This week in MathOnco 161

Tumor-immune dynamics, cancer origins, metastatic clusters, reinforcement learning chemo

“This week in Mathematical Oncology” — Newsletter
May. 6, 2021
From the editor:

Summary of contents:

  1. Quantitative mapping of individual voxels in the peritumoral region of IDH-wildtype glioblastoma to distinguish between tumor infiltration and edema
    Archya Dasgupta, Benjamin Geraghty, Pejman Jabehdar Maralani, Nauman Malik, …, James Perry, Angus Lau, Arjun Sahgal, Gregory Czarnota

  2. Exploring the dynamics of a tumor-immune interplay with time delay
    Mrinmoy Sardar, Subhas Khajanchi, Santosh Biswas, Sayed F. Abdelwahab, Kottakkaran Sooppy Nisar

  1. Cluster Size Distribution of Cells Disseminating from a Primary Tumor
    Mrinmoy Mukherjee, Herbert Levine

  2. Spatial analysis of tumor infiltrating lymphocytes based on deep learning using histopathology image to predict progression-free survival in colorectal cancer
    Hongming Xu, Yoon Jin Cha, Jean R. Clemenceau, Jinhwan Choi, Sung Hak Lee, Jeonghyun Kang, Tae Hyun Hwang

  3. Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy
    Brydon Eastman, Michelle Przedborski, Mohammad Kohandel

  4. Attribution of Cancer Origins to Endogenous, Exogenous, and Actionable Mutational Processes
    Vincent L. Cannataro, Jeffrey D. Mandell, Jeffrey P. Townsend

  5. Distortion Discovery: A Framework to Model, Spot and Explain Tumor Heterogeneity and Mitigate its Negative Impact on Cancer Risk Assessment
    Dalia Elmansy

1. A field guide to cultivating computational biology
The Mathematical Oncology Blog

Elana Fertig: “Computational biology is a transdisciplinary field, spanning expertise in mathematics, computer science, informatics, statistics, data science, and engineering. Investigators also employ numerous models to research, and are most commonly engaged in team science research. In spite of the major advances and healthy culture of computational biology, academic incentive structures often cause many interdisciplinary investigators to languish in career development. [W]e outline solutions to solve the structural barriers to attract and cultivate computational biologists.”

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