Transient power-law behaviour following induction distinguishes between competing models of stochastic gene expression
What features of transcription can be learnt by fitting mathematical models of gene
expression to mRNA count data? Given a suite of models, fitting to data selects an optimal …
expression to mRNA count data? Given a suite of models, fitting to data selects an optimal …
[HTML][HTML] scCensus: Off-target scRNA-seq reads reveal meaningful biology
Single-cell RNA-sequencing (scRNA-seq) provides unprecedented insights into cellular
heterogeneity. Although scRNA-seq reads from most prevalent and popular tagged-end …
heterogeneity. Although scRNA-seq reads from most prevalent and popular tagged-end …
[HTML][HTML] Forseti: A mechanistic and predictive model of the splicing status of scRNA-seq reads
Results: We develop Forseti, a predictive model to probabilistically assign a splicing status
to scRNA-seq reads. Our model has two key components. First, we train a binding affinity …
to scRNA-seq reads. Our model has two key components. First, we train a binding affinity …
Joint distribution of nuclear and cytoplasmic mRNA levels in stochastic models of gene expression: analytical results and parameter inference
Stochastic models of gene expression are routinely used to explain large variability in
measured mRNA levels between cells. These models typically predict the distribution of the …
measured mRNA levels between cells. These models typically predict the distribution of the …