132 related articles for article (PubMed ID: 33488064)
1. NLPEI: A Novel Self-Interacting Protein Prediction Model Based on Natural Language Processing and Evolutionary Information.
Jia LN; Yan X; You ZH; Zhou X; Li LP; Wang L; Song KJ
Evol Bioinform Online; 2020; 16():1176934320984171. PubMed ID: 33488064
[TBL] [Abstract][Full Text] [Related]
2. Improving Prediction of Self-interacting Proteins Using Stacked Sparse Auto-Encoder with PSSM profiles.
Wang YB; You ZH; Li LP; Huang DS; Zhou FF; Yang S
Int J Biol Sci; 2018; 14(8):983-991. PubMed ID: 29989064
[TBL] [Abstract][Full Text] [Related]
3. Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information.
An JY; Zhang L; Zhou Y; Zhao YJ; Wang DF
J Cheminform; 2017 Aug; 9(1):47. PubMed ID: 29086182
[TBL] [Abstract][Full Text] [Related]
4. Robust and accurate prediction of self-interacting proteins from protein sequence information by exploiting weighted sparse representation based classifier.
Li Y; Hu XG; You ZH; Li LP; Li PP; Wang YB; Huang YA
BMC Bioinformatics; 2022 Dec; 23(Suppl 7):518. PubMed ID: 36457083
[TBL] [Abstract][Full Text] [Related]
5. 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; 20(Suppl 13):928. PubMed ID: 31881833
[TBL] [Abstract][Full Text] [Related]
6. Predicting Self-Interacting Proteins Using a Recurrent Neural Network and Protein Evolutionary Information.
An JY; Zhou Y; Yan ZJ; Zhao YJ
Evol Bioinform Online; 2020; 16():1176934320924674. PubMed ID: 32550764
[TBL] [Abstract][Full Text] [Related]
7. Prediction of protein self-interactions using stacked long short-term memory from protein sequences information.
Wang YB; You ZH; Li X; Jiang TH; Cheng L; Chen ZH
BMC Syst Biol; 2018 Dec; 12(Suppl 8):129. PubMed ID: 30577794
[TBL] [Abstract][Full Text] [Related]
8. PSPEL: In Silico Prediction of Self-Interacting Proteins from Amino Acids Sequences Using Ensemble Learning.
Li JQ; You ZH; Li X; Ming Z; Chen X
IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(5):1165-1172. PubMed ID: 28092572
[TBL] [Abstract][Full Text] [Related]
9. Global Vectors Representation of Protein Sequences and Its Application for Predicting Self-Interacting Proteins with Multi-Grained Cascade Forest Model.
Chen ZH; You ZH; Zhang WB; Wang YB; Cheng L; Alghazzawi D
Genes (Basel); 2019 Nov; 10(11):. PubMed ID: 31726752
[TBL] [Abstract][Full Text] [Related]
10. An Improved Deep Forest Model for Predicting Self-Interacting Proteins From Protein Sequence Using Wavelet Transformation.
Chen ZH; Li LP; He Z; Zhou JR; Li Y; Wong L
Front Genet; 2019; 10():90. PubMed ID: 30881376
[TBL] [Abstract][Full Text] [Related]
11. Prediction of Self-Interacting Proteins from Protein Sequence Information Based on Random Projection Model and Fast Fourier Transform.
Chen ZH; You ZH; Li LP; Wang YB; Wong L; Yi HC
Int J Mol Sci; 2019 Feb; 20(4):. PubMed ID: 30795499
[TBL] [Abstract][Full Text] [Related]
12. Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC.
Zhai JX; Cao TJ; An JY; Bian YT
J Theor Biol; 2017 Nov; 432():80-86. PubMed ID: 28802824
[TBL] [Abstract][Full Text] [Related]
13. Identification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix.
An JY; You ZH; Chen X; Huang DS; Li ZW; Liu G; Wang Y
Oncotarget; 2016 Dec; 7(50):82440-82449. PubMed ID: 27732957
[TBL] [Abstract][Full Text] [Related]
14. Robust and accurate prediction of protein self-interactions from amino acids sequence using evolutionary information.
An JY; You ZH; Chen X; Huang DS; Yan G; Wang DF
Mol Biosyst; 2016 Nov; 12(12):3702-3710. PubMed ID: 27759121
[TBL] [Abstract][Full Text] [Related]
15. Computational Models for Self-Interacting Proteins Prediction.
Qu J; Zhao Y; Zhang L; Cai SB; Ming Z; Wang CC
Protein Pept Lett; 2020; 27(5):392-399. PubMed ID: 31880240
[TBL] [Abstract][Full Text] [Related]
16. An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot features.
An JY; Meng FR; Yan ZJ
BioData Min; 2021 Jan; 14(1):3. PubMed ID: 33472664
[TBL] [Abstract][Full Text] [Related]
17. Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.
Li ZW; You ZH; Chen X; Li LP; Huang DS; Yan GY; Nie R; Huang YA
Oncotarget; 2017 Apr; 8(14):23638-23649. PubMed ID: 28423569
[TBL] [Abstract][Full Text] [Related]
18. 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; 418():105-110. PubMed ID: 28088356
[TBL] [Abstract][Full Text] [Related]
19. BGFE: A Deep Learning Model for ncRNA-Protein Interaction Predictions Based on Improved Sequence Information.
Zhan ZH; Jia LN; Zhou Y; Li LP; Yi HC
Int J Mol Sci; 2019 Feb; 20(4):. PubMed ID: 30813451
[TBL] [Abstract][Full Text] [Related]
20. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM.
Gao ZG; Wang L; Xia SX; You ZH; Yan X; Zhou Y
Biomed Res Int; 2016; 2016():4563524. PubMed ID: 27437399
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]