This week in MathOnco 236
Cancer etiology, traveling waves, reinforcement learning, precision oncology, and more
“This week in Mathematical Oncology” — Dec. 8, 2022
> mathematical-oncology.org
From the editor:
Today we feature articles on cancer etiology, traveling waves, reinforcement learning, precision oncology, and more.
In other exciting news: there is an opening for a postdoc in my lab (see link below), along with a few other jobs & meetings posted, too.
Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
“You do not rise to the level of your goals. You fall to the level of your systems.”
— J. Clear (Atomic Habits)
Traveling wave speed and profile of a “go or grow” glioblastoma multiforme model
Aisha Tursynkozha, Ardak Kashkynbayev, Bibinur Shupeyeva, Erica M. Rutter, Yang KuangModel enhanced reinforcement learning to enable precision dosing: A theoretical case study with dosing of propofol
Benjamin Ribba, Dominic Stefan Bräm, Paul Gabriel Baverel, Richard Wilson PeckEvaluating cancer etiology and risk with a mathematical model of tumor evolution
Sophie Pénisson, Amaury Lambert, Cristian TomasettiPhase I study of a novel glioblastoma radiation therapy schedule exploiting cell-state plasticity
Jamie A Dean, Shyam K Tanguturi, Daniel Cagney, Kee-Young Shin, …, Paul Catalano, Daphne Haas-Kogan, Brian M Alexander, Franziska MichorSpatially aware dimension reduction for spatial transcriptomics
Lulu Shang & Xiang ZhouTen Simple Rules for Better Figures
Nicolas P. Rougier, Michael Droettboom, Philip E. BourneExtrinsic cell death pathway plasticity: a driver of clonal evolution in cancer?
Eric Seidel & Silvia von KarstedtEarly-career setback and future career impact
Yang Wang, Benjamin F. Jones & Dashun WangThe coming decade in precision oncology: six riddles
Adam Wahida, Lars Buschhorn, Stefan Fröhling, Philipp J. Jost, Andreas Schneeweiss, Peter Lichter & Razelle KurzrockModeling age-specific incidence of colon cancer via niche competition
Steffen Lange, Richard Mogwitz, Denis Hünniger, Anja Voß-Böhme
Tumor containment for Norton-Simon models
Frank Alvarez, Yannick ViossatMathematical Modeling of Leukemia Chemotherapy in Bone Marrow
Ana Niño-López, Salvador Chulián, Álvaro Martínez-Rubio, Cristina Blázquez-Goñi, María RosaOrthogonal Multi-frequency Fusion Based Image Reconstruction and Diagnosis in Diffuse Optical Tomography
Hanene Ben Yedder, Ghassan Hamarneh, Ben Cardoen
Maths + Cancer
A Podcast from the University of Oxford
Hosted by Dr Vicky Neale: “Exploring how maths and stats help with cancer prevention, diagnosis and treatment – and the stories behind the researchers making it happen.“
The newsletter now has a dedicated homepage where we post the cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group. This week’s artwork:
Based on the paper: “Inferring parameters of cancer evolution in chronic lymphocytic leukemia” in PLoS Comput Biol
Artist: Nathan Lee
Caption: "This is an abstract visual representation of a Monte Carlo simulation of carcinogenesis, similar to simulations we used in our recent paper where we reconstruct the evolutionary history of liquid cancers, including when cancer was initiated and when subsequent driver mutations occurred. Before applying our methods to clinical data, we evaluated them on simulated cancers. To generate this image, I perform a Monte Carlo simulation with birth, death, and mutation to generate a population of 600 cells. The first cell starts with no mutations, and its wild-type state is represented by a square. Upon each mutation, I sample from a distribution to determine that square’s “genotype,” or the noise added to each corner. The effect of new mutations is added to the existing genotype of each square. The opacity of each polygon is determined by the total number of mutations accumulated by the cell."
Visit the mathematical oncology page to view jobs, meetings, and special issues. We will post new additions here, but the full list can found at mathematical-oncology.org.
1. Jobs
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