These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
152 related articles for article (PubMed ID: 22489173)
1. Prediction of bioluminescent proteins using auto covariance transformation of evolutional profiles. Zhao X; Li J; Huang Y; Ma Z; Yin M Int J Mol Sci; 2012; 13(3):3650-3660. PubMed ID: 22489173 [TBL] [Abstract][Full Text] [Related]
2. Using support vector machine and evolutionary profiles to predict antifreeze protein sequences. Zhao X; Ma Z; Yin M Int J Mol Sci; 2012; 13(2):2196-2207. PubMed ID: 22408447 [TBL] [Abstract][Full Text] [Related]
3. 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 [TBL] [Abstract][Full Text] [Related]
4. iBLP: An XGBoost-Based Predictor for Identifying Bioluminescent Proteins. Zhang D; Chen HD; Zulfiqar H; Yuan SS; Huang QL; Zhang ZY; Deng KJ Comput Math Methods Med; 2021; 2021():6664362. PubMed ID: 33505515 [TBL] [Abstract][Full Text] [Related]
5. Accurate prediction of protein structural class using auto covariance transformation of PSI-BLAST profiles. Liu T; Geng X; Zheng X; Li R; Wang J Amino Acids; 2012 Jun; 42(6):2243-9. PubMed ID: 21698456 [TBL] [Abstract][Full Text] [Related]
6. BLProt: prediction of bioluminescent proteins based on support vector machine and relieff feature selection. Kandaswamy KK; Pugalenthi G; Hazrati MK; Kalies KU; Martinetz T BMC Bioinformatics; 2011 Aug; 12():345. PubMed ID: 21849049 [TBL] [Abstract][Full Text] [Related]
7. Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition. Fan GL; Li QZ J Theor Biol; 2013 Oct; 334():45-51. PubMed ID: 23770403 [TBL] [Abstract][Full Text] [Related]
8. 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; 17(5):. PubMed ID: 27213337 [TBL] [Abstract][Full Text] [Related]
9. IDRBP-PPCT: Identifying Nucleic Acid-Binding Proteins Based on Position-Specific Score Matrix and Position-Specific Frequency Matrix Cross Transformation. Wang N; Zhang J; Liu B IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(4):2284-2293. PubMed ID: 33780341 [TBL] [Abstract][Full Text] [Related]
10. Using auto covariance method for functional discrimination of membrane proteins based on evolution information. Yang L; Li Y; Xiao R; Zeng Y; Xiao J; Tan F; Li M Amino Acids; 2010 May; 38(5):1497-503. PubMed ID: 19820894 [TBL] [Abstract][Full Text] [Related]
11. Prediction of nuclear proteins using nuclear translocation signals proposed by probabilistic latent semantic indexing. Su EC; Chang JM; Cheng CW; Sung TY; Hsu WL BMC Bioinformatics; 2012; 13 Suppl 17(Suppl 17):S13. PubMed ID: 23282098 [TBL] [Abstract][Full Text] [Related]
12. Propensity scores for prediction and characterization of bioluminescent proteins from sequences. Huang HL PLoS One; 2014; 9(5):e97158. PubMed ID: 24828431 [TBL] [Abstract][Full Text] [Related]
13. Prediction of membrane transport proteins and their substrate specificities using primary sequence information. Mishra NK; Chang J; Zhao PX PLoS One; 2014; 9(6):e100278. PubMed ID: 24968309 [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. 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]
16. 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]
17. 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; 18(5):. PubMed ID: 28492483 [TBL] [Abstract][Full Text] [Related]
18. Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model. An JY; Meng FR; You ZH; Chen X; Yan GY; Hu JP Protein Sci; 2016 Oct; 25(10):1825-33. PubMed ID: 27452983 [TBL] [Abstract][Full Text] [Related]
19. Prediction of bioluminescent proteins by using sequence-derived features and lineage-specific scheme. Zhang J; Chai H; Yang G; Ma Z BMC Bioinformatics; 2017 Jun; 18(1):294. PubMed ID: 28583090 [TBL] [Abstract][Full Text] [Related]
20. A novel fusion based on the evolutionary features for protein fold recognition using support vector machines. Refahi MS; Mir A; Nasiri JA Sci Rep; 2020 Sep; 10(1):14368. PubMed ID: 32873824 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]