Parent Interventions: How can we Revert Peanut Allergies in Children?  |  Teacher Insights: Play Based Learning has a Positive Impact on Child's Learning and Development  |  Health Monitor: Social Media Use Likely to Affect the Physical Health of a Person  |  Parent Interventions: How to Deal with Developmental Language Disorder in Children  |  Health Monitor: Lifestyle Interventions from Early Childhood Prevents Cardiovascular Diseases  |  Teacher Insights: Teacher Expectations Can Have Powerful Impact on Students Academic Achievement  |  Policy Indications: Make Sure the Digital Technology Works for Public Good  |  Teacher Insights: The Significance of Social Emotional Learning Curriculum in Schools  |  Health Monitor: Forgetting is a Form of Learning  |  Higher Studies: University of Manchester Invites Application for LLB and LLM Programmes   |  Health Monitor: Is There a Blue Spot Inside our Brain?  |  Parent Interventions: Babies born during the Pandemic Performs Lower during Developmental Screening  |  Policy Indications: Invest in Structural Steel R&D : Prof BS Murty  |  Management lessons: ONPASSIVE Technologies Shows the Way in Rewarding Outperformers  |  Parent Interventions: Can We Make Our Kids Smarter?  |  
September 14, 2021 Tuesday 08:31:59 AM IST

Stanford University Develops Algorithm to Predict Molecular Structures

Research scholars at Stanford University have used new machine learning techniques to determine the structure of molecules. Determining the 3D shapes of biological molecules is one of the hardest problems in modern biology and medical discovery. Companies and research institutions often spend millions of dollars to determine a molecular structure – and even such massive efforts are frequently unsuccessful. The new algorithm predicts accurate molecular structures and, in doing so, can allow scientists to explain how different molecules work, with applications ranging from fundamental biological research to informed drug design practices. If a pair of proteins is implicated in a disease and if their interactions can be predicted, it paves the way for better drug targetting. 

Comments