TY - JOUR AU - Cruz, J. A. AU - Wishart, D. S. PY - 2006 DA - 2006// TI - Applications of Machine Learning in Cancer Prediction and Prognosis JO - Cancer Inform VL - 2 ID - Cruz2006 ER - TY - JOUR AU - Chen, X. AU - Liu, M. PY - 2005 DA - 2005// TI - Prediction of protein – protein interactions using random decision forest framework JO - Bioinformatics VL - 21 UR - https://doi.org/10.1093/bioinformatics/bti721 DO - 10.1093/bioinformatics/bti721 ID - Chen2005 ER - TY - JOUR AU - Nielsen, H. AU - Brunak, S. AU - Heijne, G. PY - 1999 DA - 1999// TI - Machine learning approaches for the prediction of signal peptides and other protein sorting signals JO - Protein Eng Des Sel VL - 12 UR - https://doi.org/10.1093/protein/12.1.3 DO - 10.1093/protein/12.1.3 ID - Nielsen1999 ER - TY - JOUR AU - Burbidge, R. AU - Trotter, M. AU - Buxton, B. AU - Holden, S. PY - 2001 DA - 2001// TI - Drug design by machine learning: support vector machines for pharmaceutical data analysis JO - Comput Chem VL - 26 UR - https://doi.org/10.1016/S0097-8485(01)00094-8 DO - 10.1016/S0097-8485(01)00094-8 ID - Burbidge2001 ER - TY - JOUR AU - Murphy, R. F. PY - 2014 DA - 2014// TI - An active role for machine learning in drug development JO - Nat Chem Biol VL - 7 UR - https://doi.org/10.1038/nchembio.576 DO - 10.1038/nchembio.576 ID - Murphy2014 ER - TY - JOUR AU - Chong, L. C. AU - Albuquerque, M. A. AU - Harding, N. J. AU - Caloian, C. AU - Chan-seng-yue, M. AU - Borja, R. AU - Fraser, M. AU - Denroche, R. E. AU - Beck, T. A. AU - Der, K. T. AU - Bristow, R. G. AU - Mcpherson, J. D. AU - Boutros, P. C. PY - 2014 DA - 2014// TI - SeqControl: process control for DNA sequencing JO - Nat Methods VL - 11 UR - https://doi.org/10.1038/nmeth.3094 DO - 10.1038/nmeth.3094 ID - Chong2014 ER - TY - JOUR AU - Ben-Hur, A. AU - Ong, C. S. AU - Sonnenburg, S. AU - Schölkopf, B. AU - Rätsch, G. PY - 2008 DA - 2008// TI - Support vector machines and kernels for computational biology JO - PLoS Comput Biol VL - 4 UR - https://doi.org/10.1371/journal.pcbi.1000173 DO - 10.1371/journal.pcbi.1000173 ID - Ben-Hur2008 ER - TY - CHAP AU - Lafferty, J. AU - McCallum, A. AU - Pereira, F. C. N. PY - 2001 DA - 2001// TI - Conditional Random Fields : Probabilistic Models for Segmenting and Labeling Sequence Data BT - Proc 18th Int Conf Mach Learn ID - Lafferty2001 ER - TY - JOUR AU - Statnikov, A. AU - Wang, L. AU - Aliferis, C. F. PY - 2008 DA - 2008// TI - A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification JO - BMC Bioinforma VL - 9 UR - https://doi.org/10.1186/1471-2105-9-319 DO - 10.1186/1471-2105-9-319 ID - Statnikov2008 ER - TY - JOUR AU - Guyon, I. AU - Weston, J. AU - Barnhill, S. PY - 2002 DA - 2002// TI - Gene Selection for Cancer Classification using Support Vector Machines JO - Mach Learn VL - 46 UR - https://doi.org/10.1023/A:1012487302797 DO - 10.1023/A:1012487302797 ID - Guyon2002 ER - TY - JOUR AU - Hilario, M. AU - Kalousis, A. AU - Müller, M. AU - Pellegrini, C. PY - 2003 DA - 2003// TI - Machine learning approaches to lung cancer prediction from mass spectra JO - Proteomics VL - 3 UR - https://doi.org/10.1002/pmic.200300523 DO - 10.1002/pmic.200300523 ID - Hilario2003 ER - TY - JOUR AU - Tan, A. C. AU - Gilbert, D. PY - 2003 DA - 2003// TI - Ensemble machine learning on gene expression data for cancer classification JO - Appl Bioinforma VL - 2 ID - Tan2003 ER - TY - JOUR AU - Shedden, K. AU - Taylor, J. M. G. AU - Enkemann, S. A. AU - Tsao, M. S. AU - Yeatman, T. J. AU - Gerald, W. L. AU - Eschrich, S. AU - Jurisica, I. AU - Giordano, T. J. AU - Misek, D. E. AU - Chang, A. C. AU - Zhu, C. Q. AU - Strumpf, D. AU - Hanash, S. AU - Shepherd, F. A. AU - Ding, K. AU - Seymour, L. AU - Naoki, K. AU - Pennell, N. AU - Weir, B. AU - Verhaak, R. AU - Ladd-Acosta, C. AU - Golub, T. AU - Gruidl, M. AU - Sharma, A. AU - Szoke, J. AU - Zakowski, M. AU - Rusch, V. AU - Kris, M. AU - Viale, A. PY - 2008 DA - 2008// TI - Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study JO - Nat Med VL - 14 UR - https://doi.org/10.1038/nm.1790 DO - 10.1038/nm.1790 ID - Shedden2008 ER - TY - JOUR AU - Ayers, M. AU - Symmans, W. F. AU - Stec, J. AU - Damokosh, A. I. AU - Clark, E. AU - Hess, K. AU - Lecocke, M. AU - Metivier, J. AU - Booser, D. AU - Ibrahim, N. AU - Valero, V. AU - Royce, M. AU - Arun, B. AU - Whitman, G. AU - Ross, J. AU - Sneige, N. AU - Hortobagyi, G. N. AU - Pusztai, L. PY - 2004 DA - 2004// TI - Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer JO - J Clin Oncol VL - 22 UR - https://doi.org/10.1200/JCO.2004.05.166 DO - 10.1200/JCO.2004.05.166 ID - Ayers2004 ER - TY - JOUR AU - Shipp, M. AU - Ross, K. N. AU - Tamayo, P. AU - Weng, A. P. AU - Kutok, J. L. AU - Aguiar, R. C. T. AU - Gaasenbeek, M. AU - Angelo, M. AU - Reich, M. AU - Pinkus, G. S. AU - Ray, T. S. AU - Koval, M. A. AU - Last, K. W. AU - Norton, A. AU - Lister, A. AU - Mesirov, J. AU - Neuberg, D. AU - Lander, E. S. AU - Aster, J. C. AU - Golub, T. R. PY - 2002 DA - 2002// TI - Diffuse large B-cell lymphoma outcome prediction by gene- expression profiling and supervised machine learning JO - Nat Med VL - 8 UR - https://doi.org/10.1038/nm0102-68 DO - 10.1038/nm0102-68 ID - Shipp2002 ER - TY - JOUR AU - Liu, J. J. AU - Cutler, G. AU - Li, W. AU - Pan, Z. AU - Peng, S. AU - Hoey, T. AU - Chen, L. AU - Ling, X. B. PY - 2005 DA - 2005// TI - Multiclass cancer classification and biomarker discovery using GA-based algorithms JO - Bioinformatics VL - 21 UR - https://doi.org/10.1093/bioinformatics/bti419 DO - 10.1093/bioinformatics/bti419 ID - Liu2005 ER - TY - JOUR AU - Yasui, Y. AU - Pepe, M. AU - Thompson, M. L. AU - Adam, B. -. L. AU - Wright JR, G. L. AU - Qu, Y. AU - Potter, J. D. AU - Winget, M. AU - Thornquist, M. AU - Feng, Z. PY - 2003 DA - 2003// TI - A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection JO - Biostatistics VL - 4 UR - https://doi.org/10.1093/biostatistics/4.3.449 DO - 10.1093/biostatistics/4.3.449 ID - Yasui2003 ER - TY - JOUR AU - Breiman, L. PY - 2001 DA - 2001// TI - Random Forests JO - Mach Learn VL - 45 UR - https://doi.org/10.1023/A:1010933404324 DO - 10.1023/A:1010933404324 ID - Breiman2001 ER - TY - JOUR AU - Díaz-Uriarte, R. AU - Andrés, S. A. PY - 2006 DA - 2006// TI - Gene selection and classification of microarray data using random forest JO - BMC Bioinforma VL - 7 UR - https://doi.org/10.1186/1471-2105-7-3 DO - 10.1186/1471-2105-7-3 ID - Díaz-Uriarte2006 ER - TY - JOUR AU - Strobl, C. AU - Boulesteix, A. -. L. AU - Zeileis, A. AU - Hothorn, T. PY - 2007 DA - 2007// TI - Bias in random forest variable importance measures: illustrations, sources and a solution JO - BMC Bioinforma VL - 8 UR - https://doi.org/10.1186/1471-2105-8-25 DO - 10.1186/1471-2105-8-25 ID - Strobl2007 ER - TY - JOUR AU - Liaw, A. AU - Wiener, M. PY - 2002 DA - 2002// TI - Classification and Regression by randomForest JO - R News VL - 2 ID - Liaw2002 ER - TY - JOUR AU - Qi, Y. AU - Bar-Joseph, Z. AU - Klein-Seetharaman, J. PY - 2006 DA - 2006// TI - Evaluation of Different Biological Data and Computational Classification Methods for Use in Protein Interaction Prediction JO - Proteins VL - 63 UR - https://doi.org/10.1002/prot.20865 DO - 10.1002/prot.20865 ID - Qi2006 ER - TY - JOUR AU - Criminisi, A. AU - Shotton, J. AU - Konukoglu, E. PY - 2011 DA - 2011// TI - Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning JO - Found Trends® Comput Graph Vis VL - 7 UR - https://doi.org/10.1561/0600000035 DO - 10.1561/0600000035 ID - Criminisi2011 ER - TY - BOOK AU - Efron, B. AU - Tibshirani, R. PY - 1993 DA - 1993// TI - Introduction to the Bootstrap PB - Hall CY - New York UR - https://doi.org/10.1007/978-1-4899-4541-9 DO - 10.1007/978-1-4899-4541-9 ID - Efron1993 ER - TY - JOUR AU - Svetnik, V. AU - Liaw, A. AU - Tong, C. AU - Culberson, J. C. AU - Sheridan, R. P. AU - Feuston, B. P. PY - 2003 DA - 2003// TI - Random forest: a classification and regression tool for compound classification and QSAR modeling JO - J Chem Inf Comput Sci VL - 43 UR - https://doi.org/10.1021/ci034160g DO - 10.1021/ci034160g ID - Svetnik2003 ER - TY - BOOK AU - Breiman, L. PY - 1996 DA - 1996// TI - Out-of-Bag Estimation ID - Breiman1996 ER - TY - JOUR AU - Breiman, L. PY - 1996 DA - 1996// TI - Bagging Predictors JO - Mach Learn VL - 24 ID - Breiman1996 ER - TY - JOUR AU - Breiman, L. PY - 1996 DA - 1996// TI - Heuristics of Instability and Stabilization in Model Selection JO - Ann Stat VL - 24 UR - https://doi.org/10.1214/aos/1032181158 DO - 10.1214/aos/1032181158 ID - Breiman1996 ER - TY - BOOK AU - Hastie, T. AU - Tibshirani, R. AU - Friedman, J. PY - 2005 DA - 2005// TI - The Elements of Statistical Learning: Data Mining, Inference, and Prediction PB - Springer CY - New York ID - Hastie2005 ER - TY - BOOK AU - Segal, M. R. PY - 2004 DA - 2004// TI - Machine Learning Benchmarks and Random Forest Regression ID - Segal2004 ER - TY - JOUR AU - Bauer, E. AU - Kohavi, R. PY - 2011 DA - 2011// TI - An Empirical Comparison of Voting Classification Algorithms : Bagging, Boosting, and Variants JO - Mach Learn VL - 38 ID - Bauer2011 ER - TY - JOUR AU - Dietterich, T. G. PY - 2000 DA - 2000// TI - An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization JO - Mach Learn VL - 40 UR - https://doi.org/10.1023/A:1007607513941 DO - 10.1023/A:1007607513941 ID - Dietterich2000 ER - TY - JOUR AU - Opitz, D. AU - Maclin, R. PY - 1999 DA - 1999// TI - Popular Ensemble Methods: An Emperical Study JO - J Artif Intell Res VL - 11 ID - Opitz1999 ER - TY - JOUR AU - Nagi, S. AU - Bhattacharyya, D. K. PY - 2013 DA - 2013// TI - Classification of microarray cancer data using ensemble approach JO - Netw Model Anal Heal Informatics Bioinforma VL - 2 UR - https://doi.org/10.1007/s13721-013-0034-x DO - 10.1007/s13721-013-0034-x ID - Nagi2013 ER - TY - STD TI - Snoek J, Larochelle H, Adams RP. Practical Bayesian Optimization of Machine Learning Algorithms. Adv Neural Inf Process Syst. 2012;1–9. ID - ref35 ER - TY - CHAP AU - Okun, O. AU - Priisalu, H. PY - 2007 DA - 2007// TI - Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues BT - Proc 4th Int Meet Comput Intell Methods Bioinforma Biostat Portofino, Italy ID - Okun2007 ER - TY - JOUR AU - Sun, Y. V. AU - Bielak, L. F. AU - Peyser, P. A. AU - Turner, S. T. AU - Sheedy, P. F. AU - Boerwinkle, E. AU - Kardia, S. L. R. PY - 2008 DA - 2008// TI - Application of machine learning algorithms to predict coronary artery calcification with a sibship-based design JO - Genet Epidemiol VL - 32 UR - https://doi.org/10.1002/gepi.20309 DO - 10.1002/gepi.20309 ID - Sun2008 ER - TY - JOUR AU - Sun, Y. V. PY - 2010 DA - 2010// TI - Multigenic Modeling of Complex Disease by Random Forest JO - Adv Genet VL - 72 ID - Sun2010 ER - TY - JOUR AU - Benjamini, Y. AU - Hochberg, Y. PY - 1995 DA - 1995// TI - Benjamini and Y FDR.pdf JO - J R Stat Soc Ser B VL - 57 ID - Benjamini1995 ER - TY - JOUR AU - Archer, K. J. AU - Kimes, R. V. PY - 2008 DA - 2008// TI - Empirical characterization of random forest variable importance measures JO - Comput Stat Data Anal VL - 52 UR - https://doi.org/10.1016/j.csda.2007.08.015 DO - 10.1016/j.csda.2007.08.015 ID - Archer2008 ER - TY - JOUR AU - Calle, M. L. AU - Urrea, V. PY - 2011 DA - 2011// TI - Letter to the editor: Stability of Random Forest importance measures JO - Brief Bioinform VL - 12 UR - https://doi.org/10.1093/bib/bbq011 DO - 10.1093/bib/bbq011 ID - Calle2011 ER - TY - JOUR AU - Goldstein, B. A. AU - Briggs, F. B. S. AU - Polley, E. C. PY - 2011 DA - 2011// TI - Random Forests for Genetic Association Studies JO - Stat Appl Genet Mol Biol VL - 10 ID - Goldstein2011 ER - TY - JOUR AU - Domingos, P. PY - 2012 DA - 2012// TI - A few useful things to know about machine learning JO - Commun ACM VL - 55 UR - https://doi.org/10.1145/2347736.2347755 DO - 10.1145/2347736.2347755 ID - Domingos2012 ER - TY - BOOK AU - Li, J. -. B. AU - Chu, S. -. C. AU - Pan, J. -. S. PY - 2013 DA - 2013// TI - Kernel Learning Algorithms for Face Recognition PB - Springer CY - New York ID - Li2013 ER - TY - JOUR AU - Dudoit, S. AU - Fridlyand, J. PY - 2003 DA - 2003// TI - Classification in microarray experiments JO - Stat Anal gene Expr microarray data VL - 1 ID - Dudoit2003 ER - TY - JOUR AU - Sun, Y. AU - Kamel, M. S. AU - Wong, A. K. C. AU - Wang, Y. PY - 2007 DA - 2007// TI - Cost-sensitive boosting for classification of imbalanced data JO - Pattern Recognit VL - 40 UR - https://doi.org/10.1016/j.patcog.2007.04.009 DO - 10.1016/j.patcog.2007.04.009 ID - Sun2007 ER - TY - JOUR AU - He, H. AU - Garcia, E. A. PY - 2009 DA - 2009// TI - Learning from Imbalanced Data JO - IEEE Trans Knowl Data Eng VL - 21 UR - https://doi.org/10.1109/TKDE.2008.239 DO - 10.1109/TKDE.2008.239 ID - He2009 ER - TY - CHAP AU - Domingos, P. PY - 1999 DA - 1999// TI - MetaCost: A General Method for Making Classifiers BT - Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining PB - ACM Press CY - San Diego ID - Domingos1999 ER - TY - CHAP AU - Kubat, M. AU - Matwin, S. ED - Kaufmann, M. PY - 1997 DA - 1997// TI - Addressing the Curse of Imbalanced Training Sets: One-Sided Selection BT - Proceedings of the 14th International conference on Machine Learning ID - Kubat1997 ER - TY - STD TI - Ling CX, Li C. Data Mining for Direct Marketing : Problems and Solutions. In: Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining. New York: AAAI Press; 1998. ID - ref50 ER - TY - JOUR AU - Chawla, N. V. AU - Bowyer, K. W. AU - Hall, L. O. PY - 2002 DA - 2002// TI - SMOTE: Synthetic Minority Over-sampling Technique JO - J Artif Intell Res VL - 16 ID - Chawla2002 ER - TY - BOOK AU - Breiman, L. AU - Cutler, A. AU - Liaw, A. AU - Wiener, M. PY - 2015 DA - 2015// TI - Breiman and Cutler’s random forests for classification and regression ID - Breiman2015 ER - TY - CHAP AU - Kohavi, R. ED - Kaufmann, M. PY - 1995 DA - 1995// TI - A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection BT - International Joint Conference on Artificial Intelligence (IJCAI) ID - Kohavi1995 ER - TY - STD TI - Leo Breiman. Manual - Setting up, using, and udnerstanding random forests v4.0. https://www.stat.berkeley.edu/~breiman/Using_random_forests_v4.0.pdf. UR - https://www.stat.berkeley.edu/~breiman/Using_random_forests_v4.0.pdf ID - ref54 ER - TY - STD TI - Boutros lab. HPCI. http://search.cpan.org/dist/HPCI/. UR - http://search.cpan.org/dist/HPCI/ ID - ref55 ER - TY - BOOK PY - 2014 DA - 2014// TI - doMC: Foreach parallel adaptor for the multicore package ID - ref56 ER - TY - BOOK PY - 2015 DA - 2015// TI - R: A language and environment for statistical computing ID - ref57 ER - TY - JOUR AU - Robin, X. AU - Turck, N. AU - Hainard, A. AU - Tiberti, N. AU - Lisacek, F. AU - Sanchez, J. -. C. AU - Müller, M. PY - 2011 DA - 2011// TI - pROC: an open-source package for R and S+ to analyze and compare ROC curves JO - BMC Bioinforma VL - 18 UR - https://doi.org/10.1186/1471-2105-12-77 DO - 10.1186/1471-2105-12-77 ID - Robin2011 ER - TY - JOUR AU - Lin, L. I. PY - 1989 DA - 1989// TI - A Concordance Correlation Coefficient to Evaluate Reproducibility JO - Biometrics VL - 45 UR - https://doi.org/10.2307/2532051 DO - 10.2307/2532051 ID - Lin1989 ER - TY - BOOK AU - Sarkar, D. PY - 2008 DA - 2008// TI - Lattice: Multivariate Data Visualization with R PB - Springer CY - New York UR - https://doi.org/10.1007/978-0-387-75969-2 DO - 10.1007/978-0-387-75969-2 ID - Sarkar2008 ER - TY - BOOK AU - Sarkar, D. AU - Andrews, F. PY - 2013 DA - 2013// TI - latticeExtra: Extra Graphical Utilities Based on Lattice ID - Sarkar2013 ER - TY - JOUR AU - Sun, J. AU - Zhao, H. PY - 2015 DA - 2015// TI - The application of sparse estimation of covariance matrix to quadratic discriminant analysis JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-014-0443-6 DO - 10.1186/s12859-014-0443-6 ID - Sun2015 ER - TY - JOUR AU - Shankar, J. AU - Szpakowski, S. AU - Solis, N. V. AU - Mounaud, S. AU - Liu, H. AU - Losada, L. AU - Nierman, W. C. AU - Filler, S. G. PY - 2015 DA - 2015// TI - A systematic evaluation of high-dimensional, ensemble-based regression for exploring large model spaces in microbiome analyses JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0467-6 DO - 10.1186/s12859-015-0467-6 ID - Shankar2015 ER - TY - JOUR AU - Wu, A. C. -. Y. AU - Rifkin, S. A. PY - 2015 DA - 2015// TI - Aro: a machine learning approach to identifying single molecules and estimating classification error in fluorescence microscopy images JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0534-z DO - 10.1186/s12859-015-0534-z ID - Wu2015 ER - TY - JOUR AU - Lee, J. AU - Lee, K. AU - Joung, I. AU - Joo, K. AU - Brooks, B. R. AU - Lee, J. PY - 2015 DA - 2015// TI - Sigma-RF: prediction of the variability of spatial restraints in template-based modeling by random forest JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0526-z DO - 10.1186/s12859-015-0526-z ID - Lee2015 ER - TY - JOUR AU - Limongelli, I. AU - Marini, S. AU - Bellazzi, R. PY - 2015 DA - 2015// TI - PaPI: pseudo amino acid composition to score human protein-coding variants JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0554-8 DO - 10.1186/s12859-015-0554-8 ID - Limongelli2015 ER - TY - JOUR AU - Hofner, B. AU - Boccuto, L. AU - Göker, M. PY - 2015 DA - 2015// TI - Controlling false discoveries in high-dimensional situations: boosting with stability selection JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0575-3 DO - 10.1186/s12859-015-0575-3 ID - Hofner2015 ER - TY - JOUR AU - Fratello, M. AU - Serra, A. AU - Fortino, V. AU - Raiconi, G. AU - Tagliaferri, R. AU - Greco, D. PY - 2015 DA - 2015// TI - A multi-view genomic data simulator JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0577-1 DO - 10.1186/s12859-015-0577-1 ID - Fratello2015 ER - TY - JOUR AU - Ruiz-Blanco, Y. B. AU - Paz, W. AU - Green, J. AU - Marrero-Ponce, Y. PY - 2015 DA - 2015// TI - ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0586-0 DO - 10.1186/s12859-015-0586-0 ID - Ruiz-Blanco2015 ER - TY - JOUR AU - Sanders, J. AU - Singh, A. AU - Sterne, G. AU - Ye, B. AU - Zhou, J. PY - 2015 DA - 2015// TI - Learning-guided automatic three dimensional synapse quantification for drosophila neurons JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0616-y DO - 10.1186/s12859-015-0616-y ID - Sanders2015 ER - TY - JOUR AU - Schönenberger, F. AU - Deutzmann, A. AU - Ferrando-May, E. AU - Merhof, D. PY - 2015 DA - 2015// TI - Discrimination of cell cycle phases in PCNA-immunolabeled cells JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0618-9 DO - 10.1186/s12859-015-0618-9 ID - Schönenberger2015 ER - TY - JOUR AU - Novianti, P. W. AU - Jong, V. L. AU - Roes, K. C. B. AU - Eijkemans, M. J. C. PY - 2015 DA - 2015// TI - Factors affecting the accuracy of a class prediction model in gene expression data JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0610-4 DO - 10.1186/s12859-015-0610-4 ID - Novianti2015 ER - TY - JOUR AU - Cheng, X. AU - Cai, H. AU - Zhang, Y. AU - Xu, B. AU - Su, W. PY - 2015 DA - 2015// TI - Optimal combination of feature selection and classification via local hyperplane based learning strategy JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0629-6 DO - 10.1186/s12859-015-0629-6 ID - Cheng2015 ER - TY - JOUR AU - Ogoe, H. A. AU - Visweswaran, S. AU - Lu, X. AU - Gopalakrishnan, V. PY - 2015 DA - 2015// TI - Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0643-8 DO - 10.1186/s12859-015-0643-8 ID - Ogoe2015 ER - TY - JOUR AU - Kuhring, M. AU - Dabrowski, P. W. AU - Piro, V. C. AU - Nitsche, A. AU - Renard, B. Y. PY - 2015 DA - 2015// TI - SuRankCo: supervised ranking of contigs in de novo assemblies JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0644-7 DO - 10.1186/s12859-015-0644-7 ID - Kuhring2015 ER - TY - JOUR AU - Khurana, J. K. AU - Reeder, J. E. AU - Shrimpton, A. E. AU - Thakar, J. PY - 2015 DA - 2015// TI - GESPA: classifying nsSNPs to predict disease association JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0673-2 DO - 10.1186/s12859-015-0673-2 ID - Khurana2015 ER - TY - JOUR AU - Ren, H. AU - Shen, Y. PY - 2015 DA - 2015// TI - RNA-binding residues prediction using structural features JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0691-0 DO - 10.1186/s12859-015-0691-0 ID - Ren2015 ER - TY - JOUR AU - Serra, A. AU - Fratello, M. AU - Fortino, V. AU - Raiconi, G. AU - Tagliaferri, R. AU - Greco, D. PY - 2015 DA - 2015// TI - MVDA: a multi-view genomic data integration methodology JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0680-3 DO - 10.1186/s12859-015-0680-3 ID - Serra2015 ER - TY - JOUR AU - Korir, P. K. AU - Geeleher, P. AU - Seoighe, C. PY - 2015 DA - 2015// TI - Seq-ing improved gene expression estimates from microarrays using machine learning JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0712-z DO - 10.1186/s12859-015-0712-z ID - Korir2015 ER - TY - JOUR AU - Sakellariou, A. AU - Spyrou, G. PY - 2015 DA - 2015// TI - mAPKL: R/ Bioconductor package for detecting gene exemplars and revealing their characteristics JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0719-5 DO - 10.1186/s12859-015-0719-5 ID - Sakellariou2015 ER - TY - JOUR AU - Huang, H. AU - Fava, A. AU - Guhr, T. AU - Cimbro, R. AU - Rosen, A. AU - Boin, F. AU - Ellis, H. PY - 2015 DA - 2015// TI - A methodology for exploring biomarker-phenotype associations: application to flow cytometry data and systemic sclerosis clinical manifestations JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0722-x DO - 10.1186/s12859-015-0722-x ID - Huang2015 ER - TY - JOUR AU - Blagus, R. AU - Lusa, L. PY - 2015 DA - 2015// TI - Boosting for high-dimensional two-class prediction JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0723-9 DO - 10.1186/s12859-015-0723-9 ID - Blagus2015 ER - TY - JOUR AU - Bellot, P. AU - Olsen, C. AU - Salembier, P. AU - Oliveras-Vergés, A. AU - Meyer, P. E. PY - 2015 DA - 2015// TI - NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0728-4 DO - 10.1186/s12859-015-0728-4 ID - Bellot2015 ER - TY - JOUR AU - König, C. AU - Cárdenas, M. I. AU - Giraldo, J. AU - Alquézar, R. AU - Vellido, A. PY - 2015 DA - 2015// TI - Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0731-9 DO - 10.1186/s12859-015-0731-9 ID - König2015 ER - TY - JOUR AU - Cremona, M. A. AU - Sangalli, L. M. AU - Vantini, S. AU - Dellino, G. I. AU - Pelicci, P. G. AU - Secchi, P. AU - Riva, L. PY - 2015 DA - 2015// TI - Peak shape clustering reveals biological insights JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0787-6 DO - 10.1186/s12859-015-0787-6 ID - Cremona2015 ER - TY - JOUR AU - Ditzler, G. AU - Morrison, J. C. AU - Lan, Y. AU - Rosen, G. L. PY - 2015 DA - 2015// TI - Fizzy: feature subset selection for metagenomics JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0793-8 DO - 10.1186/s12859-015-0793-8 ID - Ditzler2015 ER - TY - JOUR AU - Landoni, E. AU - Miceli, R. AU - Callari, M. AU - Tiberio, P. AU - Appierto, V. AU - Angeloni, V. AU - Mariani, L. AU - Daidone, M. G. PY - 2015 DA - 2015// TI - Proposal of supervised data analysis strategy of plasma miRNAs from hybridisation array data with an application to assess hemolysis-related deregulation JO - BMC Bioinforma VL - 16 UR - https://doi.org/10.1186/s12859-015-0820-9 DO - 10.1186/s12859-015-0820-9 ID - Landoni2015 ER -