dc.contributor.advisor | Beißbarth, Tim Prof. Dr. | |
dc.contributor.author | Sitte, Maren | |
dc.date.accessioned | 2020-05-12T12:33:15Z | |
dc.date.available | 2020-05-12T12:33:15Z | |
dc.date.issued | 2020-05-12 | |
dc.identifier.uri | http://hdl.handle.net/21.11130/00-1735-0000-0005-1397-B | |
dc.identifier.uri | http://dx.doi.org/10.53846/goediss-7972 | |
dc.language.iso | eng | de |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.ddc | 510 | de |
dc.title | Network Based Integration of Proteomic and Transcriptomic Data: Study of BCR and WNT11 Signaling Pathways in Cancer Cells | de |
dc.type | doctoralThesis | de |
dc.contributor.referee | Beißbarth, Tim Prof. Dr. | |
dc.date.examination | 2020-05-08 | |
dc.description.abstracteng | Bioinformatics applications in cancer research expanded rapidly over several years in
the past. Due to the fast development of high throughput technologies, it became
feasible to study the presence of hundreds of genes or proteins measured parallel in
one experiment. The challenge is to understand how the regulatory network alters
under different conditions or in disease. Their expression values can be used to learn
more about their interactions. To study their interplay under different conditions
network reconstruction methods were utilized.
This thesis demonstrates a general workflow for integrating data sets from different
data sources into a signaling network analysis for cancer cells. Exemplary, BCR
signaling in lymphomas and WNT11 signaling in breast cancer was analyzed utilizing
gene, proteinn and patient data to elucidate the changes of BCR signaling and WNT11
signaling after specific cell treatment.
The aim of the first study was to investigate proteomic data together with existing
gene expression data to predict how lymphomas translate signaling stimuli to expressed
phenotypes. BCR-related pathway interplays were reconstructed by analyzing several
gene and phospho-protein expression profiles. Therefore, the two network reconstruc-
tion techniques NEM and DDEPN were applied to transcriptomic and proteomic
measurements, followed by an integrative analysis to identify alterations in BCR
signaling after external stimulation.
In the second study, the WNT11 pathways were analyzed in relation to their interplay
to one of its receptors ROR2 in human breast cancer. It has been shown that WNT11
signaling highly depends on its receptors and ligands who determine downstream
signaling. In an integrative analysis pipeline, transcriptomic and proteo-mic data
sets were combined to estimate downstream signaling interplay. Subsequently, patient
data was included to associate the findings with clinical outcome.
In both studies, the analysis identified genes, proteins and pathways considered to
be biologically important along with potentially new results that can be used to
encourage ongoing research. | de |
dc.contributor.coReferee | Waack, Stephan Prof. Dr. | |
dc.subject.eng | integrative analysis | de |
dc.identifier.urn | urn:nbn:de:gbv:7-21.11130/00-1735-0000-0005-1397-B-0 | |
dc.affiliation.institute | Fakultät für Mathematik und Informatik | de |
dc.subject.gokfull | Informatik (PPN619939052) | de |
dc.identifier.ppn | 1698092032 | |