The expanding scale and inherent complexity of biological data have encouraged a growing
use of machine learning in biology to build informative and predictive models of the …

Denoising diffusion models embody a type of generative artificial intelligence that can be
applied in computer vision, natural language processing and bioinformatics. In this Review …

We present a systematic evaluation of state-of-the-art algorithms for inferring gene
regulatory networks from single-cell transcriptional data. As the ground truth for assessing …

With the progress of medical technology, biomedical field ushered in the era of big data,
based on which and driven by artificial intelligence technology, computational medicine has …

With the evolution of biotechnology and the introduction of the high throughput sequencing,
researchers have the ability to produce and analyze vast amounts of genomics data. Since …

Gene regulation is a central topic in cell biology. Advances in omics technologies and the
accumulation of omics data have provided better opportunities for gene regulation studies …

The gene regulatory structure of cells involves not only the regulatory relationship between
two genes, but also the cooperative associations of multiple genes. However, most gene …

Motivation Single-cell RNA-sequencing (scRNA-seq) technologies provide an opportunity to
infer cell-specific gene regulatory networks (GRNs), which is an important challenge in …

Ribonucleic acid Sequencing (RNA-Seq) analysis is particularly useful for obtaining insights
into differentially expressed genes. However, it is challenging because of its high …

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