Characterisation of plant cysteine proteases with therapeutic potential

Research output

Research output per year 2016 2019 2020 2021 2022 2024

• 58 Article
• 2 Review Article

Research output per year

Research output per year

Search results

• 2024

  PmxPred: A data-driven approach for the identification of active polymyxin analogues against gram-negative bacteria

  Wang, X., Patil, N., Li, F., Wang, Z., Zhan, H., Schmidt, D. F., Thompson, P. E., Guo, Y., Landersdorfer, C. B., Shen, H-H., Peleg, A. Y., Li, J. & Song, J., 2024, In: Computers in Biology and Medicine. 168, 10 p., 107681.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  8 Citations (Scopus)
• 2023

  iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities

  Xu, J., Li, F., Li, C., Guo, X., Landersdorfer, C. B., Shen, H-H., Peleg, A. Y., Li, J., Imoto, S., Yao, J., Akutsu, T. & Song, J., Jul 2023, In: Briefings in Bioinformatics. 24, 4, 20 p., bbad240.

  Research output: Contribution to journal › Article › Research › peer-review
  28 Citations (Scopus)

• Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues

  Zhang, Y., Wang, Z., Zhang, Y., Li, S., Guo, Y., Song, J. & Yu, D-J., 1 Dec 2023, In: Bioinformatics. 39, 12, 8 p., btad709.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  5 Citations (Scopus)

• Prediction of Multiple Types of RNA Modifications via Biological Language Model

  Zhang, Y., Ge, F., Li, F., Yang, X., Song, J. & Yu, D-J., Sept 2023, In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20, 5, p. 3205-3214 10 p.

  Research output: Contribution to journal › Article › Research › peer-review
  7 Citations (Scopus)

• PScL-2LSAESM: bioimage-based prediction of protein subcellular localization by integrating heterogeneous features with the two-level SAE-SM and mean ensemble method

  Ullah, M., Hadi, F., Song, J. & Yu, D-J., 1 Jan 2023, In: Bioinformatics. 39, 1, 8 p., btac727.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  2 Citations (Scopus)

• SMG: self-supervised masked graph learning for cancer gene identification

  Cui, Y., Wang, Z., Wang, X., Zhang, Y., Zhang, Y., Pan, T., Zhang, Z., Li, S., Guo, Y., Akutsu, T. & Song, J., Nov 2023, In: Briefings in Bioinformatics. 24, 6, 13 p., bbad406.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  2 Citations (Scopus)

• TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level

  Liu, Y., Wei, G., Shen, L-C., Gasser, R. B., Song, J., Chen, D. & Yu, D-J., May 2023, In: Briefings in Bioinformatics. 24, 3, p. 1-11 11 p.

  Research output: Contribution to journal › Article › Research › peer-review
  5 Citations (Scopus)

• VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants

  Ge, F., Li, C., Iqbal, S., Muhammad, A., Li, F., Thafar, M. A., Yan, Z., Worachartcheewan, A., Xu, X., Song, J. & Yu, D-J., 19 Jan 2023, In: Briefings in Bioinformatics. 24, 1, p. 1-16 16 p.

  Research output: Contribution to journal › Article › Research › peer-review
  10 Citations (Scopus)
• 2022

  ASPIRER: A new computational approach for identifying non-classical secreted proteins based on deep learning

  Wang, X., Li, F., Xu, J., Rong, J., Webb, G. I., Ge, Z., Li, J. & Song, J., Mar 2022, In: Briefings in Bioinformatics. 23, 2, p. 1-12 12 p., bbac031.

  Research output: Contribution to journal › Article › Research › peer-review
  20 Citations (Scopus)

• BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data

  Chen, J., Li, F., Wang, M., Li, J., Marquez-Lago, T. T., Leier, A., Revote, J., Li, S., Liu, Q. & Song, J., 18 Jan 2022, In: Frontiers in Big Data. 4, 16 p., 727216.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  2 Citations (Scopus)

• Clarion is a multi-label problem transformation method for identifying mRNA subcellular localizations

  Bi, Y., Li, F., Guo, X., Wang, Z., Pan, T., Guo, Y., Webb, G. I., Yao, J., Jia, C. & Song, J., 19 Nov 2022, In: Briefings in Bioinformatics. 23, 6, p. 1-12 12 p.

  Research output: Contribution to journal › Article › Research › peer-review
  16 Citations (Scopus)

• Enhancing Characteristic Gene Selection and Tumor Classification by the Robust Laplacian Supervised Discriminative Sparse PCA

  Zhang, L. X., Yan, H., Liu, Y., Xu, J., Song, J. & Yu, D-J., 11 Apr 2022, In: Journal of Chemical Information and Modeling. 62, 7, p. 1794-1807 14 p.

  Research output: Contribution to journal › Article › Research › peer-review
  3 Citations (Scopus)

• iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets

  Chen, Z., Liu, X., Zhao, P., Li, C., Wang, Y., Li, F., Akutsu, T., Bain, C., Gasser, R. B., Li, J., Yang, Z., Gao, X., Kurgan, L. & Song, J., 5 Jul 2022, In: Nucleic Acids Research. 50, W1, p. W434-W447 14 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  37 Citations (Scopus)

• Improving the prediction of DNA-protein binding by integrating multi-scale dense convolutional network with fault-tolerant coding

  Yin, Y. H., Shen, L. C., Jiang, Y., Gao, S., Song, J. & Yu, D-J., 1 Nov 2022, In: Analytical Biochemistry. 656, 11 p., 114878.

  Research output: Contribution to journal › Article › Research › peer-review
  7 Citations (Scopus)

• PreAcrs: a machine learning framework for identifying anti-CRISPR proteins

  Zhu, L., Wang, X., Li, F. & Song, J., Dec 2022, In: BMC Bioinformatics. 23, 1, 21 p., 444.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  8 Citations (Scopus)

• RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins

  Peng, X., Wang, X., Guo, Y., Ge, Z., Li, F., Gao, X. & Song, J., Jul 2022, In: Briefings in Bioinformatics. 23, 4, p. 1-15 15 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  17 Citations (Scopus)
• 2021

  Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features

  Zhu, Y-H., Hu, J., Ge, F., Li, F., Song, J., Zhang, Y. & Yu, D-J., 20 May 2021, In: Briefings in Bioinformatics. 22, 3, 14 p., bbaa076.

  Research output: Contribution to journal › Article › Research › peer-review
  18 Citations (Scopus)

• Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides

  Xu, J., Li, F., Leier, A., Xiang, D., Shen, H-H., Marquez Lago, T. T., Li, J., Yu, D-J. & Song, J., Sept 2021, In: Briefings in Bioinformatics. 22, 5, p. 1-22 22 p.

  Research output: Contribution to journal › Article › Research › peer-review
  82 Citations (Scopus)

• Computational prediction and interpretation of both general and specific types of promoters in Escherichia coli by exploiting a stacked ensemble-learning framework

  Li, F., Chen, J., Ge, Z., Wen, Y., Yue, Y., Hayashida, M., Baggag, A., Bensmail, H. & Song, J., 1 Mar 2021, In: Briefings in Bioinformatics. 22, 2, p. 2126-2140 15 p.

  Research output: Contribution to journal › Article › Research › peer-review
  58 Citations (Scopus)

• DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites

  Liu, Q., Chen, J., Wang, Y., Li, S., Jia, C., Song, J. & Li, F., 1 Jul 2021, In: Briefings in Bioinformatics. 22, 3, 14 p., bbaa124.

  Research output: Contribution to journal › Article › Research › peer-review
  97 Citations (Scopus)

• DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy

  Xie, R., Li, J., Wang, J., Dai, W., Leier, A., Marquez-Lago, T. T., Akutsu, T., Lithgow, T., Song, J. & Zhang, Y., 20 May 2021, In: Briefings in Bioinformatics. 22, 3, 15 p., bbaa125.

  Research output: Contribution to journal › Article › Research › peer-review
  54 Citations (Scopus)

• Formator: Predicting Lysine Formylation Sites Based on the Most Distant Undersampling and Safe-Level Synthetic Minority Oversampling

  Jia, C., Zhang, M., Fan, C., Li, F. & Song, J., Sept 2021, In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18, 5, p. 1937-1945 9 p.

  Research output: Contribution to journal › Article › Research › peer-review
  18 Citations (Scopus)

• ILearnPlus: A comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization

  Chen, Z., Zhao, P., Li, C., Li, F., Xiang, D., Chen, Y., Akutsu, T., Daly, R. J., Webb, G. I., Zhao, Q., Kurgan, L. & Song, J., 4 Jun 2021, In: Nucleic Acids Research. 49, 10, 19 p., e60.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  163 Citations (Scopus)

• Improving protein fold recognition using triplet network and ensemble deep learning

  Liu, Y., Han, K., Zhu, Y. H., Zhang, Y., Shen, L. C., Song, J. & Yu, D. J., Nov 2021, In: Briefings in Bioinformatics. 22, 6, p. 1-16 16 p.

  Research output: Contribution to journal › Article › Research › peer-review
  11 Citations (Scopus)

• Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification

  Liang, X., Li, F., Chen, J., Li, J., Wu, H., Li, S., Song, J. & Liu, Q., Jul 2021, In: Briefings in Bioinformatics. 22, 4, p. 1-17 17 p.

  Research output: Contribution to journal › Article › Research › peer-review
  57 Citations (Scopus)

• Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites

  Zhang, Y., Liu, Y., Xu, J., Wang, X., Peng, X., Song, J. & Yu, D. J., Nov 2021, In: Briefings in Bioinformatics. 22, 6, p. 1-13 13 p.

  Research output: Contribution to journal › Article › Research › peer-review
  26 Citations (Scopus)

• MutTMPredictor: Robust and accurate cascade XGBoost classifier for prediction of mutations in transmembrane proteins

  Ge, F., Zhu, Y. H., Xu, J., Muhammad, A., Song, J. & Yu, D. J., Jan 2021, In: Computational and Structural Biotechnology Journal. 19, p. 6400-6416 17 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access
  24 Citations (Scopus)

• nhKcr: a new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning

  Chen, Y. Z., Wang, Z. Z., Wang, Y., Ying, G., Chen, Z. & Song, J., Nov 2021, In: Briefings in Bioinformatics. 22, 6, p. 1-13 13 p.

  Research output: Contribution to journal › Article › Research › peer-review
  37 Citations (Scopus)

• 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

  Ullah, M., Han, K., Hadi, F., Xu, J., Song, J. & Yu, D. J., 5 Nov 2021, In: Briefings in Bioinformatics. 22, 6, 17 p.

  Research output: Contribution to journal › Article › Research › peer-review
  31 Citations (Scopus)

• Systematic evaluation of machine learning methods for identifying human-pathogen protein-protein interactions

  Chen, H., Li, F., Wang, L., Jin, Y., Chi, C-H., Kurgan, L., Song, J. & Shen, J., 27 May 2021, In: Briefings in Bioinformatics. 22, 3, 21 p., bbaa068.

  Research output: Contribution to journal › Article › Research › peer-review
  34 Citations (Scopus)

• Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation

  Liu, Y., Zhu, Y. H., Song, X., Song, J. & Yu, D. J., Sept 2021, In: Briefings in Bioinformatics. 22, 5, p. 1-14 14 p.

  Research output: Contribution to journal › Article › Research › peer-review
  12 Citations (Scopus)
• 2020

  An Interpretable Prediction Model for Identifying N⁷-Methylguanosine Sites Based on XGBoost and SHAP

  Bi, Y., Xiang, D., Ge, Z., Li, F., Jia, C. & Song, J., 4 Dec 2020, In: Molecular Therapy - Nucleic Acids. 22, p. 362-372 11 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access

  File
  115 Citations (Scopus)

• Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms

  Wei, L., Hu, J., Li, F., Song, J., Su, R. & Zou, Q., Jan 2020, In: Briefings in Bioinformatics. 21, 1, p. 106-119 14 p.

  Research output: Contribution to journal › Article › Research › peer-review
  106 Citations (Scopus)

• Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences

  Chen, Z., Zhao, P., Li, F., Wang, Y., Smith, A. I., Webb, G. I., Akutsu, T., Baggag, A., Bensmail, H. & Song, J., 25 Sept 2020, In: Briefings in Bioinformatics. 21, 5, p. 1676-1696 21 p., bbz112.

  Research output: Contribution to journal › Article › Research › peer-review
  104 Citations (Scopus)

• DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites

  Li, F., Chen, J., Leier, A., Marquez-Lago, T., Liu, Q., Wang, Y., Revote, J., Smith, A. I., Akutsu, T., Webb, G. I., Kurgan, L. & Song, J., 15 Feb 2020, In: Bioinformatics. 36, 4, p. 1057-1065 9 p.

  Research output: Contribution to journal › Article › Research › peer-review
  102 Citations (Scopus)

• iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data

  Chen, Z., Zhao, P., Li, F., Marquez-Lago, T. T., Leier, A., Revote, J., Zhu, Y., Powell, D. R., Akutsu, T., Webb, G. I., Chou, K-C., Smith, A. I., Daly, R. J., Li, J. & Song, J., 21 May 2020, In: Briefings in Bioinformatics. 21, 3, p. 1047-1057 11 p.

  Research output: Contribution to journal › Article › Research › peer-review
  315 Citations (Scopus)

• Inspector: a lysine succinylation predictor based on edited nearest-neighbor undersampling and adaptive synthetic oversampling

  Zhu, Y., Jia, C., Li, F. & Song, J., 15 Mar 2020, In: Analytical Biochemistry. 593, 10 p., 113592.

  Research output: Contribution to journal › Article › Research › peer-review
  46 Citations (Scopus)

• PASSION: an ensemble neural network approach for identifying the binding sites of RBPs on circRNAs

  Jia, C., Bi, Y., Chen, J., Leier, A., Li, F. & Song, J., 1 Aug 2020, In: Bioinformatics. 36, 15, p. 4276-4282 7 p.

  Research output: Contribution to journal › Article › Research › peer-review
  69 Citations (Scopus)

• PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins

  Zhang, Y., Yu, S., Xie, R., Li, J., Leier, A., Marquez-Lago, T. T., Akutsu, T., Smith, A. I., Ge, Z., Wang, J., Lithgow, T. & Song, J., 1 Feb 2020, In: Bioinformatics. 36, 3, p. 704-712 9 p.

  Research output: Contribution to journal › Article › Research › peer-review
  41 Citations (Scopus)

• Pippin: A random forest-based method for identifying presynaptic and postsynaptic neurotoxins

  Li, P., Zhang, H., Zhao, X., Jia, C., Li, F. & Song, J., 5 May 2020, In: Journal of Bioinformatics and Computational Biology. 18, 2, 21 p., 2050008.

  Research output: Contribution to journal › Article › Research › peer-review
  1 Citation (Scopus)

• PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

  Li, F., Fan, C., Marquez-Lago, T. T., Leier, A., Revote, J., Jia, C., Zhu, Y., Smith, A. I., Webb, G. I., Liu, Q., Wei, L., Li, J. & Song, J., 21 May 2020, In: Briefings in Bioinformatics. 21, 3, p. 1069-1079 11 p.

  Research output: Contribution to journal › Article › Research › peer-review
  34 Citations (Scopus)

• Procleave: Predicting protease-specific substrate cleavage sites by combining sequence and structural information

  Li, F., Leier, A., Liu, Q., Wang, Y., Xiang, D., Akutsu, T., Webb, G. I., Smith, A. I., Marquez-Lago, T., Li, J. & Song, J., Feb 2020, In: Genomics Proteomics and Bioinformatics. 18, 1, p. 52-64 13 p.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access

  File
  69 Citations (Scopus)

• PROSPECT: A web server for predicting protein histidine phosphorylation sites

  Chen, Z., Zhao, P., Li, F., Leier, A., Marquez-Lago, T. T., Webb, G. I., Baggag, A., Bensmail, H. & Song, J., 2020, In: Journal of Bioinformatics and Computational Biology. 18, 3, 17 p., 2050018.

  Research output: Contribution to journal › Article › Research › peer-review
  24 Citations (Scopus)
• 2019

  Bastion3: A two-layer ensemble predictor of type III secreted effectors

  Wang, J., Li, J., Yang, B., Xie, R., Marquez-Lago, T. T., Leier, A., Hayashida, M., Akutsu, T., Zhang, Y., Chou, K-C., Selkrig, J., Zhou, T., Song, J. & Lithgow, T., 1 Jun 2019, In: Bioinformatics. 35, 12, p. 2017-2028 12 p., bty914.

  Research output: Contribution to journal › Article › Research › peer-review
  67 Citations (Scopus)

• Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework

  Zhang, Y., Xie, R., Wang, J., Leier, A., Marquez-Lago, T. T., Akutsu, T., Webb, G. I., Chou, K-C. & Song, J., Nov 2019, In: Briefings in Bioinformatics. 20, 6, p. 2185-2199 15 p.

  Research output: Contribution to journal › Article › Research › peer-review
  76 Citations (Scopus)

• Large-scale comparative assessment of computational predictors for lysine post-translational modification sites

  Chen, Z., Liu, X., Li, F., Li, C., Marquez-Lago, T., Leier, A., Akutsu, T., Webb, G. I., Xu, D., Smith, A. I., Li, L., Chou, K. C. & Song, J., Nov 2019, In: Briefings in Bioinformatics. 20, 6, p. 2267-2290 24 p., bby089.

  Research output: Contribution to journal › Article › Research › peer-review
  92 Citations (Scopus)

• MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters

  Zhang, M., Li, F., Marquez-Lago, T. T., Leier, A., Fan, C., Kwoh, C. K., Chou, K-C., Song, J. & Jia, C., 1 Sept 2019, In: Bioinformatics. 35, 17, p. 2957-2965 9 p., btz016.

  Research output: Contribution to journal › Article › Research › peer-review
  103 Citations (Scopus)

• Positive-unlabelled learning of glycosylation sites in the human proteome

  Li, F., Zhang, Y., Purcell, A. W., Webb, G. I., Chou, K-C., Lithgow, T., Li, C. & Song, J., 6 Mar 2019, In: BMC Bioinformatics. 20, 1, 17 p., 112.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access

  File
  66 Citations (Scopus)

• SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models

  Wang, X., Li, C., Li, F., Sharma, V. S., Song, J. & Webb, G. I., 21 Nov 2019, In: BMC Bioinformatics. 20, 1, 12 p., 602.

  Research output: Contribution to journal › Article › Research › peer-review

  Open Access

  File
  11 Citations (Scopus)

• Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches

  Wang, J., Yang, B., An, Y., Marquez-Lago, T., Leier, A., Wilksch, J., Hong, Q., Zhang, Y., Hayashida, M., Akutsu, T., Webb, G. I., Strugnell, R. A., Song, J. & Lithgow, T., 21 May 2019, In: Briefings in Bioinformatics. 20, 3, p. 931-951 21 p.

  Research output: Contribution to journal › Article › Research › peer-review
  64 Citations (Scopus)