Scientists have developed high-throughput tools to probe the inner workings of living cells. Technologies that obtain sequence information from DNA, RNA and protein molecules work in conjunction with tools such as X-ray devices, nuclear magnetic resonance machines and cryo-electron microscopy to reveal the three-dimensional conformation of these molecules. More recent technologies — such as next-generation DNA, RNA and protein sequencing along with mass spectrometry — strive to investigate the interactions between the various proteins and genes within a cell. The result of these investigations is the production of huge amounts of data.
The objective of bioinformatics is to store, retrieve, manipulate, visualize, analyze, integrate and interpret data from a variety of data sources so we can fully understand the vast array of processes that occur in living cells, as well as understand Earth’s biodiversity by revealing species, together with their dynamics and interactions.
For human health, understanding the disease pathway is essential to treat the more than 6,000 genetic disorders along with cancers and Alzheimer’s disease and many communicable diseases. Applications of this knowledge include drug design and medical diagnostic procedures. Similarly, understanding the biological processes of other species including microorganisms will provide insights relevant in agriculture, biotechnology and fundamental biology.
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Ming Li and Hieu Tran use machine learning to develop personalized cancer vaccines
Our bodies are made of trillions of cells that form tissues and organs. The genes inside the nucleus of each cell code for proteins that determine a cell’s structure and function, as well as instruct a cell when to grow, divide and die. Normally, our cells follow these instructions, but if a cell’s DNA mutates it can cause the cell to divide and grow out of control. Cancer is fundamentally a disease of uncontrolled cell growth and regulation, and all cancers ultimately are caused by mutations to the genes that regulate cell division, growth and differentiation.
Rapid Novor, cofounded by Cheriton School of Computer Science Professor Bin Ma, secures $5-million USD to decode antibodies for potential treatments for COVID-19 and other illnesses
A world-leading University of Waterloo spinoff company, that decodes blood samples for potential treatments for illnesses like cancer and COVID-19, is expanding operations with the help of a $5-million USD investment.
Bin Ma, a University of Waterloo computer science professor who cofounded Rapid Novor in 2015, says the company’s technology is the most advanced in the world when it comes to deciphering the complex workings of antibody proteins, a process called sequencing.
Lila Kari and her colleagues use machine learning-based analysis to quickly classify novel pathogens such as the COVID-19 virus
A multidisciplinary team of researchers at Waterloo’s Cheriton School of Computer Science and Western University has developed a computational method that within minutes can identify and classify viruses such as SARS-CoV-2, the respiratory pathogen responsible for the COVID-19 pandemic.