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MACHINE LEARNING GUIDED DESIGN OF VIRAL VECTOR LIBRARIES
MACHINE LEARNING GUIDED DESIGN OF VIRAL VECTOR LIBRARIES
Researchers at UC Berkeley have developed a machine learning model that can aide in the design of more efficient viral vector libraries.
Directed evolution of biomolecules to generate large numbers of randomized variants is an important innovation in biochemistry. This methodology can be applied...
Published: 8/17/2023
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Inventor(s): David Schaffer, Jennifer Listgarten, Danqing Zhu, David Brookes
Keywords(s): Machine Learning, Recombinant Adenoviral-Associated Virus (rAAV), Vector
Category(s): Technology Classifications > Software
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PREDICTION OF PREECLAMPSIA RISK USING CIRCULATING CELL-FREE RNA
PREDICTION OF PREECLAMPSIA RISK USING CIRCULATING CELL-FREE RNA
Researchers at Stanford and the Chan Zuckerberg Biohub have developed methods for predicting the risk or existence of preeclampsia.
Preeclampsia, a multi-organ syndrome diagnosed after 20 weeks of gestation, is associated with an increase in adverse maternal and perinatal outcomes. Detection...
Published: 10/14/2024
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Inventor(s): Stephen Quake, Gary Shaw, David Stevenson, Mira Moufarrej
Keywords(s): cfRNA, Diagnosis, Gestational Age, Machine Learning, Maternal Blood, Maternal Plasma
Category(s): Technology Classifications > Biology
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GENERATION AND SCREENING OF NON-NATURAL APTAMER LIBRARIES
GENERATION AND SCREENING OF NON-NATURAL APTAMER LIBRARIES
Researchers at Stanford, supported in part by the Chan Zuckerberg Biohub, have developed an integrated system for the automated generation, screening, and characterization of base-modified aptamers.
High affinity binding reagents have revolutionized biology and medicine. One class of synthetic...
Published: 3/17/2023
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Inventor(s): Trevor Feagin, Diana Wu, Peter Mage, John Coller, Hyongsok Soh
Keywords(s): Affinity Reagent, Aptamer, Base-Modified Nucleotide, Integrated Screening System, Machine Learning
Category(s): Technology Classifications > Biology, Technology Classifications > Chemistry
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