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Our book chapter entitled "Machine learning for protein inter-residue interaction prediction" will soon be published by World Scientific Publishing. (2022.07).
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Matee's paper entitled "PScL-DDCFPred: an ensemble deep learning-based approach for characterizing multiclass subcellular localization of human proteins from bioimage data" was recently accepted by Bioinformatics. This work was collaboratively done by researchers from Nanjing University of Science and Technology and Monash University. (2022.06).
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Ying Zhang's paper entitled "Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites" was recently accepted by Briefings in Bioinformatics. This work was collaboratively done by researchers from Nanjing University of Science and Technology and Monash University. (2021.08).
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Matee Ullah's paper entitled "PScL-HDeep: image-based prediction of protein subcellular location in human tissue using ensemble learning of handcrafted and deep learned features with two-layer feature selection" was recently accepted by Briefings in Bioinformatics. (2021.07).
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Yang Li's paper entitled "Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks" has been accepted by PLOS Computational Biology. (2021.03).
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Long-Chen Shen's paper entitled "SAResNet: self-attention residual network for predicting DNA-protein binding" has been accepted by Briefings in Bioinformatics. This work was collaboratively done by researchers from Nanjing University of Science and Technology and Monash University. (2021.03).
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Yan Liu's paper entitled "Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation" has been accepted by Briefings in Bioinformatics. This work was collaboratively done by researchers from Nanjing University of Science and Technology and Monash University. (2021.01).
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Yi-Heng Zhu's paper entitled "Accurate Multi-Stage Prediction of Protein Crystallization Propensity Using Deep-Cascade Forest with Sequence-Based Features" has been
accepted by Briefings in Bioinformatics. This work was collaboratively done by researchers from Nanjing University of Science and Technology, Monash University, and University of Michigan (Ann Arbor). (2020.04).
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SSCpred, which can predict protein contact map with only the target sequence itself, is accepted by Journal of Chemical Information and Modeling. (2020.04).
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Yang Li's paper has been
accepted by Bioinformatics, (2019.04).
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Yi-Heng Zhu's paper has been
accepted by Journal of Chemical Information and Modeling,
(2019.03).
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Dr.
Jiangning Song from Monash University, Australia visited NJUST
and gave a talk entitled "Harnessing
the power of machine-learning and artificial intelligence techniques
to address significant biomedical classification problems in the big
data-driven era", (2018.12).
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Ph.D student Yiheng Zhu
attended the I-TASSER 2018 & First Structural Bioinformatics
Workshop at Hangzhou, China, on November 23-25, 2018.
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He Yan's paper has been
accepted by Machine Learning, (2018.10).
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Prof.
Yang Zhang from University of Michigan (Ann Arbor) visited our
lab, 2018.
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Jun Hu's paper has been
accepted by Bioinformatics, (2018.02).
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Jun Hu's paper has been
accepted by Journal of Chemical Information and Modeling, (2018.01).
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Chun-Qiu Xia's paper has been
accepted by IEEE/ACM Transactions on Computational Biology and
Bioinformatics , (2017.06).
