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Journal Abstract Search
671 related items for PubMed ID: 35242211
1. Predicting Protein-Protein Interactions via Random Ferns with Evolutionary Matrix Representation. Li Y, Wang Z, You ZH, Li LP, Hu X. Comput Math Methods Med; 2022; 2022():7191684. PubMed ID: 35242211 [Abstract] [Full Text] [Related]
2. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences. An JY, You ZH, Meng FR, Xu SJ, Wang Y. Int J Mol Sci; 2016 May 18; 17(5):. PubMed ID: 27213337 [Abstract] [Full Text] [Related]
3. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences. Wang Y, You Z, Li X, Chen X, Jiang T, Zhang J. Int J Mol Sci; 2017 May 11; 18(5):. PubMed ID: 28492483 [Abstract] [Full Text] [Related]
7. Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest. You ZH, Chan KC, Hu P. PLoS One; 2015 May 11; 10(5):e0125811. PubMed ID: 25946106 [Abstract] [Full Text] [Related]
12. Advancing the prediction accuracy of protein-protein interactions by utilizing evolutionary information from position-specific scoring matrix and ensemble classifier. Wang L, You ZH, Xia SX, Liu F, Chen X, Yan X, Zhou Y. J Theor Biol; 2017 Apr 07; 418():105-110. PubMed ID: 28088356 [Abstract] [Full Text] [Related]
13. Predicting Protein-Protein Interactions from Matrix-Based Protein Sequence Using Convolution Neural Network and Feature-Selective Rotation Forest. Wang L, Wang HF, Liu SR, Yan X, Song KJ. Sci Rep; 2019 Jul 08; 9(1):9848. PubMed ID: 31285519 [Abstract] [Full Text] [Related]
14. Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition. Huang YA, You ZH, Chen X, Yan GY. BMC Syst Biol; 2016 Dec 23; 10(Suppl 4):120. PubMed ID: 28155718 [Abstract] [Full Text] [Related]
16. Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter. Chen ZH, You ZH, Li LP, Wang YB, Qiu Y, Hu PW. BMC Genomics; 2019 Dec 27; 20(Suppl 13):928. PubMed ID: 31881833 [Abstract] [Full Text] [Related]
17. Predicting protein-protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach. Tian B, Wu X, Chen C, Qiu W, Ma Q, Yu B. J Theor Biol; 2019 Feb 07; 462():329-346. PubMed ID: 30452960 [Abstract] [Full Text] [Related]
18. Protein features fusion using attributed network embedding for predicting protein-protein interaction. Cao MY, Zainudin S, Daud KM. BMC Genomics; 2024 May 13; 25(1):466. PubMed ID: 38741045 [Abstract] [Full Text] [Related]
19. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis. You ZH, Lei YK, Zhu L, Xia J, Wang B. BMC Bioinformatics; 2013 May 13; 14 Suppl 8(Suppl 8):S10. PubMed ID: 23815620 [Abstract] [Full Text] [Related]
20. Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding. Huang YA, You ZH, Chen X, Chan K, Luo X. BMC Bioinformatics; 2016 Apr 26; 17(1):184. PubMed ID: 27112932 [Abstract] [Full Text] [Related] Page: [Next] [New Search]