Quantifying the dynamics of acquired treatment resistance and evolutionary herding for the prediction of collateral sensitivity in cancer model systems

Acar, Ahmet
Nichol, Daniel
Thavasu, P
Sagastume, I
Mateos, Jm
Stubbs, M
Burke, R
Maley, C
Banerji, U
Sottoriva, A
The 25th Biennial Congress of the European Association for Cancer Research


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In the cloud-based Internet of Things (IoT) environments, quantifying uncertainty is an important element input to keep the acceptable level of reliability in various configurations. In this paper, we aim to address the pricing model of delivering data over the cloud while taking into consideration the dynamic uncertainty factors such as network topology, transmission/reception energy, nodal charge and power, and computation capacity. These uncertainty factors are mapped to different nodes with varying capa...
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The amount of total and relative sway of a framed or a composite (frame-shear wall) building is of utmost importance in assessing the seismic resistance of the building. Therefore, the design engineer must calculate the sway profile of the building several times during the design process. However, it is not a simple task to calculate the sway of a three-dimensional structure. Of course, computer programs can do the job, but developing the three-dimensional model becomes necessary, which is obviously tedious...
Citation Formats
A. Acar et al., “Quantifying the dynamics of acquired treatment resistance and evolutionary herding for the prediction of collateral sensitivity in cancer model systems,” presented at the The 25th Biennial Congress of the European Association for Cancer Research, Amsterdam, Hollanda, 2018, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/89505.