished research projects: Translational Bioinformatics

2013-2016 Human pluripotent stem cells (hPSC) are characterized by their unique capacities of self-renewal and differentiation, and, as such, they provide an excellent human cell source in basic research, drug discovery and regenerative medicine.

2017-2020 Within AlgorOmics we develop and implement algorithms for integration, visualization, and analysis of large-scale omics data, with applications in stem cell differentiation and drug development.

2015-2018 The pharmaceutical industry has an urgent need for in vitro model systems with high human relevance that can be used for toxicity testing, drug development, and disease modelling. The project aims at developing a human in vitro model based on human pluripotent stem cells that can mimic important aspects of the blood-brain-barrier.

2020-2024 Artificial intelligence (AI) is an important driving force that is rapidly transforming health care and pharmaceutical industries in several ways. The vast amount of biomedical data available today poses unique opportunities to develop a repertoire of AI-based models. Although the results from studies using AI for solving biomedical problems are encouraging, there are numerous scientific challenges associated with AI for life science applications that need to be addressed.

2015-2019 The aim of this project is to contribute with improved methods for analysis, integration, and visualization of biomedical big data. Recent years it has been a massive digitalization of all types of data and information in the society and the majority of all information in the world is nowadays anticipated to be digitalized. This encompasses enormous possibilities for generation of new knowledge but also puts demands on competence and tools for analysis and interpretation of big and complex data, e.g. to identify and extract patterns and information from different data sources. To meet these increasing demands of large-scale data analysis more competence, better and faster algorithms, and powerful computers are needed for execution these algorithms.

2017-2022 This project is one of the three subprojects within the synergy project BioMine - Data-mining for biomarker discovery, selection, and validation. In this subproject we investigate how large-scale biomolecular data can be used to identify specific biomarkers for disease modelling

2017-2022 This project is one of the three subprojects within the synergy project BioMine - Data-mining for biomarker discovery, selection, and validation. In this subproject we investigate how large-scale biomolecular data can be used to identify specific biomarkers for toxicity testing. The project is performed in close collaboration between the University of Skövde, AstraZeneca Gothenburg and Takara Bio Europe.

2017-2022 In the BioMine project (Data-mining for Biomarker Discovery, Selection, and Validation), studies are performed on how large-scale biomolecular data can be mined to enable discovery and validation of multilevel biomarkers in Life Science.

2017-2021 The advancement in stem cell research over the last decade has now made it possible to generate large quantities of human specialized cells for in vitro applications. Specifically, in the drug discovery and development process this has important implications. The project involves studies of the genetic and molecular basis of hypertrophy and aims to develop new knowledge that can contribute to the development of novel therapies and treatments that can reduce cardiovascular morbidity and mortality.

2022-2024 In this project we develop and implement an innovative Deep-Learning (DL) based method for quality assessment for industrial use. By using human embryonic stem cells as a model system, we develop in different steps a neural network (NN) classifier for a stepwise prediction of the cell state (quality) of these cells using quantitative PCR (qPCR) data.

2018-2021 The DMDPipe project aims to develop a pipeline for identifying and analysing disease-causing modules of interacting proteins. The project is expected to contribute to the development of individualised diagnostics and treatment for asthma.

2019-2021 The Transplant Tissue Engineering (TransTissuE) is a collaboration project between the University of Skövde, VERIGRAFT and XVIVO. We develop methods and strategies for optimization of the production process of personalized tissue-engineered vascular transplants.