New modelling, statistics, and experiments show that cellular populations of mitochondrial DNA (mtDNA) evolve during development according to solvable stochastic dynamics involving binomial partitioning and random turnover, facilitating a predictive and quantitative theory of the mtDNA bottleneck.
New methods reveal that complex local splicing variations are more prevalent in animals than previously appreciated, and demonstrate that local splicing variations are relevant for studies of development, gene regulation and neurodegenerative diseases.
Publication bias, in which positive results are preferentially reported by authors and published by journals, can restrict the visibility of evidence against false claims and allow such claims to be canonized inappropriately as facts.
A simulation study is used to demonstrate how mistakes in identifying the experimental unit and the unit of analysis can lead to incorrect analyses and inappropriate inferences when reporting research studies.
Computational modeling and analysis of mouse neural population data finds that the excitation/inhibition imbalance theory of brain disorders is too limited to account for key changes in neural activity statistics.