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.
203 related articles for article (PubMed ID: 23988798)
1. iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints. Xiao X; Min JL; Wang P; Chou KC J Theor Biol; 2013 Nov; 337():71-9. PubMed ID: 23988798 [TBL] [Abstract][Full Text] [Related]
2. Predict drug-protein interaction in cellular networking. Xiao X; Min JL; Wang P; Chou KC Curr Top Med Chem; 2013; 13(14):1707-12. PubMed ID: 23889048 [TBL] [Abstract][Full Text] [Related]
3. iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking. Xiao X; Min JL; Wang P; Chou KC PLoS One; 2013; 8(8):e72234. PubMed ID: 24015221 [TBL] [Abstract][Full Text] [Related]
4. iCDI-W2vCom: Identifying the Ion Channel-Drug Interaction in Cellular Networking Based on word2vec and node2vec. Zheng J; Xiao X; Qiu WR Front Genet; 2021; 12():738274. PubMed ID: 34567088 [TBL] [Abstract][Full Text] [Related]
5. iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach. Xiao X; Min JL; Lin WZ; Liu Z; Cheng X; Chou KC J Biomol Struct Dyn; 2015; 33(10):2221-33. PubMed ID: 25513722 [TBL] [Abstract][Full Text] [Related]
6. iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC. Jia J; Liu Z; Xiao X; Liu B; Chou KC J Theor Biol; 2015 Jul; 377():47-56. PubMed ID: 25908206 [TBL] [Abstract][Full Text] [Related]
7. iCataly-PseAAC: Identification of Enzymes Catalytic Sites Using Sequence Evolution Information with Grey Model GM (2,1). Xiao X; Hui MJ; Liu Z; Qiu WR J Membr Biol; 2015 Dec; 248(6):1033-41. PubMed ID: 26077845 [TBL] [Abstract][Full Text] [Related]
8. GPCR-2L: predicting G protein-coupled receptors and their types by hybridizing two different modes of pseudo amino acid compositions. Xiao X; Wang P; Chou KC Mol Biosyst; 2011 Mar; 7(3):911-9. PubMed ID: 21180772 [TBL] [Abstract][Full Text] [Related]
9. iEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networking. Min JL; Xiao X; Chou KC Biomed Res Int; 2013; 2013():701317. PubMed ID: 24371828 [TBL] [Abstract][Full Text] [Related]
10. iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition. Feng PM; Chen W; Lin H; Chou KC Anal Biochem; 2013 Nov; 442(1):118-25. PubMed ID: 23756733 [TBL] [Abstract][Full Text] [Related]
11. Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system model. Lin WZ; Fang JA; Xiao X; Chou KC PLoS One; 2012; 7(11):e49040. PubMed ID: 23189138 [TBL] [Abstract][Full Text] [Related]
12. iUbiq-Lys: prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a gray system model. Qiu WR; Xiao X; Lin WZ; Chou KC J Biomol Struct Dyn; 2015; 33(8):1731-42. PubMed ID: 25248923 [TBL] [Abstract][Full Text] [Related]
13. iTIS-PseTNC: a sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition. Chen W; Feng PM; Deng EZ; Lin H; Chou KC Anal Biochem; 2014 Oct; 462():76-83. PubMed ID: 25016190 [TBL] [Abstract][Full Text] [Related]
14. iPPI-PseAAC(CGR): Identify protein-protein interactions by incorporating chaos game representation into PseAAC. Jia J; Li X; Qiu W; Xiao X; Chou KC J Theor Biol; 2019 Jan; 460():195-203. PubMed ID: 30312687 [TBL] [Abstract][Full Text] [Related]
15. iDNA-Methyl: identifying DNA methylation sites via pseudo trinucleotide composition. Liu Z; Xiao X; Qiu WR; Chou KC Anal Biochem; 2015 Apr; 474():69-77. PubMed ID: 25596338 [TBL] [Abstract][Full Text] [Related]