Nonlinear gene activity- drug sensitivity relationship modelling for improved detection of genes that affect drug sensitivity

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(1)UPTEC X 05 021 APR 2005. ISSN 1401-2138. KARIN HOLMSTRÖM. Nonlinear gene activitydrug sensitivity relationship modelling for improved detection of genes that affect drug sensitivity. Master’s degree project.

(2) Molecular Biotechnology Programme Uppsala University School of Engineering Date of issue 2005-04. UPTEC X 05 021 Author. Karin Holmström Title (English). Nonlinear gene activity–drug sensitivity relationship modelling for improved detection of genes that affect drug sensitivity Abstract A novel approach for detection of genes whose products affect drug sensitivity was introduced. Two detectors, one based on nonlinear regression and the other on errors in variable modelling, have been tested on simulated data and was, using reciever operating characteristics graphs, compared to a linear state-of-the-art detection strategy, which is based on Pearson's correlation coefficient. On small and nonlinear datasets our modelling detector performed significantly better than the correlation coefficient detector. For example, a dataset size of five points gave under certain circumstances a rate of true positives of the modelling detector that was four times that of the correlation coefficient detector, both at 5% false positives. Our regression detector outperformed the correlation coefficient detector only on very small datasets. Keywords Relationship modelling, regression, drug sensitivity, correlation coefficient, detection. Supervisors. Mats Gustafsson Dept. of Engineering Sciences, Uppsala University Scientific reviewer. Anders Isaksson Dept. of Genetics and Pathology, Uppsala University Language. Security. English Classification. ISSN 1401-2138 Supplementary bibliographical information. Pages. 22 Biology Education Centre. Biomedical Center. Husargatan 3 Uppsala. Box 592 S-75124 Uppsala. Tel +46 (0)18 4710000. Fax +46 (0)18 555217.

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(4) Nonlinear gene activity–drug sensitivity relationship modelling for improved detection of genes that affect drug sensitivity Karin Holmström. Sammanfattning Läkemedelskänslighet, d v s hur stark effekt ett läkemedel har, varierar från patient till patient. Detta är ett problem vid t ex kemoterapi i behandling av cancer. Men denna variation kan utnyttjas för att hitta gener som påverkar just läkemedelskänsligheten. Kännedom om patientens uttrycksnivåer av dessa gener kan användas vid individuell behandling och för att förutsäga behandlingens slagkraft. Dessa gener kan också ge information om hur olika läkemedel fungerar. Om man känner till patienters läkemedelskänslighet och uttrycksnivåer för olika gener kan man identifiera de intressanta generna på olika sätt. Tidigare har en korrelationskoefficient mellan genuttryck och läkemedelskänslighet använts som mått på hur mycket genen påverkar läkemedelskänsligheten. Denna metod vore smidig och bra om sambandet mellan genuttryck och läkemedelskänslighet vore linjärt. Emellertid är detta inte fallet och i detta projekt har data istället anpassats till en ickelinjär kurva på två olika sätt. Dessa metoder för att hitta gener har med hjälp av simulerade data testats och jämförts med korrelationskoefficientmetoden. Det visade sig att de nya metoderna generellt sett presterar bättre när man har små datamängder.. Examensarbete 20 p civilingenjörsprogrammet i molekylär bioteknik Uppsala universitet, april 2005.

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