In this paper, we provide an introduction to machine learning tasks that address important
problems in genomic medicine. One of the goals of genomic medicine is to determine how …

Next-generation sequencing (NGS) technologies have been used in diverse ways to
investigate various aspects of chromatin biology by identifying genomic loci that are bound …

Gene co-expression networks can be used to associate genes of unknown function with
biological processes, to prioritize candidate disease genes or to discern transcriptional …

Chromatin immunoprecipitation (ChIP) is the gold-standard technique for localizing nuclear
proteins in the genome. We used ChIP, in combination with deep sequencing (Seq), to study …

Long-term memory formation requires transcription and protein synthesis. Over the past few
decades, a great amount of knowledge has been gained regarding the molecular players …

Background Hi-C is currently the most widely used assay to investigate the 3D organization
of the genome and to study its role in gene regulation, DNA replication, and disease …

With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-
seq throughput, the development of working standards for the quality assessment of ChIP …

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in
even individual malignant cells. Epigenetic changes are critical mediators of these functional …

We evaluated how variations in sequencing depth and other parameters influence
interpretation of chromatin immunoprecipitation–sequencing (ChIP-seq) experiments. Using …

Motif discovery has been one of the most widely studied problems in bioinformatics ever
since genomic and protein sequences have been available. In particular, its application to …