147 related articles for article (PubMed ID: 21711543)
1. Prediction of plant promoters based on hexamers and random triplet pair analysis.
Azad AK; Shahid S; Noman N; Lee H
Algorithms Mol Biol; 2011 Jun; 6():19. PubMed ID: 21711543
[TBL] [Abstract][Full Text] [Related]
2. Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach.
Anwar F; Baker SM; Jabid T; Mehedi Hasan M; Shoyaib M; Khan H; Walshe R
BMC Bioinformatics; 2008 Oct; 9():414. PubMed ID: 18834544
[TBL] [Abstract][Full Text] [Related]
3. Cancer survival classification using integrated data sets and intermediate information.
Kim S; Park T; Kon M
Artif Intell Med; 2014 Sep; 62(1):23-31. PubMed ID: 24997860
[TBL] [Abstract][Full Text] [Related]
4. Annotation of gene promoters by integrative data-mining of ChIP-seq Pol-II enrichment data.
Gupta R; Wikramasinghe P; Bhattacharyya A; Perez FA; Pal S; Davuluri RV
BMC Bioinformatics; 2010 Jan; 11 Suppl 1(Suppl 1):S65. PubMed ID: 20122241
[TBL] [Abstract][Full Text] [Related]
5. An Efficient Feature Selection Strategy Based on Multiple Support Vector Machine Technology with Gene Expression Data.
Zhang Y; Deng Q; Liang W; Zou X
Biomed Res Int; 2018; 2018():7538204. PubMed ID: 30228989
[TBL] [Abstract][Full Text] [Related]
6. Human pol II promoter prediction: time series descriptors and machine learning.
Gangal R; Sharma P
Nucleic Acids Res; 2005; 33(4):1332-6. PubMed ID: 15741185
[TBL] [Abstract][Full Text] [Related]
7. Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction.
Shi P; Ray S; Zhu Q; Kon MA
BMC Bioinformatics; 2011 Sep; 12():375. PubMed ID: 21939564
[TBL] [Abstract][Full Text] [Related]
8. Computer-assisted lip diagnosis on Traditional Chinese Medicine using multi-class support vector machines.
Li F; Zhao C; Xia Z; Wang Y; Zhou X; Li GZ
BMC Complement Altern Med; 2012 Aug; 12():127. PubMed ID: 22898352
[TBL] [Abstract][Full Text] [Related]
9. Ensemble of heterogeneous classifiers for diagnosis and prediction of coronary artery disease with reduced feature subset.
Velusamy D; Ramasamy K
Comput Methods Programs Biomed; 2021 Jan; 198():105770. PubMed ID: 33027698
[TBL] [Abstract][Full Text] [Related]
10. A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts.
Schneider HW; Raiol T; Brigido MM; Walter MEMT; Stadler PF
BMC Genomics; 2017 Oct; 18(1):804. PubMed ID: 29047334
[TBL] [Abstract][Full Text] [Related]
11. Computational identification of promoters in
Lin Y; Sun M; Zhang J; Li M; Yang K; Wu C; Zulfiqar H; Lai H
Front Microbiol; 2023; 14():1200678. PubMed ID: 37250059
[TBL] [Abstract][Full Text] [Related]
12. Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification.
Lee HS; Hong H; Jung DC; Park S; Kim J
Med Phys; 2017 Jul; 44(7):3604-3614. PubMed ID: 28376281
[TBL] [Abstract][Full Text] [Related]
13. Minimal Patient Clinical Variables to Accurately Predict Stress Echocardiography Outcome: Validation Study Using Machine Learning Techniques.
Bennasar M; Banks D; Price BA; Kardos A
JMIR Cardio; 2020 May; 4(1):e16975. PubMed ID: 32469316
[TBL] [Abstract][Full Text] [Related]
14. Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data.
Becker N; Toedt G; Lichter P; Benner A
BMC Bioinformatics; 2011 May; 12():138. PubMed ID: 21554689
[TBL] [Abstract][Full Text] [Related]
15. Feature selection for gene prediction in metagenomic fragments.
Al-Ajlan A; El Allali A
BioData Min; 2018; 11():9. PubMed ID: 30026811
[TBL] [Abstract][Full Text] [Related]
16. Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.
Liang M; Cai Z; Zhang H; Huang C; Meng Y; Zhao L; Li D; Ma X; Zhao X
Acad Radiol; 2019 Nov; 26(11):1495-1504. PubMed ID: 30711405
[TBL] [Abstract][Full Text] [Related]
17. PlantProm: a database of plant promoter sequences.
Shahmuradov IA; Gammerman AJ; Hancock JM; Bramley PM; Solovyev VV
Nucleic Acids Res; 2003 Jan; 31(1):114-7. PubMed ID: 12519961
[TBL] [Abstract][Full Text] [Related]
18. OP-Triplet-ELM: Identification of real and pseudo microRNA precursors using extreme learning machine with optimal features.
Pian C; Zhang J; Chen YY; Chen Z; Li Q; Li Q; Zhang LY
J Bioinform Comput Biol; 2016 Feb; 14(1):1650006. PubMed ID: 26707924
[TBL] [Abstract][Full Text] [Related]
19. An optimal strategy for prediction of sudden cardiac death through a pioneering feature-selection approach from HRV signal.
Ebrahimzadeh E; Foroutan A; Shams M; Baradaran R; Rajabion L; Joulani M; Fayaz F
Comput Methods Programs Biomed; 2019 Feb; 169():19-36. PubMed ID: 30638589
[TBL] [Abstract][Full Text] [Related]
20. Super.FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data.
Park S; Soh J; Lee H
BMC Bioinformatics; 2021 May; 22(1):269. PubMed ID: 34034645
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
