Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …

Despite considerable progress in genome-and proteome-based high-throughput screening
methods and in rational drug design, the increase in approved drugs in the past decade did …

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 …

Many biological research areas such as drug design require gene regulatory networks to
provide clear insight and understanding of the cellular process in living cells. This is …

Gene regulatory network (GRN) is the important mechanism of maintaining life process,
controlling biochemical reaction and regulating compound level, which plays an important …

The inference of gene regulatory networks (GRNs) from expression data can mine the direct
regulations among genes and gain deep insights into biological processes at a network …

Alzheimer's Disease (AD) is a neurodegenerative disease that affects cognition and is the
most common cause of dementia in the elderly. As the number of elderly individuals …

Bioinformatics research is characterized by voluminous and incremental datasets and
complex data analytics methods. The machine learning methods used in bioinformatics are …

We introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based
causal implicit generative model for simulating single-cell RNA-seq data, in silico …

Inference of gene regulatory network from expression data is a challenging task. Many
methods have been developed to this purpose but a comprehensive evaluation that covers …