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This week in MathOnco 226
Subclonal interactions, variant allele frequencies, big data, evolutionary trajectories
“This week in Mathematical Oncology” — Sept. 8, 2022
From the editor:
Today we feature articles on subclonal interactions, variant allele frequencies, big data, evolutionary trajectories.
“A mathematician, like a painter or poet, is a maker of patterns.”
-G. H. Hardy
Embracing Project Optimus: Can we Leverage Evolutionary Theory to Optimize Dosing in Oncology?
Timothy Qi, Tyler Dunlap, Yanguang Cao
Quantification of spatial subclonal interactions enhancing the invasive phenotype of pediatric glioma
Haider Tari, Ketty Kessler, Nick Trahearn, Benjamin Werner, Maria Vinci, Chris Jones, Andrea Sottoriva
Progenitor hierarchy of chronic myelomonocytic leukemia identifies inflammatory monocytic-biased trajectory linked to worse outcomes
Meghan C. Ferrall-Fairbanks, Abhishek Dhawan, Brian Johnson, Hannah Newman, …, Jing Zhang, Rafael Bejar, Philipp M. Altrock, Eric Padron
Distinguishing excess mutations and increased cell death based on variant allele frequencies
Gergely Tibély, Dominik Schrempf, Imre Derényi, Gergely J. Szöllősi
The adaptive potential of nonheritable somatic mutations
Paco Majic, E. Yagmur Erten, Joshua L Payne
Most cancers carry a substantial deleterious load due to Hill-Robertson interference
Susanne Tilk, Svyatoslav Tkachenko, Christina Curtis, Dmitri A Petrov, Christopher D McFarland
Big data in basic and translational cancer research
Peng Jiang, Sanju Sinha, Kenneth Aldape, Sridhar Hannenhalli, Cenk Sahinalp, Eytan Ruppin
Inferring protein fitness landscapes from laboratory evolution experiments
Sameer D'Costa, Emily C Hinds, Chase R. Freschlin, Hyebin Song, Philip A Romero
Predicting anti-cancer drug synergy using extended drug similarity profiles
Sayed-Rzgar Hosseini, Xiaobo Zhou
Identifiability and inference of phylogenetic birth-death models
Brandon Legried, Jonathan Terhorst
Evolutionary states and trajectories characterized by distinct pathways stratify ovarian high-grade serous carcinoma patients
Alexandra Lahtinen, Kari Lavikka, Yilin Li, Anni Virtanen, …, Antti Häkkinen, Johanna Hynninen, Jaana Oikkonen, Sampsa Hautaniemi
National Institutes of Health
iCite is a tool to access a dashboard of bibliometrics for papers associated with a portfolio. Users type in a PubMed query or upload the PubMed IDs of articles of interest. iCite has three modules: Influence, Translation, and Open Citations.
Influence provides Relative Citation Ratio (RCR) values, which measure the scientific influence of each paper by field- and time-adjusting the citations it has received, and benchmarking to the median for NIH publications.
Translation measures how Human, Animal, or Molecular/Cellular Biology-oriented each paper is, and uses this information to track and predict citation by clinical articles.
Citations disseminates link-level, public-domain citation data from the NIH Open Citation Collection (NIH-OCC).
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. This week’s artwork:
Based on the paper: “Homeostasis limits keratinocyte evolution” in PNAS
Artist: Ryan Schenck (@research_junkie)
Caption: “This artistic representation of somatic clonal architecture of 2D tissue accompanies our recent publication on evolutionary dynamics of somatic mutational events within the epidermis. The artwork pays homage to the Sonoran Desert spanning parts of southern AZ, CA, and northern Mexico. It is home to the distinctive Saguaro cactus, a cactus whose mere silhouette evokes imagery of vast openness, cracked earth, rock, and expansive skies weathered by time through wind and water. I represent this using Voronoi tessellations whose color represents the expanding subclones as we age, depicted on the desert floor and within the body silhouettes of the child, adult, and elderly. The artwork was created using SciPy, Matplotlib, Adobe Illustrator, and Adobe Photoshop. The code for the base components can be found on my GitHub.”
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