Ph.D., Head of Bioinformatics Research and Early Development, Roche Sequencing Solutions
Hugo Lam, Ph.D., is Head of Bioinformatics Research & Early Development at Roche Sequencing Solutions. His work covers broad computational areas in personalized medicine, from translational research to clinical applications. He has over seventeen years of experience in software engineering, bioinformatics, and genomics, including time at 23andMe and Personalis. He received his Bachelor’s degree in Biology from the Hong Kong University of Science and Technology and his Master’s degree in Computing Science from Imperial College London. He holds a Ph.D. in Computational Biology and Bioinformatics from Yale University and was a postdoctoral scholar in Bioinformatics at Stanford University. His research work in Bioinformatics and Genomics has been published in over 30 publications in the past 10 years.
Clinical & Research Tools Showcase: Roche Sequencing Solutions
Roche Sequencing Solutions (RSS) is building on Roche’s legacy of innovation to transform next-generation sequencing and its application. By simplifying workflows and expanding assay menus, RSS is broadening access to genomic data and lowering barriers to routine use.
A Deep Learning Approach For Somatic Mutation Detection
We will present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly out-performs previous methods on different sequencing platforms, sequencing strategies, and tumor purities.