This week in MathOnco 222
Luria-Delbrück, spatial structures, lineage tracing, neoadjuvant chemo, mutation accumulation, and more…
“This week in Mathematical Oncology” — Aug. 11, 2022
> mathematical-oncology.org
From the editor:
Today we feature articles on Luria-Delbrück, spatial structures, lineage tracing, neoadjuvant chemo, mutation accumulation, and more.
Today’s cover artwork features another scientific newsletter, “Hot Topics in ML+Bio” written by Jacob Pettit — please consider subscribing today.
Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
"Evolution forms the first principles of all cancer biology."
- Bob Gatenby
Estimating the transfer rates of bacterial plasmids with an adapted Luria–Delbrück fluctuation analysis
Olivia Kosterlitz, Adamaris Muñiz Tirado, Claire Wate, Clint Elg, Ivana Bozic, Eva M. Top, Benjamin KerrThe role of spatial structures of tissues in cancer initiation dynamics
Cade B Spaulding, Hamid Teimouri, Anatoly B KolomeiskyA quantification method of somatic mutations in normal tissues and their accumulation in pediatric patients with chemotherapy
Sho Ueda, Satoshi Yamashita, Miho Nakajima, Tadashi Kumamoto, …, Yuichi Shiraishi, Masayuki Noguchi, Yukio Sato, Toshikazu Ushijima“Fateful” encounter: Lineage tracing meets phylogeny to unravel mysteries of cancer progression
Wing Hing Wong, Christina CurtisMRI-based digital models forecast patient-specific treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer
Chengyue Wu, Angela M. Jarrett, Zijian Zhou, Nabil Elshafeey,…, Jong Bum Son, Jingfei Ma, Gaiane M. Rauch, Thomas E. YankeelovGrowth dynamics of breast cancer stem cells: effects of self-feedback and EMT mechanisms
Liuyong Pang, Sanhong Liu, Zhong Zhao, Tianhai Tian, Xinan Zhang, Qiuying Li
Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience
Marwan Abdellah, Juan José García Cantero, Nadir Román Guerrero, Alessandro Foni, …, Pierre J. Magistretti, Henry Markram, Felix SchürmannEvolution and spread of multidrug resistant pathogens in a spatially heterogeneous environment
Quentin Griette, Matthieu Alfaro, Gaël Raoul, Sylvain GandonAllopatric divergence of cooperators confers cheating resistance and limits the effects of a defector mutation
Kaitlin A. Schaal, Yuen-Tsu Nicco Yu, Marie Vasse, Gregory J. VelicerBernstein polynomial approximation of fixation probability in finite population evolutionary games
Jiyeon Park, Paul NewtonMutation accumulation in exponentially growing populations
Michael D. Nicholson, David Cheek, Tibor Antal
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.
Jacob Pettit"‘s “Hot Topics in ML+Bio” newsletter showcases papers, research and news focusing on the fields of Machine Learning and ML for biology. Subscribe today!
Caption: “Are you interested in the interplay between machine learning and biology? I recently launched “Hot Topics in ML+Bio”, a weekly newsletter in which I try to collect papers and research relating to fields of Machine Learning and ML for biology. Thinking about the similarities between these two fields, I was inspired to create this artwork. The animated shape on the bottom of the screen represents the dynamic nature of a probability distribution, the grid represents a cell grid/lattice as is used in some simulations, the translucent circle and its contents is a stylized representation of a cell and its organelles, while the dot grid in the upper left is another visualization of a cell grid and the color-changing circle overlaying it represents the changing nature of a cell membrane. To make this image I used the Canva tool which has a large library of shapes and animations to pull from.”
Created by: Jacob Pettit (@pettitjf)
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