As a data-driven science, genomics largely utilizes machine learning to capture
dependencies in data and derive novel biological hypotheses. However, the ability to extract …

Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

Motivation Sequence motif discovery algorithms can identify novel sequence patterns that
perform biological functions in DNA, RNA and protein sequences—for example, the binding …

Abstract JASPAR (http://jaspar. genereg. net) is an open-access database of curated, non-
redundant transcription factor (TF)-binding profiles stored as position frequency matrices …

The prediction of transcription factor (TF) activities from the gene expression of their targets
(ie, TF regulon) is becoming a widely used approach to characterize the functional status of …

Abstract Transposase-Accessible Chromatin followed by sequencing (ATAC-seq) is a
simple protocol for detection of open chromatin. Computational footprinting, the search for …

We address the issue of limit cycling behavior in training Generative Adversarial Networks
and propose the use of Optimistic Mirror Decent (OMD) for training Wasserstein GANs …

Gene regulation plays a critical role in the cellular processes that underlie human health and
disease. The regulatory relationship between transcription factors (TFs), key regulators of …

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

Knowing the sequence specificities of DNA-and RNA-binding proteins is essential for
developing models of the regulatory processes in biological systems and for identifying …