**Abstract**

Ginseng contains an extraordinarily complex mixture of chemical constituents that can vary with the species used, the place of origin, and the growing conditions. Various computational analyses which include genomics, transcriptomics, proteomics and bioinformatics have been used to study ginseng plant. A genomescale metabolic network offers a holistic view of ginsenoside biosynthesis, helps to predict genes associated with the production of pharmacologically vital dammarane-type ginsenosides, and provides insight for improving medicinal values of ginseng by genomics-based breeding. The draft genomic architecture of tetraploid *P. ginseng* cultivar (cv.) Chunpoong (ChP) by de novo genome assembly, was found to be 2.98 Gbp and consist of 59,352 annotated genes. Presently, bioinformatics exploration of ginseng includes studies on its P-glycoproteins, the impact of cytochrome P-450 on ginseng pharmacokinetics, as well as target prediction and differential gene expression network analyses. This study applauded Betasitosterol and Daucosterin as ginseng bioactive constituents that have several potential pharmacological effects in human, by modulating several proteins which include androgen receptor, HMG-CoA reductase, interlukin-2, and consequently impact the signaling cascade of several kinases such as mitogen-activated protein kinases (MAPKs), as well as many transcription factors such as polycomb protein SUZ12.

**Keywords:** Ginseng, bioinformatics, transcriptomics, genomics, bioactive, pharmacokinetics
