CS646: Machine learning in bioinformatics - Projects

March 19, 2012, at 10:56 AM MST by 129.82.44.229 -

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Here are the links to the datasets you will use in your experiments:

to:

Here are the links to the datasets you will use in your feature selection experiments:

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Here are the links to the datasets you will use in your experiments:
* [[http://archive.ics.uci.edu/ml/datasets/Gisette | Gisette]]
* [[http://archive.ics.uci.edu/ml/datasets/Dexter | Dexter]]
* [[http://archive.ics.uci.edu/ml/datasets/Arcene | Arcene]]

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* Hui Zou and Trevor Hastie. [[http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2005.00503.x/full | Regularization and Variable Selection via the Elastic Net]]. JRSSB (2005) 67(2) 301-320. An R package elasticnet is available from CRAN.

to:

* Hui Zou and Trevor Hastie. [[http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2005.00503.x/full | Regularization and Variable Selection via the Elastic Net]]. JRSSB (2005) 67(2) 301-320. An R package elasticnet is available from CRAN. (Majdi)

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* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like SVMs are used in the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method. ~~(Majdi)~~

to:

* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like SVMs are used in the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method.

February 13, 2012, at 10:48 AM MST by 129.82.44.229 -

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* ~~Christoph H. Lampert.~~ [[http://~~books~~.~~nips~~.cc/papers/~~files/nips24/NIPS2011~~_~~0207~~.pdf | ~~Maximum Margin~~ Multi-Label ~~Structured Prediction]]. Neural Information Processing Systems (NIPS),~~ 2011.

to:

* Wei Bi and James Kwok. [[http://www.icml-2011.org/papers/10_icmlpaper.pdf | Multi-Label Classification on Tree- and DAG-Structured Hierarchies]]. International Conference on Machine Learning (ICML-11), 2011. (Indika)

February 10, 2012, at 11:51 AM MST by 129.82.44.229 -

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* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like SVMs are used in the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method.

to:

* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like SVMs are used in the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method. (Majdi)

February 09, 2012, at 10:19 AM MST by 129.82.44.229 -

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* Yeung K, Bumgarner R. [[http://genomebiology.com/2003/4/12/r83 | Multiclass classification of microarray data with repeated measurements: application to cancer]]. Genome Biology. 4:R83, 2003.

to:

* Yeung K, Bumgarner R. [[http://genomebiology.com/2003/4/12/r83 | Multiclass classification of microarray data with repeated measurements: application to cancer]]. Genome Biology. 4:R83, 2003. (Simon)

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* Y. Sun, S. Todorovic, and S. Goodison. [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.2272|Local Learning Based Feature Selection for High Dimensional Data Analysis]]. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 32, no. 9, pp. 1610-1626, 2010.

to:

* Y. Sun, S. Todorovic, and S. Goodison. [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.2272|Local Learning Based Feature Selection for High Dimensional Data Analysis]]. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 32, no. 9, pp. 1610-1626, 2010. (Nand)

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* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information Processing Systems (NIPS) 16, 2004. 1-norm classifiers create very sparse representations, so are useful for feature selection.

to:

* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information Processing Systems (NIPS) 16, 2004. 1-norm classifiers create very sparse representations, so are useful for feature selection. (Prathamesh)

February 08, 2012, at 12:06 PM MST by 129.82.44.229 -

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* Feiping Nie, Heng Huang, Cai Xiao, Chris Ding. [[http://books.nips.cc/papers/files/nips23/NIPS2010_1149.pdf | Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization]]. NIPS 2010.

to:

* Feiping Nie, Heng Huang, Cai Xiao, Chris Ding. [[http://books.nips.cc/papers/files/nips23/NIPS2010_1149.pdf | Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization]]. NIPS 2010. (Rehab)

February 07, 2012, at 09:50 PM MST by 76.25.21.194 -

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* Chris Ding and Hanchuan Peng. [[ http://ranger.uta.edu/~chqding/papers/mRMR_JBCB.pdf | Minimum redundancy feature selection from microarray gene expression data]]. Journal of Bioinformatics and Computational Biology, Vol. 3, No. 2, pp.185-205, 2005.

to:

* Chris Ding and Hanchuan Peng. [[ http://ranger.uta.edu/~chqding/papers/mRMR_JBCB.pdf | Minimum redundancy feature selection from microarray gene expression data]]. Journal of Bioinformatics and Computational Biology, Vol. 3, No. 2, pp.185-205, 2005. (Joel)

February 06, 2012, at 07:36 PM MST by 76.25.21.194 -

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* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method.

to:

* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like SVMs are used in the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method.

February 06, 2012, at 07:34 PM MST by 76.25.21.194 -

Changed line 23 from:

* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like the ~~RFE method~~.

to:

* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like the [[http://www.springerlink.com/content/w68424066825vr3l/|RFE]] method.

February 06, 2012, at 07:24 PM MST by 76.25.21.194 -

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* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information Processing Systems (NIPS) 16, 2004.

to:

* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information Processing Systems (NIPS) 16, 2004. 1-norm classifiers create very sparse representations, so are useful for feature selection.

February 06, 2012, at 12:02 PM MST by 129.82.44.229 -

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* Christoph H. Lampert. [[http://books.nips.cc/papers/files/nips24/NIPS2011_0207.pdf | Maximum Margin Multi-Label Structured Prediction. Neural Information Processing Systems(NIPS), 2011.

to:

* Christoph H. Lampert. [[http://books.nips.cc/papers/files/nips24/NIPS2011_0207.pdf | Maximum Margin Multi-Label Structured Prediction]]. Neural Information Processing Systems (NIPS), 2011.

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!! Prediction of protein function

* Christoph H. Lampert. [[http://books.nips.cc/papers/files/nips24/NIPS2011_0207.pdf | Maximum Margin Multi-Label Structured Prediction. Neural Information Processing Systems(NIPS), 2011.

February 06, 2012, at 12:01 PM MST by 129.82.44.229 -

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* A. ~~Rakotomamonjy~~. [[http://~~asi~~.~~insa-rouen~~.fr/~~enseignants~~/~~~arakotom~~/~~publi~~/~~rakotomamonjyROCAI2004~~.pdf | ~~Optimizing AUC with SVMs]]. Proceedings of European Conference on Artificial Intelligence Workshop~~ on ~~ROC Curve and AI, Valencia, 2004.~~ [[ http://~~asi~~.~~insa-rouen~~.fr/~~enseignants/~arakotom/toolbox/index~~.html | code]]. Can be used for feature selection like the RFE method.

to:

* T. Joachims. [[http://www.cs.cornell.edu/People/tj/publications/joachims_05a.pdf | A Support Vector Method for Multivariate Performance Measures]]. Proceedings of the International Conference on Machine Learning (ICML), 2005. [[http://svmlight.joachims.org/svm_perf.html | code]]. Can be used for feature selection like the RFE method.

February 06, 2012, at 11:39 AM MST by 129.82.44.229 -

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* A. Rakotomamonjy. [[http://asi.insa-rouen.fr/enseignants/~arakotom/publi/rakotomamonjyROCAI2004.pdf | Optimizing AUC with SVMs]]. Proceedings of European Conference on Artificial Intelligence Workshop on ROC Curve and AI, Valencia, 2004.

to:

* A. Rakotomamonjy. [[http://asi.insa-rouen.fr/enseignants/~arakotom/publi/rakotomamonjyROCAI2004.pdf | Optimizing AUC with SVMs]]. Proceedings of European Conference on Artificial Intelligence Workshop on ROC Curve and AI, Valencia, 2004. [[ http://asi.insa-rouen.fr/enseignants/~arakotom/toolbox/index.html | code]]. Can be used for feature selection like the RFE method.

February 06, 2012, at 11:37 AM MST by 129.82.44.229 -

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* A. Rakotomamonjy. [[http://asi.insa-rouen.fr/enseignants/~arakotom/publi/rakotomamonjyROCAI2004.pdf | Optimizing AUC with SVMs]]. Proceedings of European Conference on Artificial Intelligence Workshop on ROC Curve and AI, Valencia, 2004.

February 06, 2012, at 11:15 AM MST by 129.82.44.229 -

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* Y. Sun, S. Todorovic, and S. Goodison. [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.2272
| Local Learning Based Feature Selection for High Dimensional Data Analysis]]. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 32, no. 9, pp. 1610-1626, 2010.

to:

* Y. Sun, S. Todorovic, and S. Goodison. [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.2272|Local Learning Based Feature Selection for High Dimensional Data Analysis]]. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 32, no. 9, pp. 1610-1626, 2010.

February 06, 2012, at 11:14 AM MST by 129.82.44.229 -

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* Y. Sun, S. Todorovic, and S. Goodison. [[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.2272
| Local Learning Based Feature Selection for High Dimensional Data Analysis]]. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 32, no. 9, pp. 1610-1626, 2010.

February 06, 2012, at 11:12 AM MST by 129.82.44.229 -

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* Yeung K, Bumgarner R. [[http://genomebiology.com/2003/4/12/r83
| Multiclass classification of microarray data
~~with~~ repeated measurements: application to cancer]]. Genome
~~Biol~~. 4:R83, 2003.

to:

* Yeung K, Bumgarner R. [[http://genomebiology.com/2003/4/12/r83 | Multiclass classification of microarray data with repeated measurements: application to cancer]]. Genome Biology. 4:R83, 2003.

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Added lines 11-14:

* Yeung K, Bumgarner R. [[http://genomebiology.com/2003/4/12/r83
| Multiclass classification of microarray data
with repeated measurements: application to cancer]]. Genome
Biol. 4:R83, 2003.

February 06, 2012, at 11:04 AM MST by 129.82.44.229 -

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* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information
Processing Systems (NIPS) 16, 2004.

to:

* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information Processing Systems (NIPS) 16, 2004.

February 06, 2012, at 11:04 AM MST by 129.82.44.229 -

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* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm
support vector machines]]. In: Neural Information

to:

* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm support vector machines]]. In: Neural Information

February 06, 2012, at 11:03 AM MST by 129.82.44.229 -

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* Hui Zou and Trevor Hastie. [[http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2005.00503.x/full | Regularization and Variable Selection via
the Elastic Net]]. JRSSB (2005) 67(2) 301-320. An R package elasticnet is available from CRAN.

to:

* Hui Zou and Trevor Hastie. [[http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2005.00503.x/full | Regularization and Variable Selection via the Elastic Net]]. JRSSB (2005) 67(2) 301-320. An R package elasticnet is available from CRAN.

February 06, 2012, at 11:01 AM MST by 129.82.44.229 -

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* Hui Zou and Trevor Hastie. [[http://~~www~~.~~stanford~~.~~edu~~/~~~hastie~~/~~Papers/B67~~.~~2%20(~~2005~~)%20301-320%20Zou%20&%20Hastie~~.~~pdf~~ | Regularization and Variable Selection via

to:

* Hui Zou and Trevor Hastie. [[http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2005.00503.x/full | Regularization and Variable Selection via

Changed line 21 from:

* Feiping Nie, Heng Huang, Cai Xiao, Chris Ding. [[http://books.nips.cc/papers/files/nips23/NIPS2010_1149.pdf | Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization]]. NIPS 2010.

to:

* Feiping Nie, Heng Huang, Cai Xiao, Chris Ding. [[http://books.nips.cc/papers/files/nips23/NIPS2010_1149.pdf | Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization]]. NIPS 2010.

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* Chris Ding and Hanchuan Peng. [[ http://ranger.uta.edu/~chqding/papers/mRMR_JBCB.pdf | Minimum redundancy feature selection from microarray gene expression data]].
Journal of Bioinformatics and Computational Biology, Vol. 3, No. 2, pp.185-205, 2005.

to:

* Chris Ding and Hanchuan Peng. [[ http://ranger.uta.edu/~chqding/papers/mRMR_JBCB.pdf | Minimum redundancy feature selection from microarray gene expression data]]. Journal of Bioinformatics and Computational Biology, Vol. 3, No. 2, pp.185-205, 2005.

February 06, 2012, at 10:56 AM MST by 129.82.44.229 -

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~~Coming soon~~!

to:

There are two topics available for projects: feature selection and prediction of protein function. Your first step is to choose a paper whose method you will use/implement.

!!Feature selection

!!!Filter methods:

* Chris Ding and Hanchuan Peng. [[ http://ranger.uta.edu/~chqding/papers/mRMR_JBCB.pdf | Minimum redundancy feature selection from microarray gene expression data]].
Journal of Bioinformatics and Computational Biology, Vol. 3, No. 2, pp.185-205, 2005.

!!!Embedded feature selection methods:

* Hui Zou and Trevor Hastie. [[http://www.stanford.edu/~hastie/Papers/B67.2%20(2005)%20301-320%20Zou%20&%20Hastie.pdf | Regularization and Variable Selection via
the Elastic Net]]. JRSSB (2005) 67(2) 301-320. An R package elasticnet is available from CRAN.

* Ji Zhu, Saharon Rosset, Trevor Hastie and Rob Tibshirani. [[http://www.stat.lsa.umich.edu/~jizhu/pubs/Zhu-NIPS04.pdf | 1-norm
support vector machines]]. In: Neural Information
Processing Systems (NIPS) 16, 2004.

* Feiping Nie, Heng Huang, Cai Xiao, Chris Ding. [[http://books.nips.cc/papers/files/nips23/NIPS2010_1149.pdf | Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization]]. NIPS 2010.

December 27, 2010, at 12:47 PM MST by 67.190.27.250 -

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!Course projects

Coming soon!

Main.Projects History