Education: MSc in Genetic Engineering
Expertise: Ambiguous, dedicated and a sincere research scientist with deep knowledge and research experience in field of Biotechnology and Bioinformatics. Gouri Ahir is Jr. Application Scientist at RASA Life Science Informatics past 1.6 years, wherein she has utilized by skills, prior knowledge in Molecular Biology to develop and built new expertise in various conventional research methodology designing and executions in field of bioinformatics, next generation sequencing data analysis, computer-aided drug designing and molecular dynamic and simulation studies. Successfully concluded and assisted in more than 15 research oriented services and in preparations of Analytic reports along with technical briefing on respective research study.
Co-authored in 11 publications in peer reviewed high impact factor journals (2 book chapter (submitted), 2 research papers(submitted), 4 review papers (submitted, final stage) and 3 review papers ( final editing).
She has trained more than 30 research trainees, 75 industrial trainees in the fields of bioinformatics and NGS data analysis; managed and coordinated multiple research projects simultaneously. Also, assisting and giving active participation in Life Science-based databases and tools development team.
Technical Skills & knowledge:
Efficient in understanding bioinformatics tools, servers, software, databases for big data analysis, solving various genomics and proteomics cases using bioinformatics approach.
Understand big genomic data analysis, mutation studies, variant calling and analysis techniques, gene expression studies (RNA-Seq data analysis), DNA-protein interaction studies (ChIP-Seq analysis), Meta-genomic data analysis (QIME, MOTHUR, and MG-RAST), De novo assembly via NGS tools and Genome annotation studies.
Chemo-informatics, drug discovery approaches- pharmacophore based, docking studies for protein, protein-ligand interactions.
Proficient in performing in-silico protein modelling with various techniques, dynamics studies of protein and protein ligand complexes via software-based approaches.