Health Research Hub
Zusammenarbeit und wissenschaftlicher Austausch sind der Schlüssel zu erfolgreicher Forschung.
Health Research Hub
- verbindet Forschungsgruppen innerhalb der ZHAW,
- fördert deren Zusammenarbeit
- und schafft ein Netzwerk rund um die gesundheitsbezogene Forschung.
Interdisziplinäre Projekte
Das Health Research Hub fördert die gesundheitsbezogene Forschung und unterstützt interdisziplinäre Kooperationsprojekte. Die institutsübergreifende Bündelung der Kräfte fördert das Denken über Grenzen hinweg und bringt innovative gesundheitsbezogene Forschung voran.
Bayes network analysis for data-driven decision support in healthcare
Constantly rising costs in the healthcare sector require economic action without compromising the quality of care. In this project, extensive data collected from various hospitals is examined. The resulting models in the form of Bayesian networks will allow conclusions about hidden relationships and contribute to productivity and sustainability in health institutions.
Computational literature-based natural product drug discovery
Literature Based Discovery (LBD) has become widespread, but little has been done to automate it in the field of Natural Product Drug Discovery. The goal of this project is to devise an automated LBD system for natural product drugs for new discoveries, but also to query and explore present knowledge.
Engineered bacteriophages for the control of E. coli O157
Bacteriophages are bacterial viruses that are attracting increasing attention worldwide as a promising alternative to conventional antibiotics. The goal of this project is to genetically engineer bacteriophages for a better control of pathogenic Escherichia coli (E. coli) and to further develop large-scale phage production technologies.
Fighting bites with bytes - promoting public health with crowdsourced tick prevention
Ticks are currently on the rise and transmit several infectious diseases. A team of ZHAW experts in geographical information systems, artificial intelligence, data science and in tick biology develop a spacio-temporal tick risk model to help reducing the risk of tick-borne diseases.
Molecular mechanism of bacteriophage tail spike proteins in bacterial infection
Dramatic worldwide increase in antibiotic resistance to human pathogens is of great concern. Bacteriophages selectively kill bacteria and present an alternative to antibiotics. An expert team at ZHAW investigates interactions between bacteriophages and bacteria on a molecular level.
Silent pathway awakening to discover novel antibacterial compounds from actinomycetes
Many disease-causing bacteria are currently developing antibiotic resistance. This is a serious threat to human health. New antibiotics are therefore urgently needed. A project team of ZHAW and ETH is taking up this challenge.
Strategies to reduce mycotoxins in grain side product streams enabling their reintroduction into the food value chain
Food safety has become a major challenge within crops in recent years: an estimated 25% of all global crops are affected by moulds. This project aims at developing solutions to reduce mycotoxins in grain through the application of functional microorganisms and / or tailored enzymes.
News
Aktuelle Projekte
Im Zuge des Neuaufbaus der Forschungsdatenbank sind die bisherigen Listen mit Forschungsprojekten nicht mehr abrufbar. Die Zukunft geht in Richtung Volltextsuche und Filterung, um bestmögliche Suchergebnisse für unsere Besucher:innen zur Verfügung zu stellen.
In der Zwischenzeit kannst du die Projekte ganz einfach unter folgenden Link per Textsuche finden: «Zur neuen Suche in der Projektdatenbank»
Aktuelle Publikationen
-
Karavasiloglou, Nena; Pestoni, Giulia; Dehler, Anna; Sych, Janice Marie; Faeh, David; Rohrmann, Sabine,
2022.
Public Health Nutrition.
25(9), S. 2395-2402.
Verfügbar unter: https://doi.org/10.1017/S1368980022000647
-
Lardos, Andreas; Aghaebrahimian, Ahmad; Koroleva, Anna; Sidorova, Julia; Wolfram, Evelyn; Anisimova, Maria; Gil, Manuel,
2022.
Frontiers in Bioinformatics.
2(827207).
Verfügbar unter: https://doi.org/10.3389/fbinf.2022.827207
-
Smits, Theo H. M.; Arend, Lavinia N. V. S.; Cardew, Sofia; Tång-Hallbäck, Erika; Mira, Marcelo T.; Moore, Edward R. B.; Sampaio, Jorge L. M.; Rezzonico, Fabio; Pillonetto, Marcelo,
2022.
European Journal of Clinical Microbiology & Infectious Diseases.
41(4), S. 547-558.
Verfügbar unter: https://doi.org/10.1007/s10096-022-04413-8
-
Suter, Susanne; Spinner, Georg; Hoelz, Bianca; Rey, Sofia; Thanabalasingam, Sujeanthraa; Eckstein, Jens; Hirsch, Sven,
2022.
Visualization and analysis of wearable health data from COVID-19 patients.
arXiv.
Verfügbar unter: https://doi.org/10.21256/zhaw-24219
-
Hanne, Thomas; Gachnang, Phillip; Gatziu Grivas, Stella; Kirecci, Ilyas; Schmitter, Paul,
2022.
Artificial intelligence and machine learning for maturity evaluation and model validation [Paper].
In:
ICEME 2022 Proceeding.
13th International Conference on E-business, Management and Economics (ICEME), Beijing, China, 16-18 July 2022.
Association for Computing Machinery.
S. 256-260.
Verfügbar unter: https://doi.org/10.1145/3556089.3556102
Team
Der Health Research Hub wird von einem wissenschaftlichen Ausschuss geleitet und von einem Programm-Manager unterstützt:
Komitee
Programm-Manager
Es wurden keine Personendetails gefunden.