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.
2. Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier. Sriwastava BK; Basu S; Maulik U IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(6):1394-404. PubMed ID: 26684462 [TBL] [Abstract][Full Text] [Related]
3. Improved Prediction of Protein-Protein Interaction Mapping on Islam MM; Alam MJ; Ahmed FF; Hasan MM; Mollah MNH Protein Pept Lett; 2021; 28(1):74-83. PubMed ID: 32520672 [TBL] [Abstract][Full Text] [Related]
4. Computational prediction of heme-binding residues by exploiting residue interaction network. Liu R; Hu J PLoS One; 2011; 6(10):e25560. PubMed ID: 21991319 [TBL] [Abstract][Full Text] [Related]
5. Classification and prediction of protein-protein interaction interface using machine learning algorithm. Das S; Chakrabarti S Sci Rep; 2021 Jan; 11(1):1761. PubMed ID: 33469042 [TBL] [Abstract][Full Text] [Related]
6. Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins. Dong Q; Wang X; Lin L; Guan Y BMC Bioinformatics; 2007 May; 8():147. PubMed ID: 17480235 [TBL] [Abstract][Full Text] [Related]
7. Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences. Guo Y; Yu L; Wen Z; Li M Nucleic Acids Res; 2008 May; 36(9):3025-30. PubMed ID: 18390576 [TBL] [Abstract][Full Text] [Related]
8. Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM. Sriwastava BK; Basu S; Maulik U J Biosci; 2015 Oct; 40(4):809-18. PubMed ID: 26564981 [TBL] [Abstract][Full Text] [Related]
9. Computational methods for ubiquitination site prediction using physicochemical properties of protein sequences. Cai B; Jiang X BMC Bioinformatics; 2016 Mar; 17():116. PubMed ID: 26940649 [TBL] [Abstract][Full Text] [Related]
10. Predicting protein-protein interactions based only on sequences information. Shen J; Zhang J; Luo X; Zhu W; Yu K; Chen K; Li Y; Jiang H Proc Natl Acad Sci U S A; 2007 Mar; 104(11):4337-41. PubMed ID: 17360525 [TBL] [Abstract][Full Text] [Related]
11. Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces. Chen CT; Peng HP; Jian JW; Tsai KC; Chang JY; Yang EW; Chen JB; Ho SY; Hsu WL; Yang AS PLoS One; 2012; 7(6):e37706. PubMed ID: 22701576 [TBL] [Abstract][Full Text] [Related]
12. Predicting protein-ligand binding site using support vector machine with protein properties. Wong GY; Leung FH; Ling SH IEEE/ACM Trans Comput Biol Bioinform; 2013; 10(6):1517-29. PubMed ID: 24407309 [TBL] [Abstract][Full Text] [Related]
13. Combining SVM and ECOC for Identification of Protein Complexes from Protein Protein Interaction Networks by Integrating Amino Acids' Physical Properties and Complex Topology. Faridoon A; Sikandar A; Imran M; Ghouri S; Sikandar M; Sikandar W Interdiscip Sci; 2020 Sep; 12(3):264-275. PubMed ID: 32441001 [TBL] [Abstract][Full Text] [Related]
14. Prediction of protein-protein interaction sites using support vector machines. Koike A; Takagi T Protein Eng Des Sel; 2004 Feb; 17(2):165-73. PubMed ID: 15047913 [TBL] [Abstract][Full Text] [Related]
15. APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility. Xia JF; Zhao XM; Song J; Huang DS BMC Bioinformatics; 2010 Apr; 11():174. PubMed ID: 20377884 [TBL] [Abstract][Full Text] [Related]
16. Structure based approach for understanding organism specific recognition of protein-RNA complexes. Nagarajan R; Chothani SP; Ramakrishnan C; Sekijima M; Gromiha MM Biol Direct; 2015 Mar; 10():8. PubMed ID: 25886642 [TBL] [Abstract][Full Text] [Related]
17. Seeing the trees through the forest: sequence-based homo- and heteromeric protein-protein interaction sites prediction using random forest. Hou Q; De Geest PFG; Vranken WF; Heringa J; Feenstra KA Bioinformatics; 2017 May; 33(10):1479-1487. PubMed ID: 28073761 [TBL] [Abstract][Full Text] [Related]
18. A New Feature Vector Based on Gene Ontology Terms for Protein-Protein Interaction Prediction. Bandyopadhyay S; Mallick K IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(4):762-770. PubMed ID: 28113911 [TBL] [Abstract][Full Text] [Related]
19. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines. González AJ; Liao L BMC Bioinformatics; 2010 Oct; 11():537. PubMed ID: 21034480 [TBL] [Abstract][Full Text] [Related]
20. 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] [Next] [New Search]