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Items: 1 to 20 of 236

1.

Prediction of B-cell epitopes using evolutionary information and propensity scales.

Lin SY, Cheng CW, Su EC.

BMC Bioinformatics. 2013;14 Suppl 2:S10.

2.

Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature.

Zhang W, Xiong Y, Zhao M, Zou H, Ye X, Liu J.

BMC Bioinformatics. 2011 Aug 17;12:341. doi: 10.1186/1471-2105-12-341.

3.

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

Wang HW, Lin YC, Pai TW, Chang HT.

J Biomed Biotechnol. 2011;2011:432830. doi: 10.1155/2011/432830. Epub 2011 Aug 23.

4.

Predicting RNA-binding sites of proteins using support vector machines and evolutionary information.

Cheng CW, Su EC, Hwang JK, Sung TY, Hsu WL.

BMC Bioinformatics. 2008 Dec 12;9 Suppl 12:S6. doi: 10.1186/1471-2105-9-S12-S6.

5.

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:S13. doi: 10.1186/1471-2105-13-S17-S13. Epub 2012 Dec 13.

6.

SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity.

Yao B, Zhang L, Liang S, Zhang C.

PLoS One. 2012;7(9):e45152. doi: 10.1371/journal.pone.0045152. Epub 2012 Sep 12.

7.

Computational prediction of conformational B-cell epitopes from antigen primary structures by ensemble learning.

Zhang W, Niu Y, Xiong Y, Zhao M, Yu R, Liu J.

PLoS One. 2012;7(8):e43575. doi: 10.1371/journal.pone.0043575. Epub 2012 Aug 21.

8.

Improved method for linear B-cell epitope prediction using antigen's primary sequence.

Singh H, Ansari HR, Raghava GP.

PLoS One. 2013 May 7;8(5):e62216. doi: 10.1371/journal.pone.0062216. Print 2013.

9.

Harnessing Computational Biology for Exact Linear B-Cell Epitope Prediction: A Novel Amino Acid Composition-Based Feature Descriptor.

Saravanan V, Gautham N.

OMICS. 2015 Oct;19(10):648-58. doi: 10.1089/omi.2015.0095. Epub 2015 Sep 25.

PMID:
26406767
10.

Using random forest to classify linear B-cell epitopes based on amino acid properties and molecular features.

Huang JH, Wen M, Tang LJ, Xie HL, Fu L, Liang YZ, Lu HM.

Biochimie. 2014 Aug;103:1-6. doi: 10.1016/j.biochi.2014.03.016. Epub 2014 Apr 8.

PMID:
24721579
11.

EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results.

Liang S, Zheng D, Standley DM, Yao B, Zacharias M, Zhang C.

BMC Bioinformatics. 2010 Jul 16;11:381. doi: 10.1186/1471-2105-11-381.

12.

EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.

Lian Y, Ge M, Pan XM.

BMC Bioinformatics. 2014 Dec 19;15:414. doi: 10.1186/s12859-014-0414-y.

13.

An ensemble method for prediction of conformational B-cell epitopes from antigen sequences.

Zheng W, Zhang C, Hanlon M, Ruan J, Gao J.

Comput Biol Chem. 2014 Apr;49:51-8. doi: 10.1016/j.compbiolchem.2014.02.002. Epub 2014 Feb 18.

PMID:
24607818
14.
15.

Predicting B cell epitope residues with network topology based amino acid indices.

Huang J, Honda W, Kanehisa M.

Genome Inform. 2007;19:40-9.

PMID:
18546503
16.

Machine learning-based methods for prediction of linear B-cell epitopes.

Wang HW, Pai TW.

Methods Mol Biol. 2014;1184:217-36. doi: 10.1007/978-1-4939-1115-8_12. Review.

PMID:
25048127
17.

Predicting linear B-cell epitopes by using sequence-derived structural and physicochemical features.

Zhang W, Liu J, Zhao M, Li Q.

Int J Data Min Bioinform. 2012;6(5):557-69.

PMID:
23155782
18.

Classification epitopes in groups based on their protein family.

Kozlova E, Viart B, de Avila R, Felicori L, Chavez-Olortegui C.

BMC Bioinformatics. 2015;16 Suppl 19:S7. doi: 10.1186/1471-2105-16-S19-S7. Epub 2015 Dec 16.

19.

Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis.

Huang YX, Bao YL, Guo SY, Wang Y, Zhou CG, Li YX.

BMC Bioinformatics. 2008 Dec 16;9:538. doi: 10.1186/1471-2105-9-538.

20.

Machine learning approaches for prediction of linear B-cell epitopes on proteins.

Söllner J, Mayer B.

J Mol Recognit. 2006 May-Jun;19(3):200-8.

PMID:
16598694
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