Special Protein Molecules Computational Identification

Author(s): Fei Guo

Journal Name: Current Proteomics

Volume 17 , Issue 4 , 2020

DOI : 10.2174/157016461704200514074413

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[1]
Shen, Y.; Tang, J.; Guo, F. Identification of protein subcellular localization via integrating evolutionary and physicochemical information into Chou’s general PseAAC. J. Theor. Biol., 2019, 462, 230-239.
[http://dx.doi.org/10.1016/j.jtbi.2018.11.012] [PMID: 30452958]
[2]
Shen, C.; Jiang, L.; Ding, Y.; Tang, J.; Guo, F. LPI-KTASLP: Prediction of lncRNA-protein interaction by semi-supervised link learning with multivariate information. IEEE Access, 2019, 7, 13486-13496.
[http://dx.doi.org/10.1109/ACCESS.2019.2894225]
[3]
Song, J.; Tang, J.; Guo, F. Identification of inhibitors of MMPS enzymes via a novel computational approach. Int. J. Biol. Sci., 2018, 14(8), 863-871.
[http://dx.doi.org/10.7150/ijbs.24588] [PMID: 29989088]
[4]
Wei, L.; Xing, P.; Shi, G.; Ji, Z.; Zou, Q. Fast prediction of protein methylation sites using a sequence-based feature selection technique. IEEE/ACM Trans. Comput. Biol. Bioinformatics, 2019, 16(4), 1264-1273.
[http://dx.doi.org/10.1109/TCBB.2017.2670558] [PMID: 28222000]
[5]
Li, Z.; Zhao, Y.; Pan, G.; Tang, J.; Guo, F. A novel peptide binding prediction approach for HLA-DR molecule based on sequence and structural information. BioMed Res. Int., 2016, 2016, 3832176-3832176.
[http://dx.doi.org/10.1155/2016/3832176] [PMID: 27340658]
[6]
Li, Z.; Tang, J.; Guo, F. identification of 14-3-3 proteins phosphopeptide-binding specificity using an affinity-based computational approach. PLoS One, 2016, 11(2) e0147467
[http://dx.doi.org/10.1371/journal.pone.0147467] [PMID: 26828594]
[7]
Li, Z.; Tang, J.; Guo, F. Learning from real imbalanced data of 14-3-3 proteins binding specificity. Neurocomputing, 2016, 217, 83-91.
[http://dx.doi.org/10.1016/j.neucom.2016.03.093]
[8]
Ding, Y.; Tang, J.; Guo, F. Identification of residue-residue contacts using a novel coevolution- based method. Curr. Proteomics, 2016, 13, 122-129.
[http://dx.doi.org/10.2174/157016461302160514004105]
[9]
Wei, L.; Xing, P.; Su, R.; Shi, G.; Ma, Z.S.; Zou, Q. CPPred-RF: A sequence-based predictor for identifying cell-penetrating peptides and their uptake Efficiency. J. Proteome Res., 2017, 16(5), 2044-2053.
[http://dx.doi.org/10.1021/acs.jproteome.7b00019] [PMID: 28436664]
[10]
Shen, C.; Ding, Y.; Tang, J.; Xu, X.; Guo, F. An ameliorated prediction of drug-target interactions based on multi-scale discrete wavelet transform and network features. Int. J. Mol. Sci., 2017, 18(8) E1781
[http://dx.doi.org/10.3390/ijms18081781] [PMID: 28813000]
[11]
Shen, C.; Ding, Y.; Tang, J.; Song, J.; Guo, F. Identification of DNA-protein binding sites through multi-scale local average blocks on sequence information. Molecules, 2017, 22(12), 2079.
[http://dx.doi.org/10.3390/molecules22122079] [PMID: 29182548]
[12]
Ding, Y.; Tang, J.; Guo, F. identification of protein-ligand binding sites by sequence information and ensemble classifier. J. Chem. Inf. Model., 2017, 57(12), 3149-3161.
[http://dx.doi.org/10.1021/acs.jcim.7b00307] [PMID: 29125297]
[13]
Ding, Y.; Tang, J.; Guo, F. Identification of drug-target interactions via multiple information integration. Inf. Sci., 2017, 418-419, 546-560.
[http://dx.doi.org/10.1016/j.ins.2017.08.045]
[14]
Ding, Y.; Tang, J.; Guo, F. identification of protein-protein interactions via a novel matrix-based sequence representation model with amino acid contact information. Int. J. Mol. Sci., 2016, 17(10), 1623.
[http://dx.doi.org/10.3390/ijms17101623] [PMID: 27669239]
[15]
Ding, Y.; Tang, J.; Guo, F. Predicting protein-protein interactions via multivariate mutual information of protein sequences. BMC Bioinformatics, 2016, 17(1), 398.
[http://dx.doi.org/10.1186/s12859-016-1253-9] [PMID: 27677692]
[16]
Wei, L.; Tang, J.; Zou, Q. Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information. Inf. Sci., 2017, 384, 135-144.
[http://dx.doi.org/10.1016/j.ins.2016.06.026]
[17]
Wei, L.; Ding, Y.; Su, R.; Tang, J.; Zou, Q. Prediction of human protein subcellular localization using deep learning. J. Parallel Distrib. Comput., 2017, 117, 212-217.
[http://dx.doi.org/10.1016/j.jpdc.2017.08.009]


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Article Details

VOLUME: 17
ISSUE: 4
Year: 2020
Published on: 29 June, 2020
Page: [256 - 257]
Pages: 2
DOI: 10.2174/157016461704200514074413

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