De-Shuang Huang


Affiliation: Tongji University
Location: Shanghai, China


  1. Yuan L, Huang D. A Network-guided Association Mapping Approach from DNA Methylation to Disease. Sci Rep. 2019;9:5601 pubmed publisher
    ..Furthermore, we applied NAMDD to ovarian cancer data, identified significant path associations and provided hypothetical biological path associations to explain our findings. ..
  2. Shen Z, Bao W, Huang D. Recurrent Neural Network for Predicting Transcription Factor Binding Sites. Sci Rep. 2018;8:15270 pubmed publisher
    ..The robustness of KEGRU is proved by experiments with different k-mer length, stride window and embedding vector dimension. ..
  3. request reprint
    Huang D, Zhang L, Han K, Deng S, Yang K, Zhang H. Prediction of protein-protein interactions based on protein-protein correlation using least squares regression. Curr Protein Pept Sci. 2014;15:553-60 pubmed
    ..Therefore, LSR(+) is a powerful tool to characterize the protein-protein correlations and to infer PPI, whilst keeping high performance on prediction of PPI networks. ..
  4. Yi H, You Z, Huang D, Li X, Jiang T, Li L. A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information. Mol Ther Nucleic Acids. 2018;11:337-344 pubmed publisher
  5. Chuai G, Ma H, Yan J, Chen M, Hong N, Xue D, et al. DeepCRISPR: optimized CRISPR guide RNA design by deep learning. Genome Biol. 2018;19:80 pubmed publisher
    ..In addition, DeepCRISPR fully automates the identification of sequence and epigenetic features that may affect sgRNA knockout efficacy in a data-driven manner. DeepCRISPR is available at . ..
  6. Deng S, Huang D. SFAPS: an R package for structure/function analysis of protein sequences based on informational spectrum method. Methods. 2014;69:207-12 pubmed publisher
    ..It is released under the GNU General Public License. The R package along with its source code and additional material are freely available at ..
  7. Zhang H, Zhu L, Huang D. WSMD: weakly-supervised motif discovery in transcription factor ChIP-seq data. Sci Rep. 2017;7:3217 pubmed publisher
  8. Guo W, Huang D. An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency. Mol Biosyst. 2017;13:1827-1837 pubmed publisher
    ..We anticipate that our approach will constitute a useful complement to experimental mapping of TF binding, which is beneficial for further study of regulation mechanisms and disease. ..
  9. Bao W, Jiang Z, Huang D. Novel human microbe-disease association prediction using network consistency projection. BMC Bioinformatics. 2017;18:543 pubmed publisher
    ..It is anticipated that NCPHMDA would become an effective biological resource for clinical experimental guidance. ..