Meta-clustering of gene expression data and literature-based information
暂无分享,去创建一个
[1] Francis D. Gibbons,et al. Judging the quality of gene expression-based clustering methods using gene annotation. , 2002, Genome research.
[2] Robert Tibshirani,et al. Estimating the number of clusters in a data set via the gap statistic , 2000 .
[3] John Quackenbush,et al. Computational genetics: Computational analysis of microarray data , 2001, Nature Reviews Genetics.
[4] Russ B. Altman,et al. A literature-based method for assessing the functional coherence of a gene group , 2003, Bioinform..
[5] Russ B. Altman,et al. Inclusion of Textual Documentation in the Analysis of Multidimensional Data Sets: Application to Gene Expression Data , 2003, Machine Learning.
[6] Alexander E. Kel,et al. TRANSFAC®: transcriptional regulation, from patterns to profiles , 2003, Nucleic Acids Res..
[7] Ali S. Hadi,et al. Finding Groups in Data: An Introduction to Chster Analysis , 1991 .
[8] Michael Ruogu Zhang,et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.
[9] D. Pe’er,et al. Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data , 2003, Nature Genetics.
[10] A. Valencia,et al. Mining functional information associated with expression arrays , 2001, Functional & Integrative Genomics.
[11] H. Bussemaker,et al. Regulatory element detection using correlation with expression , 2001, Nature Genetics.
[12] Esko Ukkonen,et al. Mining for Putative Regulatory Elements in the Yeast Genome Using Gene Expression Data , 2000, ISMB.
[13] G. Church,et al. Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae. , 2000, Journal of molecular biology.
[14] Nicola J. Rinaldi,et al. Transcriptional Regulatory Networks in Saccharomyces cerevisiae , 2002, Science.
[15] Ka Yee Yeung,et al. Principal component analysis for clustering gene expression data , 2001, Bioinform..
[16] B. De Moor,et al. TXTGate: profiling gene groups with text-based information , 2004, Genome Biology.
[17] Jung-Hsien Chiang,et al. MeKE: Discovering the Functions of Gene Products from Biomedical Literature Via Sentence Alignment , 2003, Bioinform..
[18] Bart De Moor,et al. Text-Based Gene Profiling with Domain-Specific Views , 2003, SWDB.
[19] William B. Frakes,et al. Stemming Algorithms , 1992, Information Retrieval: Data Structures & Algorithms.
[20] Thomas Lengauer,et al. Analysis of Gene Expression Data with Pathway Scores , 2000, ISMB.
[21] Anil K. Jain,et al. Algorithms for Clustering Data , 1988 .
[22] Mark J. van der Laan,et al. A Method to Identify Significant Clusters in Gene Expression Data , 2002 .
[23] Jeffrey T. Chang,et al. The computational analysis of scientific literature to define and recognize gene expression clusters. , 2003, Nucleic acids research.
[24] Jeffrey B. Colombe,et al. Finding relevant references to genes and proteins in Medline using a Bayesian approach , 2002, Bioinform..
[25] Kathleen Marchal,et al. INCLUSive: a web portal and service registry for microarray and regulatory sequence analysis , 2003, Nucleic Acids Res..
[27] Andreas D. Baxevanis,et al. The Molecular Biology Database Collection: 2002 update , 2002, Nucleic Acids Res..
[28] Isabelle Guyon,et al. A Stability Based Method for Discovering Structure in Clustered Data , 2001, Pacific Symposium on Biocomputing.
[29] T. Jenssen,et al. A literature network of human genes for high-throughput analysis of gene expression , 2001 .
[30] D. Chaussabel,et al. Mining microarray expression data by literature profiling , 2002, Genome Biology.
[31] Ronald W. Davis,et al. A genome-wide transcriptional analysis of the mitotic cell cycle. , 1998, Molecular cell.
[32] Jun S. Liu,et al. Integrating regulatory motif discovery and genome-wide expression analysis , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[33] Hagit Shatkay,et al. Information retrieval meets gene analysis , 2002 .
[34] William Stafford Noble,et al. Exploring Gene Expression Data with Class Scores , 2001, Pacific Symposium on Biocomputing.
[35] David D. Lewis,et al. An evaluation of phrasal and clustered representations on a text categorization task , 1992, SIGIR '92.
[36] G. Church,et al. Systematic determination of genetic network architecture , 1999, Nature Genetics.
[37] M. Eisen,et al. Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering , 2002, Genome Biology.
[38] Jeffrey T. Chang,et al. Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature. , 2002, Genome research.
[39] angesichts der Corona-Pandemie,et al. UPDATE , 1973, The Lancet.
[40] L Hunter,et al. MedMiner: an Internet text-mining tool for biomedical information, with application to gene expression profiling. , 1999, BioTechniques.
[41] Ka Yee Yeung,et al. Validating clustering for gene expression data , 2001, Bioinform..
[42] Javed Mostafa,et al. Detecting Gene Relations from MEDLINE Abstracts , 2000, Pacific Symposium on Biocomputing.
[43] Yoshihiro Yamanishi,et al. Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis , 2003, ISMB.
[44] David R. Bickel,et al. Robust Cluster Analysis of Microarray Gene Expression Data with the Number of Clusters Determined Biologically , 2003, Bioinform..
[45] Jason Weston,et al. Learning Gene Functional Classifications from Multiple Data Types , 2002, J. Comput. Biol..
[46] B. De Moor,et al. Comparison and meta-analysis of microarray data: from the bench to the computer desk. , 2003, Trends in genetics : TIG.
[47] T. Jenssen,et al. A literature network of human genes for high-throughput analysis of gene expression , 2001, Nature Genetics.
[48] M. Vidal. A Biological Atlas of Functional Maps , 2001, Cell.
[49] Bart De Moor,et al. Evaluation of the Vector Space Representation in Text-Based Gene Clustering , 2002, Pacific Symposium on Biocomputing.