Solving Genome Puzzles
Genomics sequencing has created opportunities and challenges to gain new insights in biology and biomedical research.
Genome sequencing data usually consists of millions or billions of short DNA sequences, called reads, that are randomly drawn from genomes.
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Genomics sequencing has created opportunities and challenges to gain new insights in biology and biomedical research. Genome sequencing data usually consists of millions or billions of short DNA sequences, called reads, that are randomly drawn from genomes. Genome assembly is to put reads back together into a single genome, like solving a giant jigsaw puzzle. While genome assembly remains computationally challenging, metagenomics analysis aims to resolve the composition of a mixture of genomes, like solving mixed jigsaw puzzles simultaneously. In this masterclass, you will learn about computational models and algorithms to address these emerging challenges.
Dr Yu Lin
About the speaker
Dr Yu Lin is a Senior Lecturer at The Australian National University (ANU) School of Computing. His research focuses on computational biology and bioinformatics, an interdisciplinary area at the intersection of computer science and biology. He has been working on designing new models and algorithms to address computational challenges for interpreting complex datasets – including genome assembly, metagenomics and comparative genomics. In 2020, Dr Lin received the Outstanding Contribution by an Early Career Researcher Award from the Australian Bioinformatics and Computational Biology Society.
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