Results - Details
Search command : Author="Νικολάου"
And Author="Μαρία"
Current Record: 8 of 18
|
Identifier |
000419430 |
Title |
Learning pathway dynamics from single-cell proteomic data |
Alternative Title |
Μάθηση δυναμικών βιολογικών μονοπατιών από single cell δεδομένα |
Author
|
Βέρρου, Κλειώ-Μαρία
|
Thesis advisor
|
Τσαμαρδίνος, Ι
Νικολάου, Χ.
Στρουμπούλης, Ι
|
Abstract |
Single-cell platforms provide data with statistically large samples of snapshot observations capable
of resolving intercellular heterogeneity. Currently, there is a growing literature on algorithms
that exploit this attribute in order to infer the trajectory of biological mechanisms, such as cell proliferation
and differentiation. The trajectory inference methodology has not yet been used to address
the challenging problem of learning the dynamics of signaling protein systems. In this work
we assess this prospect. We test the performance of this novel class of methods on two of proteomic
temporal datasets that were produced using different signaling perturbations on the same
population of cells. To evaluate the learning quality we employ four different evaluation metrics
that quantify the performance of each algorithm according to (a) the biological meaning of the
output, (b) the robustness, (c) the correlation with the initial dataset and (d) the roughness of the
phosphorylation levels though the biological time. We show that experimental time alone is insufficient
to provide knowledge about the order of proteins during signal transduction. Accordingly,
we show that the inferred trajectories provide richer information about the underlying dynamics.
Our results also highlight that none of the already developed algorithms is universally applicable
to this problem because the learning quality highly depends on the signaling perturbation.
|
Language |
English |
Subject |
Mass cytometry |
|
Proteomics |
|
Ψευδοχρόνος |
Issue date |
2018-12-05 |
Collection
|
School/Department--School of Medicine--Department of Medicine--Post-graduate theses
|
|
Type of Work--Post-graduate theses
|
Permanent Link |
https://elocus.lib.uoc.gr//dlib/4/e/b/metadata-dlib-1543577806-995359-30058.tkl
|
Views |
307 |