首页|New Machine Learning Research from Stanford University Described (A machine lear ning approach uncovers principles and determinants of eukaryotic ribosome pausin g)
New Machine Learning Research from Stanford University Described (A machine lear ning approach uncovers principles and determinants of eukaryotic ribosome pausin g)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligen ce have been presented. According to news originating from Stanford University b y NewsRx correspondents, research stated, “Nonuniform local translation speed di ctates diverse protein biogenesis outcomes.” The news editors obtained a quote from the research from Stanford University: “T o unify known and uncover unknown principles governing eukaryotic elongation rat e, we developed a machine learning pipeline to analyze RiboSeq datasets. We find that the chemical nature of the incoming amino acid determines how codon optima lity influences elongation rate, with hydrophobic residues more dependent on tra nsfer RNA (tRNA) levels than charged residues. Unexpectedly, we find that wobble interactions exert a widespread effect on elongation pausing, with wobble-media ted decoding being slower than Watson-Crick decoding, irrespective of tRNA level s.”
Stanford UniversityCyborgsEmerging T echnologiesMachine Learning
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