This week in MathOnco 183

Radiation-immune dynamics, plasticity, cultivating computational biology, immunotherapy resistance hallmarks, metabolic scaling theory

“This week in Mathematical Oncology” — Oct. 14, 2021
> mathematical-oncology.org
From the editor:

This week’s edition includes radiation-immune dynamics, plasticity, cultivating computational biology, immunotherapy resistance hallmarks, metabolic scaling theory, and many more exciting manuscripts.

Scroll down for a ton of new job, conference/workshop postings!

Enjoy!

Jeffrey West
jeffrey.west@moffitt.org

  1. Systems-level network modeling deciphers the master regulators of phenotypic plasticity and heterogeneity in melanoma
    Maalavika Pillai, Mohit Kumar Jolly

  2. A field guide to cultivating computational biology
    Gregory P. Way, Casey S. Greene, Piero Carninci, Benilton S. Carvalho, …, Fabian J. Theis, Jean Y. H. Yang, Anne E. Carpenter, Elana J. Fertig

  3. Hallmarks of response, resistance, and toxicity to immune checkpoint blockade
    Golnaz Morad, Beth A. Helmink, Padmanee Sharma, Jennifer A. Wargo

  4. Tumor-immune ecosystem dynamics define an individual Radiation Immune Score to predict pan-cancer radiocurability
    Juan C. L. Alfonso, G. Daniel Grass, Eric Welsh, Kamran A. Ahmed, …James J. Mulé, Steven A. Eschrich, Javier F. Torres-Roca, Heiko Enderling

  5. Computational modeling identifies multitargeted kinase inhibitors as effective therapies for metastatic, castration-resistant prostate cancer
    Thomas Bello, Claudia Paindelli, Luis A. Diaz-Gomez, Anthony Melchiorri, Antonios G. Mikos, Peter S. Nelson, Eleonora Dondossola, Taranjit S. Gujral

  6. Informing and Validating Translational Mechanism-Based Models for Antibiotics by Experimental and Computational Approaches
    Jürgen B. Bulitta

  7. Cancer as a Model System for Testing Metabolic Scaling Theory
    Alexander B. Brummer, Van M. Savage

  1. Mistic: an open-source multiplexed image t-SNE viewer
    Sandhya Prabhakaran, Chandler Gatenbee, Mark Robertson-Tessi, Jeffrey West, Amer A Beg, Jhanelle E Gray, Scott Antonia, Robert A Gatenby, Alexander R. A. Anderson

  2. Constrained optimisation of divisional load in hierarchically-organised tissues during homeostasis
    Peter Ashcroft, Sebastian Bonhoeffer

  3. Chemotherapy-Induced Cachexia and Model-Informed Dosing to Preserve Lean Mass in Cancer Treatment
    Suzan Farhang-Sardroodi, Michael A. La Croix, Kathleen P. Wilkie

  4. A model for the intrinsic limit of cancer therapy: duality of treatment-induced cell death and treatment-induced stemness
    Erin Angelini, Yue Wang, Joseph Xu Zhou, Hong Qian, Sui Huang

  5. Uncovering expression signatures of synergistic drug response using an ensemble of explainable AI models
    Joseph D Janizek, Ayse Berceste Dincer, Safiye Celik, Hugh Chen, William Chen, Kamila Naxerova, Su-In Lee

  1. Slowed canonical progress in large fields of science
    Proceedings of the National Academy of Sciences
    Johan S. G. Chu & James A. Evans: “The size of scientific fields may impede the rise of new ideas. Examining 1.8 billion citations among 90 million papers across 241 subjects, we find a deluge of papers does not lead to turnover of central ideas in a field, but rather to ossification of canon.”

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Caption: Gene regulatory networks can explain the existence of multiple phenotypes observed in melanoma. Simulated gene expression based on these networks show that the four experimentally identified phenotypes (Melanocytic, Transitory, Neural Crest-like and Undifferentiated) are a result of further classification of the two broader "macro" states that form the proliferative and invasive phenotypes. These four states can further be subdivided into an ensemble of smaller "micro" states (represented within the circles) which possibly contribute to the high degree of heterogeneity seen within melanoma tumors. To find out more, read our paper here.

Created by: Atchuta Srinivas Duddu

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