#MathOnco Issue 115: early detection, mechanistic models, Bayesian inference, tumor spheroids, web browser CA simulations, and more.
This week in
Math Oncology
May 14, 2020 ~ Issue 115
From the editor
Dear Readers,
This might be one of my favorite issues, with so many interesting articles. We have the following topics: early detection, mechanistic models, Bayesian inference, tumor spheroids, web browser CA simulations, and more. Cool stuff!
Enjoy,
-Jeffrey West
#MathOnco Publications
The challenge of early detection in cancer (Perspective)
Authors: Nora Pashayan, Paul D. P. Pharoah
Tools and Concepts for Interrogating and Defining Cellular Identity
Authors: Kara L. McKinley, David Castillo-Azofeifa, Ophir D. Klein
Mechanistic Learning for Combinatorial Strategies With Immuno-oncology Drugs: Can Model-Informed Designs Help Investigators?
Authors: Joseph Ciccolini, Dominique Barbolosi, Nicolas André, Fabrice Barlesi, Sébastien Benzekry
A hybrid model of tumor growth and angiogenesis: In silico experiments
Authors: Caleb M. Phillips, Ernesto A. B. F. Lima, Ryan T. Woodall, Amy Brock, Thomas E. Yankeelov
A Random Matrix Theory Approach to Denoise Single-Cell Data
Authors: Luis Aparicio, Mykola Bordyuh, Andrew J. Blumberg, Raul Rabadan
#MathOnco Preprints
Artistoo: build, share, and explore simulations of cells and tissues in the web browser
Authors: Inge M. N. Wortel, Johannes Textor
Why is cyclic dominance so rare?
Authors: Hye Jin Park, Yuriy Pichugin, Arne Traulsen
Comparison of drug inhibitory effects (IC50) in monolayer and spheroid cultures
Authors: Catherine Berrouet, Naika Dorilas, Katarzyna A. Rejniak, Necibe Tuncer
Single cell fitness landscapes induced by genetic and pharmacologic perturbations in cancer
Authors: Sohrab Salehi, Farhia Kabeer, Nicholas Ceglia, Mirela Andronescu, ..., Andrew McPherson, Alexandre Bouchard-Côté, Samuel Aparicio, Sohrab P Shah
Efficient Bayesian inference of phylogenetic trees from large scale, low-depth genome-wide single-cell data
Authors: Fatemeh Dorri, Sohrab Salehi, Kevin Chern, Tyler Funnell, ..., Samuel Aparicio, Andrew Roth, Sohrab Shah, Alexandre Bouchard-Côté
Descriptive and prognostic value of a computational model of metastasis in high-risk neuroblastoma
Authors: Sebastien Benzekry, Coline Sentis, Carole Coze, Laetitia Tessonnier, Nicolas Andre
Bayesian combination of mechanistic modeling and machine learning (BaM3): improving clinical tumor growth predictions
Authors: Pietro Mascheroni, Juan Carlos López Alfonso, Michael Meyer-Hermann, Haralampos Hatzikirou
Exploiting evolutionary steering to induce collateral drug sensitivity in cancer
The Mathematical Oncology Blog
Dan Nichol: "The evolution of drug resistance is the ultimate driver of late stage cancer mortality. Rapid tumour growth and genetic instability yield genetically and phenotypically heterogeneous cancer cell populations that harbour subclones resistant to our presently most effective therapies. Drug treatments initially induce cell death and tumour shrinkage, but resistant clones survive and drive the recurrence of refractory disease. Any effective drug treatment for late stage cancer needs to contend with this ubiquitous evolutionary process. Consequently, evolutionary treatment strategies such as adaptive therapy and collateral sensitivity have seen extensive study over the last 15 years."
Artistoo: Build. Share. Explore. "Artistoo (Artificial Tissue Toolbox, formerly called CPMjs) is a framework that lets you build interactive, explorable simulation models of cells and tissues in the web browser." Free textbooks during Covid-19
Springer: As a response to Covid-19, Springer Link is offering several hundred books (in PDF format) for FREE. Relevant titles include:
Stability and Control of Linear Systems
Applied Bioinformatics
Neural Networks and Deep Learning
The A-Z of the PhD Trajectory
Data Science and Predictive Analytics
... and more!
#MathOnco - Book of the month
The Art of Theoretical Biology
Franziska Matthäus, Sebastian Matthäus, Sarah Harris, Thomas Hillen: "This beautifully crafted book collects images, which were created during the process of research in all fields of theoretical biology. Data analysis, numerical treatment of a model, or simulation results yield stunning images, which represent pieces of art just by themselves. The approach of the book is to present for each piece of visualization a lucid synopsis of the scientific background as well as an outline of the artistic vision."
Jobs
NEW: Research Associate, Postdoc, and Research Faculty positions – Mathematical Oncology (Russ Rockne)
Computational Approaches to Breast Cancer Evolution - Postdoc (Marc Ryser)
Pre-leukemic Dynamics – MSc or PhD Studentship (Morgan Craig)
Math/statistical models of stem cell lineage dynamics and cancer genomics - Postdoc (Adam MacLean)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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