@colincess

Computational biologist in search of a postdoc

Joined May 2018
  • Tweets5
  • Following35
  • Followers45
Preprint with @USCSysBio_Lab now out! “Fitting agent-based models to tumor images using representation learning” biorxiv.org/content/10.1101/…

Fitting agent-based models to tumor images using representation learning

Agent-based models (ABMs) have enabled great advances in the study of tumor development and therapeutic response, allowing researchers to explore the spatiotemporal evolution of the tumor and its...

biorxiv.org
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Colin Cess (@colincess ) Stacey Finley (@USCSysBio_Lab) describe a new method to compare computational outputs in our latest post: mathematical-oncology.org/bl…
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excited to share the lab’s latest preprint from @colincess ! we developed a way to represent complex model outputs as a simple quantitative value, making it easy to compare simulation results.
Colin Cess@colincess16 Aug 2022
Preprint out! “Siamese neural networks for a generalized, quantitative comparison of complex model outputs” arxiv.org/abs/2208.06530

Representation learning for a generalized, quantitative comparison...

Computational models are quantitative representations of systems. By analyzing and comparing the outputs of such models, it is possible to gain a better understanding of the system itself. Though...

arxiv.org
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Preprint out! “Siamese neural networks for a generalized, quantitative comparison of complex model outputs” arxiv.org/abs/2208.06530

Representation learning for a generalized, quantitative comparison...

Computational models are quantitative representations of systems. By analyzing and comparing the outputs of such models, it is possible to gain a better understanding of the system itself. Though...

arxiv.org
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first time presenting this exciting new work from @colincess! he will have to do a #tweetorial when the paper comes out! #mathonco
Sandy Anderson@ara_anderson3 Dec 2020
Replying to @ara_anderson
Stacey now shows cool just accepted work in @PLOSCompBiol on modeling the tumor-immune ecosystem at the tissue scale. Love the idea of using a feed forward network to make macrophage state decisions facilitating a massive speed up in computational time!
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