Pairwise gene GO-based measures for biclustering of high-dimensional expression data
暂无分享,去创建一个
Juan A. Nepomuceno | Alicia Troncoso Lora | Jesús S. Aguilar-Ruiz | Isabel A. Nepomuceno-Chamorro | J. Aguilar-Ruiz | Alicia Troncoso
[1] Katharina J. Hoff,et al. Orphelia: predicting genes in metagenomic sequencing reads , 2009, Nucleic Acids Res..
[2] Takashi Yoneya,et al. TCP: a tool for designing chimera proteins based on the tertiary structure information , 2009, BMC Bioinformatics.
[3] J. Morgan,et al. Problems in the Analysis of Survey Data, and a Proposal , 1963 .
[4] Catia Pesquita,et al. Metrics for GO based protein semantic similarity: a systematic evaluation , 2008, BMC Bioinformatics.
[5] F. Wagner. GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge , 2015, PloS one.
[6] T. M. Murali,et al. Extracting Conserved Gene Expression Motifs from Gene Expression Data , 2002, Pacific Symposium on Biocomputing.
[7] Jesús S. Aguilar-Ruiz,et al. Shifting and scaling patterns from gene expression data , 2005, Bioinform..
[8] Juan A. Nepomuceno,et al. Integrating biological knowledge based on functional annotations for biclustering of gene expression data , 2015, Comput. Methods Programs Biomed..
[9] Alex E. Lash,et al. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..
[10] P. Nelson,et al. Theory of high-force DNA stretching and overstretching. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[11] Mehmet Deveci,et al. A comparative analysis of biclustering algorithms for gene expression data , 2013, Briefings Bioinform..
[12] Ying Xu,et al. QUBIC: a qualitative biclustering algorithm for analyses of gene expression data , 2009, Nucleic acids research.
[13] Joseph T. Chang,et al. Spectral biclustering of microarray data: coclustering genes and conditions. , 2003, Genome research.
[14] Joaquín Dopazo,et al. Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling , 2010, Nucleic Acids Res..
[15] Rachael P. Huntley,et al. QuickGO: a web-based tool for Gene Ontology searching , 2009, Bioinform..
[16] Federico Divina,et al. A multi-objective approach to discover biclusters in microarray data , 2007, GECCO '07.
[17] Arlindo L. Oliveira,et al. Biclustering algorithms for biological data analysis: a survey , 2004, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[18] Chris Sander,et al. Characterizing gene sets with FuncAssociate , 2003, Bioinform..
[19] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[20] Lincoln Stein,et al. Reactome pathway analysis to enrich biological discovery in proteomics data sets , 2011, Proteomics.
[21] Michelangelo Ceci,et al. A Novel Biclustering Algorithm for the Discovery of Meaningful Biological Correlations between microRNAs and their Target Genes , 2013, BMC Bioinformatics.
[22] Sushmita Mitra,et al. Evolutionary biclustering of gene expressions , 2006, UBIQ.
[23] Juan A. Nepomuceno,et al. Biclustering of Gene Expression Data by Correlation-Based Scatter Search , 2011, BioData Mining.
[24] Anindya Bhattacharya,et al. Bi-correlation clustering algorithm for determining a set of co-regulated genes , 2009, Bioinform..
[25] Roded Sharan,et al. Biclustering Algorithms: A Survey , 2007 .
[26] Paul Strauss,et al. Genome Stability And Human Diseases , 2016 .
[27] Ricardo J. G. B. Campello,et al. A systematic comparative evaluation of biclustering techniques , 2017, BMC Bioinformatics.
[28] Hong Yan,et al. Finding Correlated Biclusters from Gene Expression Data , 2011, IEEE Transactions on Knowledge and Data Engineering.
[29] Richard M. Karp,et al. Discovering local structure in gene expression data: the order-preserving submatrix problem , 2002, RECOMB '02.
[30] Juan A. Nepomuceno,et al. An Overlapping Control–Biclustering Algorithm from Gene Expression Data , 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.
[31] Gwan-Su Yi,et al. Biclustering for the comprehensive search of correlated gene expression patterns using clustered seed expansion , 2013, BMC Genomics.
[32] George M. Church,et al. Biclustering of Expression Data , 2000, ISMB.
[33] Jinyan Li,et al. Maximization of negative correlations in time-course gene expression data for enhancing understanding of molecular pathways , 2009, Nucleic acids research.
[34] Francesca D. Ciccarelli,et al. NCG 5.0: updates of a manually curated repository of cancer genes and associated properties from cancer mutational screenings , 2015, Nucleic Acids Res..
[35] Shusaku Tsumoto,et al. Mining Rules for Risk Factors on Blood Stream Infection in Hospital Information System , 2007, 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007).
[36] Derek Y. Chiang,et al. MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery , 2010, Nucleic acids research.
[37] Francisco Azuaje,et al. Bioinformatics and biomarker discovery : "omic" data analysis for personalised medicine , 2010 .
[38] Rui Henriques,et al. BiC2PAM: constraint-guided biclustering for biological data analysis with domain knowledge , 2016, Algorithms for Molecular Biology.
[39] Jesús S. Aguilar-Ruiz,et al. Biclustering on expression data: A review , 2015, J. Biomed. Informatics.
[40] Sven Bergmann,et al. Iterative signature algorithm for the analysis of large-scale gene expression data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[41] Adetayo Kasim,et al. Applied Biclustering Methods for Big and High-Dimensional Data Using R , 2016 .
[42] Ruggero G. Pensa,et al. Leveraging additional knowledge to support coherent bicluster discovery in gene expression data , 2014, Intell. Data Anal..
[43] Philip S. Yu,et al. An Improved Biclustering Method for Analyzing Gene Expression Profiles , 2005, Int. J. Artif. Intell. Tools.
[44] Panos M. Pardalos,et al. Biclustering in data mining , 2008, Comput. Oper. Res..
[45] D. Altman,et al. Multiple significance tests: the Bonferroni method , 1995, BMJ.
[46] Ricardo J. G. B. Campello,et al. Proximity Measures for Clustering Gene Expression Microarray Data: A Validation Methodology and a Comparative Analysis , 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[47] Lothar Thiele,et al. A systematic comparison and evaluation of biclustering methods for gene expression data , 2006, Bioinform..
[48] Mark Woodbridge,et al. XperimentR: painless annotation of a biological experiment for the laboratory scientist , 2013, BMC Bioinformatics.
[49] Zhoujun Li,et al. Biclustering of microarray data with MOSPO based on crowding distance , 2009, BMC Bioinformatics.
[50] Pedro Larrañaga,et al. A new measure for gene expression biclustering based on non-parametric correlation , 2013, Comput. Methods Programs Biomed..
[51] Juan Cui. Genomic Data Analysis for Personalized Medicine , 2015 .
[52] Knut Reinert,et al. Robust consensus computation , 2008, BMC Bioinformatics.
[53] Francisco Azuaje. Bioinformatics and Biomarker Discovery , 2010 .
[54] Juan A. Nepomuceno,et al. Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure , 2016, HAIS.
[55] Juan A. Nepomuceno,et al. Scatter search-based identification of local patterns with positive and negative correlations in gene expression data , 2015, Appl. Soft Comput..
[56] Jin-Kao Hao,et al. A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data , 2009, BioData Mining.
[57] L. Lazzeroni. Plaid models for gene expression data , 2000 .
[58] Jessica Andrea Carballido,et al. Microarray Biclustering: A Novel Memetic Approach Based on the PISA Platform , 2009, EvoBIO.
[59] Rafael Martí,et al. Scatter Search: Diseño Básico y Estrategias avanzadas , 2002, Inteligencia Artif..
[60] Ricardo Martínez,et al. GenMiner: Mining Informative Association Rules from Genomic Data , 2007, 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007).
[61] Carsten Wiuf,et al. Co-clustering and visualization of gene expression data and gene ontology terms for Saccharomyces cerevisiae using self-organizing maps , 2007, J. Biomed. Informatics.
[62] Valentin Wagner,et al. Towards a Psychological Construct of Being Moved , 2015, PloS one.
[63] Ulrich Bodenhofer,et al. FABIA: factor analysis for bicluster acquisition , 2010, Bioinform..
[64] Edward W. J. Curry. A framework for generalized subspace pattern mining in high-dimensional datasets , 2014, BMC Bioinformatics.
[65] Sébastien Lê,et al. A new unsupervised gene clustering algorithm based on the integration of biological knowledge into expression data , 2013, BMC Bioinformatics.