88 related articles for article (PubMed ID: 20658339)
1. Prediction of non-classical secreted proteins using informative physicochemical properties.
Hung CH; Huang HL; Hsu KT; Ho SJ; Ho SY
Interdiscip Sci; 2010 Sep; 2(3):263-70. PubMed ID: 20658339
[TBL] [Abstract][Full Text] [Related]
2. A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search.
Garg A; Raghava GP
In Silico Biol; 2008; 8(2):129-40. PubMed ID: 18928201
[TBL] [Abstract][Full Text] [Related]
3. SecretP: a new method for predicting mammalian secreted proteins.
Yu L; Guo Y; Zhang Z; Li Y; Li M; Li G; Xiong W; Zeng Y
Peptides; 2010 Apr; 31(4):574-8. PubMed ID: 20045033
[TBL] [Abstract][Full Text] [Related]
4. Sequence based human leukocyte antigen gene prediction using informative physicochemical properties.
Shoombuatong W; Mekha P; Chaijaruwanich J
Int J Data Min Bioinform; 2015; 13(3):211-24. PubMed ID: 26547977
[TBL] [Abstract][Full Text] [Related]
5. Ranking Gene Ontology terms for predicting non-classical secretory proteins in eukaryotes and prokaryotes.
Huang WL
J Theor Biol; 2012 Nov; 312():105-13. PubMed ID: 22967952
[TBL] [Abstract][Full Text] [Related]
6. A new hybrid coding for protein secondary structure prediction based on primary structure similarity.
Li Z; Wang J; Zhang S; Zhang Q; Wu W
Gene; 2017 Jun; 618():8-13. PubMed ID: 28322997
[TBL] [Abstract][Full Text] [Related]
7. Signal peptide discrimination and cleavage site identification using SVM and NN.
Kazemian HB; Yusuf SA; White K
Comput Biol Med; 2014 Feb; 45():98-110. PubMed ID: 24480169
[TBL] [Abstract][Full Text] [Related]
8. SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes.
Kandaswamy KK; Pugalenthi G; Hartmann E; Kalies KU; Möller S; Suganthan PN; Martinetz T
Biochem Biophys Res Commun; 2010 Jan; 391(3):1306-11. PubMed ID: 19995554
[TBL] [Abstract][Full Text] [Related]
9. Computational identification of ubiquitylation sites from protein sequences.
Tung CW; Ho SY
BMC Bioinformatics; 2008 Jul; 9():310. PubMed ID: 18625080
[TBL] [Abstract][Full Text] [Related]
10. The accurate prediction of protein family from amino acid sequence by measuring features of sequence fragments.
Hong H; Hong Q; Perkins R; Shi L; Fang H; Su Z; Dragan Y; Fuscoe JC; Tong W
J Comput Biol; 2009 Dec; 16(12):1671-88. PubMed ID: 20047490
[TBL] [Abstract][Full Text] [Related]
11. Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach.
Lin HH; Han LY; Zhang HL; Zheng CJ; Xie B; Cao ZW; Chen YZ
BMC Bioinformatics; 2006 Dec; 7 Suppl 5(Suppl 5):S13. PubMed ID: 17254297
[TBL] [Abstract][Full Text] [Related]
12. Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties.
Huang HL; Lin IC; Liou YF; Tsai CT; Hsu KT; Huang WL; Ho SJ; Ho SY
BMC Bioinformatics; 2011 Feb; 12 Suppl 1(Suppl 1):S47. PubMed ID: 21342579
[TBL] [Abstract][Full Text] [Related]
13. Remote homology detection incorporating the context of physicochemical properties.
Bedoya O; Tischer I
Comput Biol Med; 2014 Feb; 45():43-50. PubMed ID: 24480162
[TBL] [Abstract][Full Text] [Related]
14. Properties and identification of human protein drug targets.
Bakheet TM; Doig AJ
Bioinformatics; 2009 Feb; 25(4):451-7. PubMed ID: 19164304
[TBL] [Abstract][Full Text] [Related]
15. Prediction of ubiquitin proteins using artificial neural networks, hidden markov model and support vector machines.
Jaiswal K
In Silico Biol; 2007; 7(6):559-68. PubMed ID: 18467768
[TBL] [Abstract][Full Text] [Related]
16. Protein location prediction using atomic composition and global features of the amino acid sequence.
Cherian BS; Nair AS
Biochem Biophys Res Commun; 2010 Jan; 391(4):1670-4. PubMed ID: 20036215
[TBL] [Abstract][Full Text] [Related]
17. Support Vector Machine-based classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs.
Shamim MT; Anwaruddin M; Nagarajaram HA
Bioinformatics; 2007 Dec; 23(24):3320-7. PubMed ID: 17989092
[TBL] [Abstract][Full Text] [Related]
18. Using amino acid physicochemical distance transformation for fast protein remote homology detection.
Liu B; Wang X; Chen Q; Dong Q; Lan X
PLoS One; 2012; 7(9):e46633. PubMed ID: 23029559
[TBL] [Abstract][Full Text] [Related]
19. Prediction of neurotoxins by support vector machine based on multiple feature vectors.
Guang XM; Guo YZ; Wang X; Li ML
Interdiscip Sci; 2010 Sep; 2(3):241-6. PubMed ID: 20658336
[TBL] [Abstract][Full Text] [Related]
20. Predict potential drug targets from the ion channel proteins based on SVM.
Huang C; Zhang R; Chen Z; Jiang Y; Shang Z; Sun P; Zhang X; Li X
J Theor Biol; 2010 Feb; 262(4):750-6. PubMed ID: 19903486
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
