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Proliferating active matter
The fascinating patterns of collective motion created by autonomously driven particles have
fuelled active-matter research for over two decades. So far, theoretical active-matter …
fuelled active-matter research for over two decades. So far, theoretical active-matter …
The 2019 mathematical oncology roadmap
Whether the nom de guerre is Mathematical Oncology, Computational or Systems Biology,
Theoretical Biology, Evolutionary Oncology, Bioinformatics, or simply Basic Science, there is …
Theoretical Biology, Evolutionary Oncology, Bioinformatics, or simply Basic Science, there is …
Spatial heterogeneity and evolutionary dynamics modulate time to recurrence in continuous and adaptive cancer therapies
Abstract Treatment of advanced cancers has benefited from new agents that supplement or
bypass conventional therapies. However, even effective therapies fail as cancer cells deploy …
bypass conventional therapies. However, even effective therapies fail as cancer cells deploy …
Quantification of subclonal selection in cancer from bulk sequencing data
Subclonal architectures are prevalent across cancer types. However, the temporal
evolutionary dynamics that produce tumor subclones remain unknown. Here we measure …
evolutionary dynamics that produce tumor subclones remain unknown. Here we measure …
Chemotaxis as a navigation strategy to boost range expansion
Bacterial chemotaxis, the directed movement of cells along gradients of chemoattractants, is
among the best-characterized subjects in molecular biology,,,,,,,,–, but much less is known …
among the best-characterized subjects in molecular biology,,,,,,,,–, but much less is known …
Subclonal reconstruction of tumors by using machine learning and population genetics
Most cancer genomic data are generated from bulk samples composed of mixtures of cancer
subpopulations, as well as normal cells. Subclonal reconstruction methods based on …
subpopulations, as well as normal cells. Subclonal reconstruction methods based on …
Computational approaches to modelling and optimizing cancer treatment
Computational models can be applied to optimize treatment schedules and model treatment
responses in cancer therapy. In this Review, we provide an overview of such computational …
responses in cancer therapy. In this Review, we provide an overview of such computational …
Exploiting evolutionary steering to induce collateral drug sensitivity in cancer
Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer
therapy today. However, evolving resistance to one drug may come at a cost of decreased …
therapy today. However, evolving resistance to one drug may come at a cost of decreased …
Chromosomal copy number heterogeneity predicts survival rates across cancers
Survival rates of cancer patients vary widely within and between malignancies. While
genetic aberrations are at the root of all cancers, individual genomic features cannot explain …
genetic aberrations are at the root of all cancers, individual genomic features cannot explain …
A theoretical analysis of tumour containment
Recent studies have shown that a strategy aiming for containment, not elimination, can
control tumour burden more effectively in vitro, in mouse models and in the clinic. These …
control tumour burden more effectively in vitro, in mouse models and in the clinic. These …