#MathOnco Issue 82: estimating heterogeneity, microenvironmental models, oncolytic virotherapy, brain mets, and immune-mediated mets.
This week in
Math Oncology
Sept. 12, 2019 ~ Issue 82
From the editor
#MathOnco friends,
Now that summer is over, it seems that math oncology is back in full force. The issue below is jam-packed with exciting articles in topics like estimating heterogeneity, microenvironmental models, oncolytic virotherapy, brain metastasis, and immune-mediated metastasis.
Many of you will be interested to know that registration is open for the 9th annual Integrated Mathematical Oncology (IMO) workshop at the Moffitt Cancer Center. The IMO Workshop is chaired and organized by the IMO Department Chair, Sandy Anderson. This year's theme: Tumor Board Evolution.
-Jeffrey West
#MathOnco Publications
Quantitative mathematical modeling of clinical brain metastasis dynamics in non-small cell lung cancer
Authors: M. Bilous, C. Serdjebi, A. Boyer, P. Tomasini, C. Pouypoudat, D. Barbolosi, F. Barlesi, F. Chomy, S. Benzekry
Critical behavior of spatial networks as a model of paracrine signaling in tumorigenesis
Authors: Philip Tee, Allan Balmain
Mathematical Modeling of Oncolytic Virotherapy
Authors: Johannes P. W. Heidbuechel, Daniel Abate-Daga, Christine E. Engeland, Heiko Enderling
A mathematical model for the immune-mediated theory of metastasis
Authors: AdamRhodes, Thomas Hillen
Clonal evolution of acute myeloid leukemia from diagnosis to relapse
Authors: Sebastian Vosberg, Philipp A. Greif
Prediction of PD-L1 Expression in Neuroblastoma via Computational Modeling
Authors: Salvo Danilo Lombardo, Mario Presti, Katia Mangano, Maria Cristina Petralia, Maria Sofia Basile, Massimo Libra, Saverio Candido, Paolo Fagone, Emanuela Mazzon, Ferdinando Nicoletti, Alessia Bramanti
#MathOnco Preprints
Data-based RNA-seq Simulations by Binomial Thinning
Authors: David Gerard
A Monte Carlo method to estimate cell population heterogeneity
Authors: Ben Lambert, David J. Gavaghan, Simon Tavener
Estimating growth patterns and driver effects in tumor evolution from individual samples
Authors: Leonidas Salichos, William Meyerson, Jonathan Warrell, Mark Gerstein
Why is cancer not more common? A changing microenvironment may help to explain why, and suggests strategies for anti-cancer therapy
Authors: Xiaowei Jiang, Ian P.M. Tomlinson
#MathOnco - Book of the month
An Editor's Guide to Writing and Publishing Science
Michael Hochberg: "Publishing is rapidly changing, and needs to be explained with a fresh perspective. Simply writing good, clear, concise, science is no longer enough-there is a different mind-set now required that students need to adopt if they are to succeed. The purpose of this book is to provide the foundations of this new approach for both young scientists at the start of their careers, as well as for more experienced scientists to teach the younger generation."
Most clicked links of August
A short comment on statistical versus mathematical modelling
Mathematical Models of Cancer: When to Predict Novel Therapies, and When Not to
Jobs
Math/statistical models of stem cell lineage dynamics and cancer genomics - Postdoc (Adam MacLean)
Data-driven modeling of breast cancer metastasis - Postdoc (Paul Macklin)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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