Triplebar
Gabriel Navarro is a highly experienced bioinformatics and data scientist with a strong background in computational metabolomics and mass spectrometry. Currently serving as a Senior Bioinformatics Scientist at Triplebar since February 2024, Gabriel previously worked as a Data Scientist at Amyris, focusing on computational pipelines and machine learning applications for protein engineering. Additional experience includes roles as a Senior Scientist at Hexagon Bio and Brightseed, specializing in computational metabolomics, and various positions at Mondelēz International as a Mass Spectrometry Specialist. Gabriel's early career includes a postdoctoral researcher role at the University of California, San Diego, and an internship at Plexxikon Inc. with educational qualifications comprising a Ph.D. in Chemistry from the University of California, Santa Cruz, and a Bachelor of Science in Chemical Biology from the University of California, Berkeley.
Triplebar
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We discover the 1 in a million 10,000x faster. Harnessing evolution means giving nature the time and space to find complex solutions. Current technology falls fall short of the scale required to accelerate this process. The current state of the art is to rely on technology like liquid-handling robotics to look for a 1-in-a-million solution using a method that can only search through thousands of samples. At Triplebar, we measure the effect of billions of mutations. We oversample the genome every day and use this capacity to quickly find solutions to the greatest problems we face.