Benjamin Ulfenborg

Education
Research
During my post-graduate studies, I developed new bioinformatics algorithms and tools for discovery of biomarkers for endometrial cancer. This research was carried out as a collaboration between the University of Skövde and Örebro University. I obtained my PhD degree in 2016 and started a post doc in the TransBiG research group, where I worked with algorithm development and large-scale data analysis to increase mechanistic understanding of stem cell differentiation, and stem cell-based in vitro models. In 2018 I became associate senior lecturer in bioinformatics and have since then been involved in several research projects, both at the university and externally.
The aims of my research are to develop powerful bioinformatics algorithms and tools for discovery of biomarkers, and to increase understanding of how biological processer are regulated. I have a particular interest in integration of different types of data and in machine learning. Examples of tools I have published are the R-packages Miodin for integration of multi-omics data and MAsC for clustering of large-scale data.
2023
Stem Cells
2023. Article.
https://doi.org/10.1093/stmcls/sxad049
Bioinformatics and Biomedical Engineering: 10th International Work-Conference, IWBBIO 2023, Meloneras, Gran Canaria, Spain, July 12–14, 2023, Proceedings, Part I
2023. Conference paper. https://doi.org/10.1007/978-3-031-34953-9_8
2022
Scientific Reports
2022. Article.
https://doi.org/10.1038/s41598-022-15924-x
International Journal of Cancer
2022. Article.
https://doi.org/10.1002/ijc.34111
Life
2022. Article.
https://doi.org/10.3390/life12020293
PLOS ONE
2022. Article.
https://doi.org/10.1371/journal.pone.0269985
Briefings in Bioinformatics
2022. Article, review.
https://doi.org/10.1093/bib/bbab569
2021
Frontiers in Cardiovascular Medicine
2021. Article.
https://doi.org/10.3389/fcvm.2021.753470
Clinical Chemistry and Laboratory Medicine
2021. Article.
https://doi.org/10.1515/cclm-2021-0510
Journal of Biotechnology
2021. Article.
https://doi.org/10.1016/j.jbiotec.2020.12.002
2020
2019
2018
2017
2016
2015
2014
2013
Ongoing projects
BIO-AID - Biomedical AI-driven data analytics
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.
October 2020 - September 2024 Systems BiologyFinished projects
Biomarkers for disease modelling
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
October 2017 - May 2022 Systems BiologyBiomarkers for toxicity testing
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.
October 2017 - May 2022 Systems BiologyData-mining for Biomarker Discovery, Selection, and Validation
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.
October 2017 - May 2022 Systems BiologyTransplant Tissue Engineering
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.
April 2019 - September 2021 Systems BiologyAlgorOmics - developing new algorithms for biomarker identification
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.
April 2017 - March 2020 Systems BiologyBioinformatics - Biomedical Big Data
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.
October 2015 - September 2019 Systems BiologyBISON: Better decisions through Big Data
Big data has gained much interesting in recent years due to the rapid expansion of the massive amount of data that is available for solving different types of tasks within many different application domains. However, today's big data is still on a fairly low level of abstraction when it comes to complex decision support tasks, subject to e.g. high dimensionality and significant portions of uncertainty regarding which patterns to look for in the data.
October 2015 - September 2019 InformaticsHuman stem cell based in vitro model of the blood brain barrier
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.
October 2015 - September 2018 Systems Biology