Identification of the active compounds and their mechanisms of medicinal and edible Shanzha based on network pharmacology and molecular docking.

Shanzha (Crataegus pinnatifida Bunge), an edible traditional Chinese medicine (TCM), has an effect on dyspepsia. However, the investigations of the pharmacological effects have not been carried out. This study aimed to identify the potential targets and pharmacological mechanisms of Shanzha in the treatment of dyspepsia by network pharmacology and molecular docking.

Transcriptome profiling analysis of tea plant (Camellia sinensis) using Oxford Nanopore long-read RNA-Seq technology.

Transcriptome profiles have been widely captured using short-read sequencing technology, but there are still limitations partially due to the read length. Here, we generated long reads using Oxford Nanopore PromethION™ technology and short reads using the Illumina sequencing platform to study the transcriptome of root, stem, and leaf of Camellia sinensis cv. Fudingdabai.

Complement Genome Annotation Lift Over Using a Weighted Sequence Alignment Strategy.

With the broad application of high-throughput sequencing, more whole-genome resequencing data and assemblies of natural populations are becoming available. For a particular species, in general, only the reference genome is well established and annotated. Computational tools based on sequence alignment have been developed to investigate the gene models of individuals belonging to the same or closely related species.

Prediction and characterization of protein-protein interaction networks in swine.

Background: Studying the large-scale protein-protein interaction (PPI) network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes.

Results: We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins.