COB is delighted to present you its first Genomics Learning Program in November 2021! We are organizing a series of comprehensive and interactive virtual training sessions, progressing into 3 chapters. The training session will be directed by Rashedul Islam, a Ph.D. candidate in Bioinformatics at the University of British Columbia, Canada, and Atia Amin Oni, a Ph.D. student in Bioinformatics, McGill University, Canada.
The 3 stages of the program include Next Generation Sequencing (NGS) Data Analysis, Bacterial Genome Assembly and Gene Annotation and Alignment and Mutation Calling from NGS Data.
This program is meant to provide in-depth training on the necessary modern skillset required in genomics. Registration will be started soon. Please stay tuned!
The description will be available soon.
PhD Candidate University of British Columbia Canada
Ph.D. Student in Bioinformatics McGill University, Canada
The description will be available soon.
PhD Candidate University of British Columbia Canada
Ph.D. Student in Bioinformatics McGill University, Canada
The description will be available soon.
PhD Candidate University of British Columbia Canada
Ph.D. Student in Bioinformatics McGill University, Canada
PhD candidate, Bioinformatics
University of British Columbia
A researcher since his undergrad days in Shahjalal University of Science and Technology (SUST), Rashedul Islam has been dedicated to field of bioinformatics for the past 10 years and is currently pursuing his PhD in University of British Columbia
Ph.D. StudentĀ in Bioinformatics
McGill University, Canada
Atia Amin is passionate about interdisciplinary research that bridges the gap between machine learning and molecular genomics to address various problems in life science. Throughout her research experience so far, she diversified her skills that span across multiple disciplines including microbiology, molecular biology, plant science, and bioinformatics. Currently, she is doing her PhD in Bioinformatics at McGill University, Canada, where her research involves identifying genetic biomarkers of pathogens causing different vector borne diseases using machine learning and bioinformatics approaches.