Priyanka Purkayastha

Results-oriented bioinformatician with a strong background in bioinformatics and computational biology, specializing in next-generation sequencing (NGS) data analysis. Leveraging advanced programming skills in languages such as R and Python ,I have successfully processed and interpreted large-scale genomic datasets to uncover meaningful insights in the fields of genomics and precision medicine. A collaborative and detail-oriented professional, I thrive in interdisciplinary research settings, working closely with multidisciplinary teams to accelerate discoveries in genomics. Seeking to apply my passion for bioinformatics and computational biology to drive innovation and shape the future of genomic research.

GVK Biosciences Private Limited

Role: 

Big data analysis and data automation through programming using R, Python, and Shell. Presented deliverables to clients.
Collaborated and consulted clients (Takeda Pharmaceuticals) to optimize the drug repurposing protocols using various text mining tools like Apache Solr and National Language Processing (NLP).
Developed visualization strategies for finding out associations between complex biological data.
Identified alternate indications (cancer) for drugs using machine learning approaches.
Designed protocol for extracting gene expression data from the databases such as TCGA using R programming and shell scripts.

Indian Institute of Technology Bombay

Role: @Analyzed and processed complex genomics data using advanced querying, visualization, and analytics tools. @Identified, measured and improved strategies for utilizing machine learning algorithms to predict drug-resistant Mycobacterium tuberculosis (MTB). @Analyzed @impact of feature selection to improve accuracy of predictive models. @Delivered seminars and mentored Ph.D. students on data mining techniques and classification algorithms

Ph.D. @Birla Institute of Technology and Science, Pilani @2011-2016 
Thesis: Classification, Structure prediction and Molecular dynamics study of novel protein targets involved in neurodegenerative diseases