Dr. Raghava is a bioinformatician, currently working as a Professor at Center for Computational Biology, Indraprastha Institute of Information Technology (IIIT), Delhi. Previously, he was appointed as a chief scientist at Bioinformatics Centre, Institute of Microbial Technology (IMTECH), Chandigarh, India. He was ranked 1 on list of best Bioinformaticians in India
He obtained his M.Tech. from Indian Institute of Technology (IIT), New Delhi in 1986, and received a doctorate in Bioinformatics in 1966 from the Institute of Microbial Technology and Panjab University, Chandigarh. He has worked as a Postdoctoral fellow at Oxford University, Oxford and European Bioinformatics Institute, Cambridge UK (1996-98). He also worked as a Bioinformatics specialist at UAMS, USA (2002-3 & 2006) where he established bioinformatics infrastructure.
Dr. Raghava has been a visiting professor at POSTECH, South Korea (2005). He has currently been listed in The Worlds' Most Influential Scientific Minds 2014.
Dr. Raghava's group has developed a large number of open source software which is freely available for scientific use. His group has developed more than 200 web servers and 30 databases in the field of computer-aided drug/vaccine design (probably the highest number of services developed/maintained from a single group in the world). His research group has published more than 200 research papers in reputed journals with total Google Scholar citations of 10,509. Some of his contributed websites are:
- How to read fasta sequences as hash using perl?
- Installing Roary and Prokka on Ubuntu
- How to create a pangenome of isolated genome sequences using Roary and Prokka?
- Interview with Professor G.P.S Raghava – discussing Bioinformatics, Research, & science in India
- India ranks 4th among the Top 20 Bioinformatics Database Contributors in the world
- How to do molecular orbital analysis to find d-orbitals involved in bonding in an organometallic compound?
- BiR-Taking it to the next level: Editorial
- Bioinformatics and stem cell research- A mini review
- Tutorial: Vina Output Analysis Using PyMol
- Video Tutorial: Autodock Vina Result Analysis with PyMol