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Items: 1 to 20 of 142

1.

Machine learning applications in proteomics research: how the past can boost the future.

Kelchtermans P, Bittremieux W, De Grave K, Degroeve S, Ramon J, Laukens K, Valkenborg D, Barsnes H, Martens L.

Proteomics. 2014 Mar;14(4-5):353-66. doi: 10.1002/pmic.201300289. Epub 2014 Jan 21. Review.

PMID:
24323524
2.

Bioinformatic challenges in targeted proteomics.

Reker D, Malmström L.

J Proteome Res. 2012 Sep 7;11(9):4393-402. doi: 10.1021/pr300276f. Epub 2012 Aug 23.

PMID:
22866949
3.

Machine learning in bioinformatics: a brief survey and recommendations for practitioners.

Bhaskar H, Hoyle DC, Singh S.

Comput Biol Med. 2006 Oct;36(10):1104-25. Epub 2005 Oct 13. Review.

PMID:
16226240
4.

Protein fold recognition using the gradient boost algorithm.

Jiao F, Xu J, Yu L, Schuurmans D.

Comput Syst Bioinformatics Conf. 2006:43-53.

5.

Resolving confusion of tongues in statistics and machine learning: a primer for biologists and bioinformaticians.

van Iterson M, van Haagen HH, Goeman JJ.

Proteomics. 2012 Feb;12(4-5):543-9. doi: 10.1002/pmic.201100395. Epub 2012 Jan 23. Review.

PMID:
22246801
6.

Machine learning in bioinformatics.

Larrañaga P, Calvo B, Santana R, Bielza C, Galdiano J, Inza I, Lozano JA, Armañanzas R, Santafé G, Pérez A, Robles V.

Brief Bioinform. 2006 Mar;7(1):86-112. Review.

PMID:
16761367
7.

Comparison of feature selection and classification for MALDI-MS data.

Liu Q, Sung AH, Qiao M, Chen Z, Yang JY, Yang MQ, Huang X, Deng Y.

BMC Genomics. 2009 Jul 7;10 Suppl 1:S3. doi: 10.1186/1471-2164-10-S1-S3.

8.

An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies.

Lancashire LJ, Lemetre C, Ball GR.

Brief Bioinform. 2009 May;10(3):315-29. doi: 10.1093/bib/bbp012. Epub 2009 Mar 23.

PMID:
19307287
9.

PatternLab for proteomics: a tool for differential shotgun proteomics.

Carvalho PC, Fischer JS, Chen EI, Yates JR 3rd, Barbosa VC.

BMC Bioinformatics. 2008 Jul 21;9:316. doi: 10.1186/1471-2105-9-316.

10.

Re-fraction: a machine learning approach for deterministic identification of protein homologues and splice variants in large-scale MS-based proteomics.

Yang P, Humphrey SJ, Fazakerley DJ, Prior MJ, Yang G, James DE, Yang JY.

J Proteome Res. 2012 May 4;11(5):3035-45. doi: 10.1021/pr300072j. Epub 2012 Mar 30.

PMID:
22428558
11.

Artificial intelligence approaches for rational drug design and discovery.

Duch W, Swaminathan K, Meller J.

Curr Pharm Des. 2007;13(14):1497-508. Review.

PMID:
17504169
12.

Machine learning: an indispensable tool in bioinformatics.

Inza I, Calvo B, Armañanzas R, Bengoetxea E, Larrañaga P, Lozano JA.

Methods Mol Biol. 2010;593:25-48. doi: 10.1007/978-1-60327-194-3_2.

PMID:
19957143
13.

Informatics for peptide retention properties in proteomic LC-MS.

Shinoda K, Sugimoto M, Tomita M, Ishihama Y.

Proteomics. 2008 Feb;8(4):787-98. doi: 10.1002/pmic.200700692. Review.

PMID:
18214845
14.

Inferring latent task structure for Multitask Learning by Multiple Kernel Learning.

Widmer C, Toussaint NC, Altun Y, Rätsch G.

BMC Bioinformatics. 2010 Oct 26;11 Suppl 8:S5. doi: 10.1186/1471-2105-11-S8-S5.

15.

A cross-validation scheme for machine learning algorithms in shotgun proteomics.

Granholm V, Noble WS, Käll L.

BMC Bioinformatics. 2012;13 Suppl 16:S3. doi: 10.1186/1471-2105-13-S16-S3. Epub 2012 Nov 5.

16.

Computational intelligence techniques in bioinformatics.

Hassanien AE, Al-Shammari ET, Ghali NI.

Comput Biol Chem. 2013 Dec;47:37-47. doi: 10.1016/j.compbiolchem.2013.04.007. Epub 2013 Jul 10. Review.

PMID:
23891719
17.

A comparison of methods for classifying clinical samples based on proteomics data: a case study for statistical and machine learning approaches.

Sampson DL, Parker TJ, Upton Z, Hurst CP.

PLoS One. 2011;6(9):e24973. doi: 10.1371/journal.pone.0024973. Epub 2011 Sep 28.

18.

Machine learning methods for predictive proteomics.

Barla A, Jurman G, Riccadonna S, Merler S, Chierici M, Furlanello C.

Brief Bioinform. 2008 Mar;9(2):119-28. doi: 10.1093/bib/bbn008. Epub 2008 Feb 29. Review.

PMID:
18310105
19.

Intelligible machine learning with malibu.

Langlois RE, Lu H.

Conf Proc IEEE Eng Med Biol Soc. 2008;2008:3795-8. doi: 10.1109/IEMBS.2008.4650035.

PMID:
19163538
20.

A primer on gene expression and microarrays for machine learning researchers.

Kuo WP, Kim EY, Trimarchi J, Jenssen TK, Vinterbo SA, Ohno-Machado L.

J Biomed Inform. 2004 Aug;37(4):293-303. Review.

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