Diana Tilevik
Head of School/Senior Lecturer in Systems Biology
School of Bioscience
Room G2256
Teacher and researcher in systems biology.
Research
My research is conducted within the Infection Biology Research Group at the Systems Biology Research Environment and primarily focuses on applying computational and statistical methods and models in infection biology. In recent years, I have focused on the development and use of data-mining methods to analyze large-scale biomarker data for sepsis diagnostics.
Research
Publications
Projects
My research
The overall goal of our sepsis research is to improve sepsis diagnostics to increase the chances of survival for affected patients and reduce complications. Sepsis is a life-threatening condition that affects over 50,000 people annually in Sweden, with 10,000 fatalities. Timely and accurate diagnosis and treatment are crucial for survival.
At the University of Skövde, we collaborate with Skaraborg Hospital, Unilabs AB, 1928Diagnostics AB, QIAGEN AB, and more, to develop methods that enable the early identification of sepsis patients. Our research is mainly focused on developing methods to detect pathogenic microorganisms in patients' blood, and to diagnose sepsis using biomarkers.
We have evaluated several molecular biological methods for the rapid identification of bacteria and fungi, and also developed new diagnostic approaches. Among other advancements, we have developed multimarker panels that can identify patients with bacterial sepsis at an early stage of the disease. These panels combine biological and clinical markers for improved diagnostic precision. To ensure the reliable use of biomarkers in clinical diagnostics, we also work on developing quality controls. Additionally, we utilize various sequencing techniques to characterize bacterial genomes and develop pipelines for rapid and cost-effective species identification, as well as analysis of antibiotic resistance and virulence factors.
Academic Degrees and Levels
- Docent in Systems Biology, Univeristy of Skövde, 2022
- Doctor of Philosophy in Infection Biology, Karolinska Institutet, 2010
- Master of Science in Computational Molecular Biology, University of Skövde, 2004
2023
BMC Infectious Diseases
2023. Article.
https://doi.org/10.1186/s12879-022-07977-0
2022
Microbial Pathogenesis
2022. Article.
https://doi.org/10.1016/j.micpath.2022.105836
2021
Frontiers in Microbiology
2021. Article.
https://doi.org/10.3389/fmicb.2021.640408
2019
Evaluation of QuickFISH and maldi Sepsityper for identification of bacteria in bloodstream infection
Infectious Diseases
2019. Article.
https://doi.org/10.1080/23744235.2018.1554258
14th Annual Workshop in Systems Biology, University of Skövde, Sweden, 21 November 2019
2019. Conference paper, poster.
14th Annual Workshop in Systems Biology, University of Skövde, Sweden, 21 November 2019
2019. Conference paper, poster.
29th European Congress of Clinical Microbiology and Infectious Diseases, ECCMID, Amsterdam, Netherlands, 13-16 April, 2019
2019. Conference paper, poster.
29th European Congress of Clinical Microbiology and Infectious Diseases, ECCMID, Amsterdam, Netherlands, 13-16 April, 2019
2019. Conference paper, poster.
2018
Laboratory Investigation
2018. Article, review. https://doi.org/10.1038/s41374-018-0143-3
2017
Digital Human Modeling - Applications in Health, Safety, Ergonomics, and Risk Management: Health and Safety: 8th International Conference, DHM 2017 Held as Part of HCI International 2017 Vancouver, BC, Canada, July 9–14, 2017, Proceedings, Part II
2017. Conference paper. https://doi.org/10.1007/978-3-319-58466-9_3
2016
2015
2014
2013
2012
2011
2010
2008
2007
2006
Finished 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 BiologymiRSeps - Future diagnostics of sepsis
This project is one of several ongoing projects within the research programme “Future diagnostics for sepsis”. The aim is to develop diagnostics that can be used earlier in cases of sepsis in order to increase the patient’s chances of survival with fewer complications.
January 2020 - June 2023 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 BiologyBiomarkers in clinical diagnosis
This project is one of several ongoing projects in the research "Future diagnostics of sepsis". The goal is to develop earlier and more accurate diagnostics for sepsis in order to increase the chance of patients suffering from survival and with less disease complications.
October 2017 - September 2021 Systems BiologySMARTDIAGNOS – rapid detection of sepsis
This project is one of several ongoing projects in the research "Future diagnostics of sepsis". The goal is to develop earlier and more accurate diagnostics for sepsis in order to increase the chance of patients suffering from survival and with less disease complications.
February 2016 - January 2020 Systems BiologySepsIT® – the development of diagnostic systems for sepsis
This project is one of several ongoing projects within the research programme “Future diagnostics for sepsis”. The aim is to develop diagnostics that can be used earlier in cases of sepsis in order to increase the patient’s chances of survival with fewer complications.
October 2016 - September 2019 Systems BiologyEarly diagnosis of sepsis
This project is one of several ongoing projects in the research "Future diagnostics of sepsis". The goal is to develop earlier and more accurate diagnostics for sepsis in order to increase the chance of patients suffering from survival and with less disease complications.
January 2014 - December 2016 Systems Biology