Principles and challenges of modeling temporal and spatial omics data
Studies with temporal or spatial resolution are crucial to understand the molecular dynamics
and spatial dependencies underlying a biological process or system. With advances in high …
and spatial dependencies underlying a biological process or system. With advances in high …
Computational analyses of mechanism of action (MoA): data, methods and integration
The elucidation of a compound's Mechanism of Action (MoA) is a challenging task in the
drug discovery process, but it is important in order to rationalise phenotypic findings and to …
drug discovery process, but it is important in order to rationalise phenotypic findings and to …
Spatial profiling of early primate gastrulation in utero
Gastrulation controls the emergence of cellular diversity and axis patterning in the early
embryo. In mammals, this transformation is orchestrated by dynamic signalling centres at the …
embryo. In mammals, this transformation is orchestrated by dynamic signalling centres at the …
SpatialDE: identification of spatially variable genes
Technological advances have made it possible to measure spatially resolved gene
expression at high throughput. However, methods to analyze these data are not established …
expression at high throughput. However, methods to analyze these data are not established …
Esrrb guides naive pluripotent cells through the formative transcriptional programme
During embryonic development, naive pluripotent epiblast cells transit to a formative state.
The formative epiblast cells form a polarized epithelium, exhibit distinct transcriptional and …
The formative epiblast cells form a polarized epithelium, exhibit distinct transcriptional and …
Protein biogenesis machinery is a driver of replicative aging in yeast
An integrated account of the molecular changes occurring during the process of cellular
aging is crucial towards understanding the underlying mechanisms. Here, using novel …
aging is crucial towards understanding the underlying mechanisms. Here, using novel …
Multitask Gaussian processes for multivariate physiological time-series analysis
Gaussian process (GP) models are a flexible means of performing nonparametric Bayesian
regression. However, GP models in healthcare are often only used to model a single …
regression. However, GP models in healthcare are often only used to model a single …
Chromatin map** and single-cell immune profiling define the temporal dynamics of ibrutinib response in CLL
The Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for patients
with chronic lymphocytic leukemia (CLL), despite extensive heterogeneity in this disease. To …
with chronic lymphocytic leukemia (CLL), despite extensive heterogeneity in this disease. To …
Computational approaches for interpreting sc RNA‐seq data
The recent developments in high‐throughput single‐cell RNA sequencing technology (sc
RNA‐seq) have enabled the generation of vast amounts of transcriptomic data at cellular …
RNA‐seq) have enabled the generation of vast amounts of transcriptomic data at cellular …
Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters
Background Time course data from microarrays and high-throughput sequencing
experiments require simple, computationally efficient and powerful statistical models to …
experiments require simple, computationally efficient and powerful statistical models to …