In recent years, microRNAs (miRNAs) have emerged as a major class of regulatory genes,
present in most metazoans and important for a diverse range of biological functions …

In recent years gene regulatory networks (GRNs) have attracted a lot of interest and many
methods have been introduced for their statistical inference from gene expression data …

The complex language of eukaryotic gene expression remains incompletely understood.
Despite the importance suggested by many noncoding variants statistically associated with …

This book unifies and extends latent variable models, including multilevel or generalized
linear mixed models, longitudinal or panel models, item response or factor models, latent …

Key challenges for human genetics, precision medicine and evolutionary biology include
deciphering the regulatory code of gene expression and understanding the transcriptional …

Identifying master regulators of biological processes and map** their downstream gene
networks are key challenges in systems biology. We developed a computational method …

The inference of transcriptional networks that regulate transitions into physiological or
pathological cellular states remains a central challenge in systems biology. A mesenchymal …

How transcription factors (TFs) interpret cis-regulatory DNA sequence to control gene
expression remains unclear, largely because past studies using native and engineered …

Computational methods for discovery of sequence elements that are enriched in a target set
compared with a background set are fundamental in molecular biology research. One …

Post-translational histone modifications modulate chromatin activity to affect gene
expression. How chromatin states underlie lineage choice in single cells is relatively …