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个人简介
My research lies in the interface of machine learning and AI, computer algorithms and computational biology. I am interested in studying AI and computer algorithms to analyze and interpret high volumes of biological data (especially proteomics data) and based upon which building predictive models. I am known for a protein structure prediction program RaptorX, which has been ranked very top in CASPs (Critical Assessment of Structure Prediction) and more importantly, widely used by the broader community. The deep convolutional residual neural network method invented by me in2016 for protein structure prediction has led to the first revolution of protein structure prediction by AI. Afterwards, through the effort of the broad community especially DeepMind, AI is now able to predict 50% of proteins with resolution comparable to that of experimental techniques. My other work includes machine learning methods, protein de novo sequencing, transcript assembly, protein homology search, protein-protein interaction prediction and functional prediction of variants.
研究兴趣
论文共 203 篇作者统计合作学者相似作者
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Proceedings of the National Academy of Sciences of the United States of Americano. 13 (2024): e2308788121-e2308788121
Briefings in bioinformaticsno. 2 (2024)
biorxiv(2023)
Benjamin Boyerinas,Sun-Mi Park,Noam Shomron, Mads M. Hedegaard,Jeppe Vinther,Jens S. Andersen,Christine Feig,Jinbo Xu,Christopher B. Burge, Marcus E. Peter
crossref(2023)
CoRR (2023)
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bioRxiv (Cold Spring Harbor Laboratory) (2023)
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crossref(2023)
Benjamin Boyerinas,Sun-Mi Park,Noam Shomron, Mads M. Hedegaard,Jeppe Vinther,Jens S. Andersen,Christine Feig,Jinbo Xu,Christopher B. Burge, Marcus E. Peter
crossref(2023)
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