#MathOnco Issue 70: immune-tumor interactions, optimal metastatic control, distribution of fitness effects, data integration & population models
This week in
Math Oncology
June 13, 2019 ~ Issue 70
From the editor
#MathOnco friends,
Today's issue contains manuscripts on immune-tumor interactions, optimal metastatic control, distribution of fitness effects, and data integration for interacting population models.
In other news, you may have heard rumors of "medRxiv" - the preprint server for medical/clinical science. You may wish to read this Nature Briefing on what's to come: "MedRxiv launches with beefed up screening processes to allay concerns about risks of publishing unvetted clinical research."
-Jeffrey West
#MathOnco Publications
Learning-accelerated discovery of immune-tumour interactions
Authors: Jonathan Ozik, Nicholson Collier, Randy Heiland, Gary An, Paul Macklin
Numerical optimal control of a size-structured PDE model for metastatic cancer treatment
Authors: JunLiu, Xiang-Sheng Wang
#MathOnco Preprints
Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios
Authors: Marc J Williams, Luiz Zapata, Benjamin Werner, Chris Barnes, Andrea Sottoriva, Trevor A Graham
State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia Development
Authors: Russell C. Rockne, Branciamore, Jing Qi, David Frankhouser, Denis O’Meally, ..., Leo D. Wang, Stephen J. Forman, Nadia Carlesso, Ya-Huei Kuo, Guido Marcucci
Integrating multiple data sources to fit matrix population models for interacting species
Authors: Frédéric Barraquand, Olivier Gimenez
Single-cell information analysis reveals small intra- and large intercellular variations increase cellular information capacity
Authors: Takumi Wada, Mitsutaka Wataya, Masashi Fujii, Ken-ichi Hironaka, ..., Yasuro Furuichi, Yasuko Manabe, Nobuharu L. Fujii, Shinya Kuroda
High-dimensional Bayesian network inference from systems genetics data using genetic node ordering
Authors: Lingfei Wang, Pieter Audenaert, Tom Michoel
Introduction to Algorithmic Biology: Evolution as Algorithm
Artem Kaznatcheev: "I bet with my career: 'Rigorously understanding evolution as a computational process will be one of the most important problems in theoretical biology in the next century. The basics of evolution are many students’ first exposure to “computational thinking” — but we need to finish the thought!'"
#MathOnco - Book of the month
Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
Eric Topol: "Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help."
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