Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to
quantify the gene expression profile of thousands of single cells simultaneously. Analysis of …

New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …

Medical discoveries mainly depend on the capability to process and analyze biological
datasets, which inundate the scientific community and are still expanding as the cost of next …

The integration of multi-omics data makes it possible to understand complex biological
organisms at the system level. Numerous integration approaches have been developed by …

Background Sepsis is a heterogenous syndrome and individualized management strategy is
the key to successful treatment. Genome wide expression profiling has been utilized for …

Gene regulatory networks (GRNs) involve complex and multi-layer regulatory interactions
between regulators and their target genes. Precise knowledge of GRNs is important in …

Single-cell RNA sequencing (scRNA-seq) allows quantitative analysis of gene expression at
the level of single cells, beneficial to study cell heterogeneity. The recognition of cell types …

Gastrointestinal diseases are complex diseases that occur in the gastrointestinal tract.
Common gastrointestinal diseases include chronic gastritis, peptic ulcers, inflammatory …

As Deep Learning and Bioinformatics are constantly evolving fields, this review focuses on
four types of Deep Neural Networks; Feedforward, Recurrent, Convolutional and Generative …

Autoencoders have been used to model single-cell mRNA-sequencing data with the
purpose of denoising, visualization, data simulation, and dimensionality reduction. We, and …