Alexis Boukouvalas

The paper introduces GPcounts, a non-parametric method for modeling temporal and spatial counts data in RNA-seq using a negative binomial likelihood, showing improved performance over Gaussian and Poisson models.

OscoNet improves upon Oscope by providing a statistical criterion for selecting oscillatory genes and a more accurate pseudo-time estimation method.

GrandPrix improves the Bayesian GPLVM for single-cell data by scaling it to large datasets and enabling pseudotime inference with branching dynamics.

BGP identifies gene-specific branching dynamics in single-cell data using a non-parametric model and demonstrates its effectiveness on synthetic and hematopoiesis data.