Arli Aditya Parikesit  

Arli Aditya Parikesit is a bioinformatics expert from Indonesia. He is the Professor, and Faculty Member of Bioinformatics Department at the Indonesia International Institute for Life Sciences (i3L). He has a strong background in chemistry, biotechnology, and computer science, and has conducted research in various fields such as structural bioinformatics, immunoinformatics, in silico drug design, and in silico transcriptomics.

Parikesit was born in Jakarta, Indonesia, and completed his bachelor's and master's degrees in chemistry at the University of Indonesia. He received a full scholarship from the German Academic Exchange Service (DAAD) to pursue his doctoral degree in bioinformatics at the University of Leipzig, Germany. His doctoral research focused on the utilization of modern protein domain annotation techniques to the three domains of life. He also worked as a research fellow at the Max Planck Institute for Mathematics in the Natural Sciences in Germany.

Parikesit has published several papers in international journals and conferences, and has received various awards and grants for his research. He is also a honorary member of the Indonesian Young Academy of Science (ALMI), a member of Indonesia Society of Bioinformatics and Biodiversity (MABBI) and a Bioinformatics scientific cluster member of Indonesian Association of Higher Education in Informatics and Computing (APTIKOM). He is passionate about developing bioinformatics education and research in Indonesia, and collaborating with industry partners to apply bioinformatics solutions to real-world problems. He is also interested in artificial intelligence and its applications to life sciences.

Selected Publications:

• Maladan, Y., Krismawati, H., Wahyuni, T., Tanjung, R., Awaludin, K., Audah, K. A., & Parikesit, A. A. (2021). The whole-genome sequencing in predicting Mycobacterium tuberculosis drug susceptibility and resistance in Papua, Indonesia. BMC Genomics 2021 22:1, 22(1), 1-11. DOI: 10.1186/S12864-021-08139-3.

• Parikesit, A. A., Ansori, A. N. M., & Kharisma, V. D. (2022). A Computational Design of siRNA in SARS-CoV-2 Spike Glycoprotein Gene and Its Binding Capability toward mRNA. Indonesian Journal of Chemistry, 22(5), 1163. DOI: 10.22146/ijc.68415.

• Parikesit, A. A., & Nurdiansyah, R. (2021). Natural products repurposing of the H5N1-based lead compounds for the most fit inhibitors against 3C-like protease of SARS-CoV-2. Journal of Pharmacy & Pharmacognosy Research, 9(5), 730-745. DOI: 10.5281/zenodo.5529215.