ArticleBioinformatics (Oxford, England)2017
SIApopr: a computational method to simulate evolutionary branching trees for analysis of tumor clonal evolution.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments.BMC bioinformatics · 2022Article
- ESTIpop: a computational tool to simulate and estimate parameters for continuous-time Markov branching processes.Bioinformatics (Oxford, England) · 2020Article
- CellCoal: Coalescent Simulation of Single-Cell Sequencing Samples.Molecular biology and evolution · 2020Article
- Subclonal cooperation drives metastasis by modulating local and systemic immune microenvironments.Nature cell biology · 2019Article
- KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance.Cancer cell · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
summarySIApopr (Simulating Infinite-Allele populations) is an R package to simulate time-homogeneous and inhomogeneous stochastic branching processes under a very flexible set of assumptions using the speed of C ++. The software simulates clonal evolution with the emergence of driver and passenger mutations under the infinite-allele assumption. The software is an application of the Gillespie Stochastic Simulation Algorithm expanded to a large number of cell types and scenarios, with the intention of allowing users to easily modify existing models or create their own. AVAILABILITY AND IMPLEMENTATION: SIApopr is available as an R library on Github ( https://github.com/olliemcdonald/siapopr ). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: michor@jimmy.harvard.edu.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.