biosvm references

[Mukherjee1998Support] S. Mukherjee, P. Tamayo, J. P. Mesirov, D. Slonim, A. Verri, and T. Poggio. Support vector machine classification of microarray data. Technical Report 182, C.B.L.C., 1998. A.I. Memo 1677. [ bib | .html | .pdf ]
[Jaakkola1999Exploiting] T. S. Jaakkola and D. Haussler. Exploiting generative models in discriminative classifiers. In Proc. of Tenth Conference on Advances in Neural Information Processing Systems, 1999. [ bib | .ps | .pdf ]
[Jaakkola1999Using] T. S. Jaakkola, M. Diekhans, and D. Haussler. Using the Fisher Kernel Method to Detect Remote Protein Homologies. In Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology, pages 149-158. AAAI Press, 1999. [ bib ]
[Haussler1999Convolution] D. Haussler. Convolution Kernels on Discrete Structures. Technical Report UCSC-CRL-99-10, UC Santa Cruz, 1999. [ bib | .pdf | Abstract ]
[Zien2000Engineering] A. Zien, G. Rätsch, S. Mika, B. Schölkopf, T. Lengauer, and K.-R. Müller. Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics, 16(9):799-807, 2000. [ bib | http | .pdf | Abstract ]
[Watkins2000Dynamic] C. Watkins. Dynamic alignment kernels. In A.J. Smola, P.L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 39-50. MIT Press, Cambridge, MA, 2000. [ bib | .ps.gz | .pdf ]
[Moler2000Analysis] E. J. Moler, M. L. Chow, and I. S. Mian. Analysis of molecular profile data using generative and discriminative methods. Physiol. Genomics, 4(2):109-126, Dec 2000. [ bib | http | .pdf | Abstract ]
[Lodhi2000Text] H. Lodhi, J. Shawe-Taylor, N. Cristianini, and C. J. C. H. Watkins. Text Classification using String Kernels. In Adv. Neural Inform. Process. Syst., pages 563-569, 2000. [ bib | .ps.gz | .pdf ]
[Jaakkola2000Discriminative] T. Jaakkola, M. Diekhans, and D. Haussler. A Discriminative Framework for Detecting Remote Protein Homologies. J. Comput. Biol., 7(1,2):95-114, 2000. [ bib | .ps | .pdf ]
[Furey2000Support] T. S. Furey, N. Cristianini, N. Duffy, D. W. Bednarski, M. Schummer, and D. Haussler. Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics, 16(10):906-914, Oct 2000. [ bib | http | .pdf | Abstract ]
[Cai2000Support] Y.D. Cai, X.J. Liu, X.B. Xu, and K.C. Chou. Support vector machines for prediction of protein subcellular location. Mol. Cell Biol. Res. Commun., 4(4):230-234, 2000. [ bib | DOI | http | www: | Abstract ]
[Brown2000Knowledge-based] M. P. Brown, W. N. Grundy, D. Lin, N. Cristianini, C. W. Sugnet, T. S. Furey, M. Ares, and D. Haussler. Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl. Acad. Sci. USA, 97(1):262-7, Jan 2000. [ bib | http | .pdf | Abstract ]
[Ben-Dor2000Tissue] A. Ben-Dor, L. Bruhn, N. Friedman, I. Nachman, M. Schummer, and Z. Yakhini. Tissue classification with gene expression profiles. J. Comput. Biol., 7(3-4):559-583, 2000. [ bib | http | .pdf | Abstract ]
[Yeang2001Molecular] C.H. Yeang, S. Ramaswamy, P. Tamayo, S. Mukherjee, R.M. Rifkin, M. Angelo, M. Reich, E. Lander, J. Mesirov, and T. Golub. Molecular classification of multiple tumor types. Bioinformatics, 17(Suppl. 1):S316-S322, 2001. [ bib | http | .pdf | Abstract ]
[Xiong2001Biomarker] M. Xiong, X. Fang, and J. Zhao. Biomarker Identification by Feature Wrappers. Genome Res., 11(11):1878-1887, 2001. [ bib | http | .pdf | Abstract ]
[Su2001Molecular] A. I. Su, J. B. Welsh, L. M. Sapinoso, S. G. Kern, P. Dimitrov, H. Lapp, P. G. Schultz, S. M. Powell, C. A. Moskaluk, H. F.Jr. Frierson, and G. M. Hampton. Molecular Classification of Human Carcinomas by Use of Gene Expression Signatures. Cancer Res., 61(20):7388-7393, 2001. [ bib | http | .html | Abstract ]
[Ramaswamy2001Multiclass] S. Ramaswamy, P. Tamayo, R. Rifkin, S. Mukherjee, C.H. Yeang, M. Angelo, C. Ladd, M. Reich, E. Latulippe, J.P. Mesirov, T. Poggio, W. Gerald, M. Loda, E.S. Lander, and T.R. Golub. Multiclass cancer diagnosis using tumor gene expression signatures. Proc. Natl. Acad. Sci. USA, 98(26):15149-15154, Dec 2001. [ bib | DOI | http | .pdf | Abstract ]
[Pavlidis2001Gene] P. Pavlidis, J. Weston, J. Cai, and W.N. Grundy. Gene functional classification from heterogeneous data. In Proceedings of the Fifth Annual International Conference on Computational Biology, pages 249-255, 2001. [ bib | .pdf | .pdf ]
[Pavlidis2001Promoter] P. Pavlidis, T. S. Furey, M. Liberto, D. Haussler, and W. N. Grundy. Promoter Region-Based Classification of Genes. In Pacific Symposium on Biocomputing, pages 139-150, 2001. [ bib | .pdf | .pdf ]
[Model2001Feature] F. Model, P. Adorjan, A. Olek, and C. Piepenbrock. Feature selection for DNA methylation based cancer classification. Bioinformatics, 17(Supp. 1):S157-S164, 2001. [ bib | http | .pdf | Abstract ]
[Hua2001Support] S. Hua and Z. Sun. Support vector machine approach for protein subcellular localization prediction. Bioinformatics, 17(8):721-728, 2001. [ bib | http | .pdf | Abstract ]
[Ding2001Multi-class] C.H.Q. Ding and I. Dubchak. Multi-class protein fold recognition using support vector machines and neural networks. Bioinformatics, 17:349-358, 2001. [ bib | .pdf | .pdf | Abstract ]
[Chow2001Identifying] M. L. Chow, E. J. Moler, and I. S. Mian. Identifying marker genes in transcription profiling data using a mixture of feature relevance experts. Physiol. Genomics, 5(2):99-111, Mar 2001. [ bib | http | .pdf | Abstract ]
[Carter2001computational] R. J. Carter, I. Dubchak, and S. R. Holbrook. A computational approach to identify genes for functional RNAs in genomic sequences. Nucl. Acids Res., 29(19):3928-3938, 2001. [ bib | http | .pdf | Abstract ]
[Cai2001Support] Y.-D. Cai, X.-J. Liu, X.-B. Xu, and G.-P. Zhou. Support Vector Machines for predicting protein structural class. BMC Bioinformatics, 2(3):3, 2001. [ bib | DOI | http | .pdf | Abstract ]
[Bock2001Predicting] J. R. Bock and D. A. Gough. Predicting protein-protein interactions from primary structure. Bioinformatics, 17(5):455-460, 2001. [ bib | .pdf | .pdf ]
[Beerenwinkel2001Geno2pheno] N. Beerenwinkel, B. Schmidt, H. Walter, R. Kaiser, T. Lengauer, D. Hoffman, K. Korn, and J. Selbig. Geno2pheno: Interpreting Genotypic HIV Drug Resistance Tests. IEEE Intelligent Systems, 6(6):35-41, 2001. [ bib | DOI | http | .pdf | Abstract ]
[Bazzani2001SVM] A. Bazzani, A. Bevilacqua, D. Bollini, R. Brancaccio, R. Campanini, N. Lanconelli, A. Riccardi, and D. Romani. An SVM classifier to separate false signals from microcalcifications in digital mammograms. Phys Med Biol, 46(6):1651-63, Jun 2001. [ bib | DOI | http | .pdf | Abstract ]
[Hua2001Novel] S. Hua and Z. Sun. A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach. J. Mol. Biol., 308(2):397-407, April 2001. [ bib | DOI | .pdf ]
[Logan2001Study] B. Logan, P. Moreno, B. Suzek, Z. Weng, and S. Kasif. A Study of Remote Homology Detection. Technical Report CRL 2001/05, Compaq Cambridge Research laboratory, June 2001. [ bib | .pdf | Abstract ]
[Burbidge2001Drug] R. Burbidge, M. Trotter, B. Buxton, and S. Holden. Drug design by machine learning: support vector machines for pharmaceutical data analysis. Comput. Chem., 26(1):4-15, December 2001. [ bib | .pdf | .pdf ]
[Zavaljevski2002Support] N. Zavaljevski, F.J. Stevens, and J. Reifman. Support vector machines with selective kernel scaling for protein classification and identification of key amino acid positions. Bioinformatics, 18(5):689-696, 2002. [ bib | http | .pdf | Abstract ]
[Yuan2002Prediction] Z. Yuan, K. Burrage, and J.S. Mattick. Prediction of protein solvent accessibility using support vector machines. Proteins, 48(3):566-570, 2002. [ bib | DOI | http | .pdf | Abstract ]
[Warmuth2002Active] M. K. Warmuth, G. Rätsch, M. Mathieson, L. Liao, and C. Lemmen. Active learning in the drug discovery process. In T.G. Dietterich, S. Becker, and Z. Ghahramani, editors, Adv. Neural Inform. Process. Syst., volume 14, pages 1449-1456. MIT Press, 2002. [ bib ]
[Vert2002Graph-driven] J.-P. Vert and M. Kanehisa. Graph-driven features extraction from microarray data. Technical Report 0206055, Arxiv physics, 2002. [ bib ]
[Vert2002tree] J.-P. Vert. A tree kernel to analyze phylogenetic profiles. Bioinformatics, 18:S276-S284, 2002. [ bib | .html | .pdf ]
[Vert2002Support] J.-P. Vert. Support vector machine prediction of signal peptide cleavage site using a new class of kernels for strings. In R. B. Altman, A. K. Dunker, L. Hunter, K. Lauerdale, and T. E. Klein, editors, Proceedings of the Pacific Symposium on Biocomputing 2002, pages 649-660. World Scientific, 2002. [ bib | .pdf | .pdf ]
[Valentini2002Gene] G. Valentini. Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles. Artif. Intell. Med., 26(3):281-304, Nov 2002. [ bib | DOI | .pdf | Abstract ]
[Tsuda2002Marginalized] K. Tsuda, T. Kin, and K. Asai. Marginalized Kernels for Biological Sequences. Bioinformatics, 18:S268-S275, 2002. [ bib | .pdf | Abstract ]
[Tsuda2002new] K. Tsuda, M. Kawanabe, G. Rätsch, S. Sonnenburg, and K.-R. Müller. A new discriminative kernel from probabilistic models. Neural Computation, 14(10):2397-2414, 2002. [ bib | DOI | http | .pdf ]
[Stapley2002Predicting] B.J. Stapley, L.A. Kelley, and M.J. Sternberg. Predicting the sub-cellular location of proteins from text using support vector machines. In Russ B. Altman, A. Keith Dunker, Lawrence Hunter, Kevin Lauerdale, and Teri E. Klein, editors, Proceedings of the Pacific Symposium on Biocomputing 2002, pages 374-385. World Scientific, 2002. [ bib | .pdf | .pdf | Abstract ]
[Sonnenburg2002New] S. Sonnenburg, G. Rätsch, A. Jagota, and K.-R. Müller. New methods for splice-site recognition. In JR. Dorronsoro, editor, Proc. International conference on artificial Neural Networks ? ICANN?02, number 2415 in LNCS, pages 329-336. Springer Berlin, 2002. [ bib | .pdf ]
[Shipp2002Diffuse] M. A. Shipp, K. N. Ross, P. Tamayo, A. P. Weng, J. L. Kutok, R. C. T. Aguiar, M. Gaasenbeek, M. Angelo, M. Reich, G. A. Pinkus, T. S. Ray, M. A. Koval, K. W. Last, A. Norton, T. A. Lister, J. Mesirov, D. S. Neuberg, E. S. Lander, J. C. Aster, and T. R. Golub. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat. Med., 8(1):68-74, 2002. [ bib | DOI | .pdf | Abstract ]
[Seeger2002Covariance] M. Seeger. Covariance Kernels from Bayesian Generative Models. In Adv. Neural Inform. Process. Syst., volume 14, pages 905-912, 2002. [ bib | www: ]
[Pavlidis2002Learning] P. Pavlidis, J. Weston, J. Cai, and W.S. Noble. Learning gene functional classifications from multiple data types. J. Comput. Biol., 9(2):401-411, 2002. [ bib | DOI | .pdf | Abstract ]
[Patterson2002Pre-mRNA] D.J. Patterson, K. Yasuhara, and W.L. Ruzzo. Pre-mRNA secondary structure prediction aids splice site prediction. In Russ B. Altman, A. Keith Dunker, Lawrence Hunter, Kevin Lauerdale, and Teri E. Klein, editors, Proceedings of the Pacific Symposium on Biocomputing 2002, pages 223-234. World Scientific, 2002. [ bib | .pdf | .pdf | Abstract ]
[Myasnikova2002Support] E. Myasnikova, A. Samsonova, M. Samsonova, and J. Reinitz. Support vector regression applied to the determination of the developmental age of a Drosophila embryo from its segmentation gene expression patterns. Bioinformatics, 18(Suppl. 1):S87-S95, 2002. [ bib | http | .pdf | Abstract ]
[Lodhi2002Text] H. Lodhi, C. Saunders, J. Shawe-Taylor, N. Cristianini, and C.je n'ai pas vraiment d'éléments de réponse. Watkins. Text classification using string kernels. J. Mach. Learn. Res., 2:419-444, 2002. [ bib | .html | .pdf ]
[Lin2002Conserved] K. Lin, Y. Kuang, J. S. Joseph, and P. R. Kolatkar. Conserved codon composition of ribosomal protein coding genes in Escherichia coli, Mycobacterium tuberculosis and Saccharomyces cerevisiae: lessons from supervised machine learning in functional genomics. Nucl. Acids Res., 30(11):2599-2607, 2002. [ bib | http | .pdf | Abstract ]
[Liao2002Combining] L. Liao and W. S. Noble. Combining pairwise sequence similarity and support vector machines for remote protein homology detection. In Proceedings of the Sixth International Conference on Computational Molecular Biology, 2002. [ bib | .html | .pdf ]
[Leslie2002spectrum] C. Leslie, E. Eskin, and W.S. Noble. The spectrum kernel: a string kernel for SVM protein classification. In Russ B. Altman, A. Keith Dunker, Lawrence Hunter, Kevin Lauerdale, and Teri E. Klein, editors, Proceedings of the Pacific Symposium on Biocomputing 2002, pages 564-575, Singapore, 2002. World Scientific. [ bib | .pdf ]
[Kramer2002Fragment] S. Kramer, E. Frank, and C. Helma. Fragment generation and support vector machines for inducing SARs. SAR QSAR Environ Res, 13(5):509-23, Jul 2002. [ bib | DOI | http | Abstract ]
[Kondor2002Diffusion] R. I. Kondor and J. Lafferty. Diffusion kernels on graphs and other discrete input. In Proceedings of the Nineteenth International Conference on Machine Learning, pages 315-322, San Francisco, CA, USA, 2002. Morgan Kaufmann Publishers Inc. [ bib | .pdf ]
[Kin2002Marginalized] T. Kin, K. Tsuda, and K. Asai. Marginalized kernels for RNA sequence data analysis. In R.H. Lathtop, K. Nakai, S. Miyano, T. Takagi, and M. Kanehisa, editors, Genome Informatics 2002, pages 112-122. Universal Academic Press, 2002. [ bib | .html | .pdf | Abstract ]
[Karchin2002Classifying] R. Karchin, K. Karplus, and D. Haussler. Classifying G-protein coupled receptors with support vector machines. Bioinformatics, 18:147-159, 2002. [ bib | http | .pdf | Abstract ]
[Guyon2002Gene] I. Guyon, J. Weston, S. Barnhill, and V. Vapnik. Gene selection for cancer classification using support vector machines. Mach. Learn., 46(1/3):389-422, Jan 2002. [ bib | .pdf | .pdf | Abstract ]
[Guermeur2002Combining] Y. Guermeur. Combining Discriminant Models with New Multi-Class SVMs. Pattern Anal. Appl., 5(2):168-179, 2002. [ bib | DOI | http | .pdf | Abstract ]
[Fritz2002Microarray-based] B. Fritz, F. Schubert, G. Wrobel, C. Schwaenen, S. Wessendorf, M. Nessling, C. Korz, R. J. Rieker, K. Montgomery, R. Kucherlapati, G. Mechtersheimer, R. Eils, S. Joos, and P. Lichter. Microarray-based Copy Number and Expression Profiling in Dedifferentiated and Pleomorphic Liposarcoma. Cancer Res., 62(11):2993-2998, 2002. [ bib | http | .pdf | Abstract ]
[Donnes2002Prediction] P. Dönnes and A. Elofsson. Prediction of MHC class I binding peptides, using SVMHC. BMC Bioinformatics, 3(1):25, Sep 2002. [ bib | DOI | http | .pdf | Abstract ]
[Doniger2002Predicting] S. Doniger, T. Hofmann, and J. Yeh. Predicting CNS permeability of drug molecules: comparison of neural network and support vector machine algorithms. J. Comput. Biol., 9(6):849-864, 2002. [ bib | DOI | .pdf | Abstract ]
[Deshpande2002Evaluation] M. Deshpande and G. Karypis. Evaluation of Techniques for Classifying Biological Sequences. In PAKDD '02: Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, pages 417-431. Springer Verlag, 2002. [ bib | .pdf | Abstract ]
[Degroeve2002Feature] S. Degroeve, B. De Baets, Y. Van de Peer, and P. Rouze. Feature subset selection for splice site prediction. Bioinformatics, 18(Suppl. 1):S75-S83, 2002. [ bib | http | .pdf | Abstract ]
[Chou2002Using] K.-C. Chou and Y.-D. Cai. Using Functional Domain Composition and Support Vector Machines for Prediction of Protein Subcellular Location. J. Biol. Chem., 277(48):45765-45769, 2002. [ bib | http | .pdf | Abstract ]
[Cai2002Prediction] Y.-D. Cai, X.-J. Liu, X.-B. Xu, and G.-P. Zhou. Prediction of protein structural classes by support vector machines. Comput. Chem., 26(3):293-296, 2002. [ bib | DOI | http | .pdf | Abstract ]
[Cai2002Support] Y.-D. Cai, X.-J. Liu, X.-B. Xu, and K.-C. Chou. Support vector machines for prediction of protein subcellular location by incorporating quasi-sequence-order effect. J. Cell. Biochem., 84(2):343-348, 2002. [ bib | DOI | http | .pdf | Abstract ]
[Cai2002Supportc] Y.D. Cai, X.J. Liu, X.B. Xu, and K.C. Chou. Support vector machines for the classification and prediction of beta-turn types. J. Pept. Sci., 8(7):297-301, 2002. [ bib | DOI | http | www: | Abstract ]
[Cai2002Supportb] Y.D. Cai, X.J. Liu, X.B. Xu, and K.C. Chou. Support vector machines for predicting the specificity of GalNAc-transferase. Peptides, 23:205-208, 2002. [ bib | DOI | http | .pdf | Abstract ]
[Cai2002Supporta] Y.D. Cai, X.J. Liu, X.B. Xu, and K.C. Chou. Support Vector Machines for predicting HIV protease cleavage sites in protein. J. Comput. Chem., 23(2):267-274, 2002. [ bib | DOI | http | www: | Abstract ]
[Bock2002New] J. R. Bock and D. A. Gough. A New Method to Estimate Ligand-Receptor Energetics. Mol Cell Proteomics, 1(11):904-910, 2002. [ bib | http | .pdf | Abstract ]
[Bao2002Identifying] L. Bao and Z. Sun. Identifying genes related to drug anticancer mechanisms using support vector machine. FEBS Lett., 521:109-114, 2002. [ bib | .html | .pdf | Abstract ]
[Ambroise2002Selection] C. Ambroise and G.J. McLachlan. Selection bias in gene extraction on the basis of microarray gene-expression data. Proc. Natl. Acad. Sci. USA, 99(10):6562-6566, 2002. [ bib | http | .pdf | Abstract ]
[Aliferis2002Machine] C.F. Aliferis, D.P. Hardin, and P. Massion. Machine Learning Models For Lung Cancer Classification Using Array Comparative Genomic Hybridization. In Proceedings of the 2002 American Medical Informatics Association (AMIA) Annual Symposium, pages 7-11, 2002. [ bib | .pdf | Abstract ]
[Zhao2003Application] Y. Zhao, C. Pinilla, D. Valmori, R. Martin, and R. Simon. Application of support vector machines for T-cell epitopes prediction. Bioinformatics, 19(15):1978-1984, 2003. [ bib | http | .pdf | Abstract ]
[Zhang2003Sequence] X. H-F. Zhang, K. A. Heller, I. Hefter, C. S. Leslie, and L. A. Chasin. Sequence Information for the Splicing of Human Pre-mRNA Identified by Support Vector Machine Classification. Genome Res., 13(12):2637-2650, 2003. [ bib | DOI | http | .pdf | Abstract ]
[Zhang2003Classification] S.-W. Zhang, Q. Pan, H.-C. Zhang, Y-L. Zhang, and H.-Y. Wang. Classification of protein quaternary structure with support vector machine. Bioinformatics, 19(18):2390-2396, 2003. [ bib | http | .pdf | Abstract ]
[Zernov2003Drug] V. V. Zernov, K. V. Balakin, A. A. Ivaschenko, N. P. Savchuk, and I. V. Pletnev. Drug discovery using support vector machines. The case studies of drug-likeness, agrochemical-likeness, and enzyme inhibition predictions. J Chem Inf Comput Sci, 43(6):2048-56, 2003. [ bib | DOI | http | .pdf | Abstract ]
[Yu2003Fine-grained] C.S. Yu, J.Y. Wang, J.M. Yang, P.C. Lyu, C.J. Lin, and J.K. Hwang. Fine-grained protein fold assignment by support vector machines using generalized npeptide coding schemes and jury voting from multiple-parameter sets. Proteins, 50(4):531, 6 2003. [ bib | DOI | http | .pdf | Abstract ]
[Yoon2003Analysis] Y. Yoon, J. Song, S.H. Hong, and J.Q. Kim. Analysis of multiple single nucleotide polymorphisms of candidate genes related to coronary heart disease susceptibility by using support vector machines. Clin. Chem. Lab. Med., 41(4):529-534, 2003. [ bib | .html | .pdf | Abstract ]
[Yamanishi2003Extraction] Y. Yamanishi, J.-P. Vert, A. Nakaya, and M. Kanehisa. Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis. Bioinformatics, 19(Suppl. 1):i323-i330, 2003. [ bib | http | .pdf | Abstract ]
[Wu2003Comparison] B. Wu, T. Abbott, D. Fishman, W. McMurray, G. Mor, K. Stone, D. Ward, K. Williams, and H. Zhao. Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data. Bioinformatics, 19(13):1636-1643, 2003. [ bib | http | .pdf | Abstract ]
[Winters-Hilt2003Highly] S. Winters-Hilt, W. Vercoutere, V.S. DeGuzman, D. Deamer, M. Akeson, and D. Haussler. Highly accurate classification of Watson-Crick basepairs on termini of single DNA molecules. Biophys. J., 84(2):967-976, 2003. [ bib | http | .pdf | Abstract ]
[Wilton2003Comparison] D. Wilton, P. Willett, K. Lawson, and G. Mullier. Comparison of ranking methods for virtual screening in lead-discovery programs. J Chem Inf Comput Sci, 43(2):469-74, 2003. [ bib | DOI | http | .pdf | Abstract ]
[Weston2003Feature] J. Weston, F. Pérez-Cruz, O. Bousquet, O. Chapelle, A. Elisseeff, and B. Schölkopf. Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics, 19(6):764-771, 2003. [ bib | http | .pdf | Abstract ]
[Warmuth2003Active] M. K. Warmuth, J. Liao, G. Rätsch, M. Mathieson, S. Putta, and C. Lemmen. Active learning with support vector machines in the drug discovery process. J Chem Inf Comput Sci, 43(2):667-673, 2003. [ bib | DOI | http | .pdf | Abstract ]
[Ward2003Secondary] J. J. Ward, L. J. McGuffin, B. F. Buxton, and D. T. Jones. Secondary structure prediction with support vector machines. Bioinformatics, 19(13):1650-1655, 2003. [ bib | http | .pdf | Abstract ]
[Wagner2003Protocols] M. Wagner, D. Naik, and A. Pothen. Protocols for disease classification from mass spectrometry data. Proteomics, 3(9):1692-1698, 2003. [ bib | DOI | http | .pdf | Abstract ]
[Vert2003Extracting] J.-P. Vert and M. Kanehisa. Extracting active pathways from gene expression data. Bioinformatics, 19:238ii-234ii, 2003. [ bib | http | .pdf | Abstract ]
[Vert2003Graph-driven] J.-P. Vert and M. Kanehisa. Graph-driven features extraction from microarray data using diffusion kernels and kernel CCA. In S. Becker, S. Thrun, and K. Obermayer, editors, Adv. Neural Inform. Process. Syst., pages 1449-1456. MIT Press, 2003. [ bib | .pdf ]
[Tsuda2003em] K. Tsuda, S. Akaho, and K. Asai. The em Algorithm for Kernel Matrix Completion with Auxiliary Data. J. Mach. Learn. Res., 4:67-81, 2003. [ bib | .html | .pdf | Abstract ]
[Takaoka2003Development] Y. Takaoka, Y. Endo, S. Yamanobe, H. Kakinuma, T. Okubo, Y. Shimazaki, T. Ota, S. Sumiya, and K. Yoshikawa. Development of a method for evaluating drug-likeness and ease of synthesis using a data set in which compounds are assigned scores based on chemists' intuition. J Chem Inf Comput Sci, 43(4):1269-75, 2003. [ bib | DOI | http | .pdf | Abstract ]
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[Su2003RankGene] Yang Su, T.M. Murali, Vladimir Pavlovic, Michael Schaffer, and Simon Kasif. RankGene: identification of diagnostic genes based on expression data. Bioinformatics, 19(12):1578-1579, 2003. [ bib | http | .pdf | Abstract ]
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