ArticleThe annals of applied statistics2009
A branching process model for flow cytometry and budding index measurements in cell synchrony experiments.
Article in The annals of applied statistics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Cell cycle-dependent protein dynamics in budding yeast resolved by deconvolution of bulk proteomics.Molecular systems biology · 2026Article
- Competitive resource allocation drives asynchronous and rapid nuclear multiplication in the malaria parasite.Nature communications · 2026Article
- Comprehensive profiling of chromatin occupancy dynamics through the cell cycle.Nucleic acids research · 2026Article
- Probabilistic modeling of cell cycle dynamics in response to cell cycle targeting chemotherapy drugs to guide treatment strategies.PLoS computational biology · 2025Article
- Connecting virulence pathways to cell-cycle progression in the fungal pathogen Cryptococcus neoformans.Current genetics · 2017Review
- Investigating Conservation of the Cell-Cycle-Regulated Transcriptional Program in the Fungal Pathogen, Cryptococcus neoformans.PLoS genetics · 2016Article
- Branching process deconvolution algorithm reveals a detailed cell-cycle transcription program.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- Cell cycle regulated interaction of a yeast Hippo kinase and its activator MO25/Hym1.PloS one · 2013Article
- A generalized model for multi-marker analysis of cell cycle progression in synchrony experiments.Bioinformatics (Oxford, England) · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
We present a flexible branching process model for cell population dynamics in synchrony/time-series experiments used to study important cellular processes. Its formulation is constructive, based on an accounting of the unique cohorts in the population as they arise and evolve over time, allowing it to be written in closed form. The model can attribute effects to subsets of the population, providing flexibility not available using the models historically applied to these populations. It provides a tool for in silico synchronization of the population and can be used to deconvolve population-level experimental measurements, such as temporal expression profiles. It also allows for the direct comparison of assay measurements made from multiple experiments. The model can be fit either to budding index or DNA content measurements, or both, and is easily adaptable to new forms of data. The ability to use DNA content data makes the model applicable to almost any organism. We describe the model and illustrate its utility and flexibility in a study of cell cycle progression in the yeast Saccharomyces cerevisiae.
Identifiers
What OpenQuestion holds
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.