首页|Data on Machine Learning Discussed by Researchers at Shanghai Jiao Tong Universi ty (Decoding Missense Variants by Incorporating Phase Separation via Machine Lea rning)
Data on Machine Learning Discussed by Researchers at Shanghai Jiao Tong Universi ty (Decoding Missense Variants by Incorporating Phase Separation via Machine Lea rning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news reporting from Shanghai Jiao T ong University by NewsRx journalists, research stated, “Computational models hav e made significant progress in predicting the effect of protein variants.” The news correspondents obtained a quote from the research from Shanghai Jiao To ng University: “However, deciphering numerous variants of uncertain significance (VUS) located within intrinsically disordered regions (IDRs) remains challengin g. To address this issue, we introduce phase separation, which is tightly linked to IDRs, into the investigation of missense variants. Phase separation is vital for multiple physiological processes. By leveraging missense variants that alte r phase separation propensity, we develop a machine learning approach named PSMu tPred to predict the impact of missense mutations on phase separation. PSMutPred demonstrates robust performance in predicting missense variants that affect nat ural phase separation. In vitro experiments further underscore its validity.”
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