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      University of Skövde, link to startpage

      Peter Sartipy

      Adjunct Professor
      School of Bioscience
      Room G2240

      Research

      2022

      Markus Johansson, Benyapa Tangruksa, Sepideh Heydarkhan-Hagvall, Anders Jeppsson, Peter Sartipy, Jane Synnergren

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

      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

      Gianluigi Savarese, Johan Bodegard, Anna Norhammar, Peter Sartipy, Marcus Thuresson, Martin R. Cowie, Gregg C. Fonarow, Muthiah Vaduganathan, Andrew J. S. Coats

      European Journal of Heart Failure

      2021. Article. https://doi.org/10.1002/ejhf.2271 Open Access

      Bergur V. Stefánsson, Hiddo J. L. Heerspink, David C. Wheeler, C. David Sjöström, Peter J. Greasley, Peter Sartipy, Valerie Cain, Ricardo Correa-Rotter

      Data in Brief

      2021. Article. https://doi.org/10.1016/j.dib.2021.107237 Open Access

      Benjamin Ulfenborg, Alexander Karlsson, Maria Riveiro, Christian X. Andersson, Peter Sartipy, Jane Synnergren

      Journal of Biotechnology

      2021. Article. https://doi.org/10.1016/j.jbiotec.2020.12.002 Open Access

      2020

      Nidal Ghosheh, Barbara Küppers-Munther, Annika Asplund, Christian X. Andersson, Petter Björquist, Tommy B. Andersson, Helena Carén, Stina Simonsson, Peter Sartipy, Jane Synnergren

      ACS Omega

      2020. Article. https://doi.org/10.1021/acsomega.9b03514 Open Access

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

      Biology open

      2020. Article. https://doi.org/10.1242/bio.052381 Open Access

      Rosalie A. Scholtes, Daniël H. van Raalte, Ricardo Correa-Rotter, Robert D. Toto, Hiddo J. L. Heerspink, Valerie Cain, C. David Sjöström, Peter Sartipy, Bergur V. Stefánsson

      Diabetes, obesity and metabolism

      2020. Article. https://doi.org/10.1111/dom.13923 Open Access

      Bergur V. Stefánsson, Hiddo J. L. Heerspink, David C. Wheeler, C. David Sjöström, Peter J. Greasley, Peter Sartipy, Valerie Cain, Ricardo Correa-Rotter

      Journal of diabetes and its complications

      2020. Article. https://doi.org/10.1016/j.jdiacomp.2020.107729

      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

      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

      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

      Aberrant DNA methylation patterns in hepatocytes derived from human pluripotent stem cells

      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.

      July 2013 - June 2016 Systems Biology

      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

      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

      CardioTrophy - for reduced morbidity and mortality in cardiovascular diseases

      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.

      March 2017 - February 2021 Systems Biology
      Published: 1/9/2020
      Edited: 1/9/2020
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