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Published by LAP LAMBERT Academic Publishing Apr 2022, 2022
ISBN 10: 6200114129ISBN 13: 9786200114129
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The epidermal growth factor receptor (EGFR) is a cell surface receptor, which controls cell growth and division. Mutations affecting the receptor expression could lead to cancer. Analysis of EGFR interactions with living cells requires measuring separations between 5 and 60nm. The separations are calculated by analysing time-series of diffraction limited spots, generated by labelled EGFRs. Finding such time-series manually is time consuming and non-reproducible. This project uses machine learning algorithms in combination with understanding of the data collection process and analysis requirements to optimise the data selection process, by automatically rejecting non-analysable time-series. The comparison to the manual process shows that the automated process significantly decreases the time required for data selection and decreases the uncertainty in the distance measurements. 300 pp. Englisch.
Published by LAP Lambert Academic Publishing, 2022
ISBN 10: 6200114129ISBN 13: 9786200114129
Seller: moluna, Greven, Germany
Book Print on Demand
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The epidermal growth factor receptor (EGFR) is a cell surface receptor, which controls cell growth and division. Mutations affecting the receptor expression could lead to cancer. Analysis of EGFR interactions with living cells requires measuring separations.
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200114129ISBN 13: 9786200114129
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The epidermal growth factor receptor (EGFR) is a cell surface receptor, which controls cell growth and division. Mutations affecting the receptor expression could lead to cancer. Analysis of EGFR interactions with living cells requires measuring separations between 5 and 60nm. The separations are calculated by analysing time-series of diffraction limited spots, generated by labelled EGFRs. Finding such time-series manually is time consuming and non-reproducible. This project uses machine learning algorithms in combination with understanding of the data collection process and analysis requirements to optimise the data selection process, by automatically rejecting non-analysable time-series. The comparison to the manual process shows that the automated process significantly decreases the time required for data selection and decreases the uncertainty in the distance measurements.