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      University of Skövde, link to startpage

      Benjamin Ulfenborg

      Senior Lecturer in BioInformatics
      School of Bioscience
      Room G2241B
      Benjamin Ulfenborg, senior lecturer in bioinformatics. Teaches on basic, advanced and research level, mainly in bioinformatics. Participates in several research projects carried out by the research group TransBiG at the university and in external collaborations.

      Education

      Programme
      60 credits
      Master's (2nd cycle)
      Programme
      120 credits
      Master's (2nd cycle)

      Research

      My research

      About my 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.

      2024

      Susanna Larsson, Sandra Holmgren, Lachmi Jenndahl, Benjamin Ulfenborg, Raimund Strehl, Jane Synnergren, Nidal Ghosheh

      ACS Omega

      2024. Article. https://doi.org/10.1021/acsomega.3c07098 Open Access

      A. Linder, S. Westbom-Fremer, C. Mateoiu, A. Olsson Widjaja, T. Österlund, S. Veerla, A. Ståhlberg, Benjamin Ulfenborg, I. Hedenfalk, K. Sundfeldt

      Human Reproduction

      2024. Article. https://doi.org/10.1093/humrep/deae043 Open Access

      2023

      Katarzyna Marzec-Schmidt, Nidal Ghosheh, Sören Richard Stahlschmidt, Barbara Küppers-Munther, Jane Synnergren, Benjamin Ulfenborg

      Stem Cells

      2023. Article. https://doi.org/10.1093/stmcls/sxad049 Open Access

      Sören Richard Stahlschmidt, Benjamin Ulfenborg, Jane Synnergren

      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

      Maria Araceli Diaz Cruz, Benjamin Ulfenborg, Peter Blomstrand, Maria Faresjö, Fredrik Ståhl, Sandra Karlsson

      Scientific Reports

      2022. Article. https://doi.org/10.1038/s41598-022-15924-x Open Access

      Shruti Jain, Nimrah Nadeem, Benjamin Ulfenborg, Maria Mäkelä, Shamima Afrin Ruma, Joonas Terävä, Kaisa Huhtinen, Janne Leivo, Björg Kristjansdottir, Kim Pettersson, Karin Sundfeldt, Kamlesh Gidwani

      International Journal of Cancer

      2022. Article. https://doi.org/10.1002/ijc.34111 Open Access

      Markus Johansson, Benjamin Ulfenborg, Christian X. Andersson, Sepideh Heydarkhan-Hagvall, Anders Jeppsson, Peter Sartipy, Jane Synnergren

      Mikael Sandstedt, Kristina Vukusic, Benjamin Ulfenborg, Marianne Jonsson, Lillemor Mattsson Hultén, Göran Dellgren, Anders Jeppsson, Jane Synnergren, Joakim Sandstedt

      Sören Richard Stahlschmidt, Benjamin Ulfenborg, Jane Synnergren

      Briefings in Bioinformatics

      2022. Article, review. https://doi.org/10.1093/bib/bbab569 Open Access

      2021

      Cláudia Correia, Qing-Dong Wang, Gunilla Linhardt, Leif G. Carlsson, Benjamin Ulfenborg, Anna Walentinsson, Katarina Rydén-Markinhutha, Margareta Behrendt, Johannes Wikström, Peter Sartipy, Karin Jennbacken, Jane Synnergren

      Frontiers in Cardiovascular Medicine

      2021. Article. https://doi.org/10.3389/fcvm.2021.753470 Open Access

      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 Biology

      Finished 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 Biology

      Biomarkers 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 Biology

      Data-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 Biology

      Transplant 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 Biology

      AlgorOmics - 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 Biology

      Bioinformatics - 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 Biology

      BISON: 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 Informatics

      Human 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
      Published: 1/9/2020
      Edited: 1/9/2020
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