105 related articles for article (PubMed ID: 25708089)
1. PNImodeler: web server for inferring protein-binding nucleotides from sequence data.
Im J; Tuvshinjargal N; Park B; Lee W; Huang DS; Han K
BMC Genomics; 2015; 16 Suppl 3(Suppl 3):S6. PubMed ID: 25708089
[TBL] [Abstract][Full Text] [Related]
2. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.
Park B; Im J; Tuvshinjargal N; Lee W; Han K
Comput Methods Programs Biomed; 2014 Nov; 117(2):158-67. PubMed ID: 25113160
[TBL] [Abstract][Full Text] [Related]
3. Predicting protein-binding RNA nucleotides using the feature-based removal of data redundancy and the interaction propensity of nucleotide triplets.
Choi S; Han K
Comput Biol Med; 2013 Nov; 43(11):1687-97. PubMed ID: 24209914
[TBL] [Abstract][Full Text] [Related]
4. Predicting protein-binding regions in RNA using nucleotide profiles and compositions.
Choi D; Park B; Chae H; Lee W; Han K
BMC Syst Biol; 2017 Mar; 11(Suppl 2):16. PubMed ID: 28361677
[TBL] [Abstract][Full Text] [Related]
5. Predicting protein-binding RNA nucleotides with consideration of binding partners.
Tuvshinjargal N; Lee W; Park B; Han K
Comput Methods Programs Biomed; 2015 Jun; 120(1):3-15. PubMed ID: 25907142
[TBL] [Abstract][Full Text] [Related]
6. Design of accurate predictors for DNA-binding sites in proteins using hybrid SVM-PSSM method.
Ho SY; Yu FC; Chang CY; Huang HL
Biosystems; 2007; 90(1):234-41. PubMed ID: 17275170
[TBL] [Abstract][Full Text] [Related]
7. PSSM-based prediction of DNA binding sites in proteins.
Ahmad S; Sarai A
BMC Bioinformatics; 2005 Feb; 6():33. PubMed ID: 15720719
[TBL] [Abstract][Full Text] [Related]
8. Using evolutionary and structural information to predict DNA-binding sites on DNA-binding proteins.
Kuznetsov IB; Gou Z; Li R; Hwang S
Proteins; 2006 Jul; 64(1):19-27. PubMed ID: 16568445
[TBL] [Abstract][Full Text] [Related]
9. Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein.
Raghava GP; Han JH
BMC Bioinformatics; 2005 Mar; 6():59. PubMed ID: 15773999
[TBL] [Abstract][Full Text] [Related]
10. Prediction of RNA binding sites in a protein using SVM and PSSM profile.
Kumar M; Gromiha MM; Raghava GP
Proteins; 2008 Apr; 71(1):189-94. PubMed ID: 17932917
[TBL] [Abstract][Full Text] [Related]
11. Prediction of RNA-binding amino acids from protein and RNA sequences.
Choi S; Han K
BMC Bioinformatics; 2011; 12 Suppl 13(Suppl 13):S7. PubMed ID: 22373313
[TBL] [Abstract][Full Text] [Related]
12. SVM based prediction of RNA-binding proteins using binding residues and evolutionary information.
Kumar M; Gromiha MM; Raghava GP
J Mol Recognit; 2011; 24(2):303-13. PubMed ID: 20677174
[TBL] [Abstract][Full Text] [Related]
13. Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides.
Panwar B; Raghava GP
Genomics; 2015 Apr; 105(4):197-203. PubMed ID: 25640448
[TBL] [Abstract][Full Text] [Related]
14. DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins.
Hwang S; Gou Z; Kuznetsov IB
Bioinformatics; 2007 Mar; 23(5):634-6. PubMed ID: 17237068
[TBL] [Abstract][Full Text] [Related]
15. Prediction of protein subcellular localization.
Yu CS; Chen YC; Lu CH; Hwang JK
Proteins; 2006 Aug; 64(3):643-51. PubMed ID: 16752418
[TBL] [Abstract][Full Text] [Related]
16. PRIdictor: Protein-RNA Interaction predictor.
Tuvshinjargal N; Lee W; Park B; Han K
Biosystems; 2016 Jan; 139():17-22. PubMed ID: 26607710
[TBL] [Abstract][Full Text] [Related]
17. Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure.
Lewis DP; Jebara T; Noble WS
Bioinformatics; 2006 Nov; 22(22):2753-60. PubMed ID: 16966363
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. A general computational model for predicting ribosomal frameshifts in genome sequences.
Byun Y; Moon S; Han K
Comput Biol Med; 2007 Dec; 37(12):1796-801. PubMed ID: 17678640
[TBL] [Abstract][Full Text] [Related]
20. MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes.
Marinescu VD; Kohane IS; Riva A
BMC Bioinformatics; 2005 Mar; 6():79. PubMed ID: 15799782
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
