Ontologies and Functional Genomics
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[1] J. Schug,et al. Predicting gene ontology functions from ProDom and CDD protein domains. , 2002, Genome research.
[2] Fatima Al-Shahrour,et al. The Use of Go Terms to Understand the Biological Significance of Microarray Differential Gene Expression Data , 2004 .
[3] Mark D. Robinson,et al. FunSpec: a web-based cluster interpreter for yeast , 2002, BMC Bioinformatics.
[4] T. Jenssen,et al. A literature network of human genes for high-throughput analysis of gene expression , 2001 .
[5] P. Brown,et al. Exploring the metabolic and genetic control of gene expression on a genomic scale. , 1997, Science.
[6] L Hunter,et al. MedMiner: an Internet text-mining tool for biomedical information, with application to gene expression profiling. , 1999, BioTechniques.
[7] Jeffrey T. Chang,et al. The computational analysis of scientific literature to define and recognize gene expression clusters. , 2003, Nucleic acids research.
[8] J. Booth,et al. Resampling-Based Multiple Testing. , 1994 .
[9] M. Gerstein,et al. Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons. , 2002, Genome research.
[10] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[11] J. Dopazo,et al. Phylogenetic Reconstruction Using an Unsupervised Growing Neural Network That Adopts the Topology of a Phylogenetic Tree , 1997, Journal of Molecular Evolution.
[12] P. Khatri,et al. Profiling gene expression using onto-express. , 2002, Genomics.
[13] C. Blaschke,et al. Expression profiles and biological function. , 2000, Genome informatics. Workshop on Genome Informatics.
[14] Jeffrey T. Chang,et al. Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature. , 2002, Genome research.
[15] M. Daly,et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.
[16] May D. Wang,et al. GoMiner: a resource for biological interpretation of genomic and proteomic data , 2003, Genome Biology.
[17] Bart Kosko,et al. Neural networks for signal processing , 1992 .
[18] Susumu Goto,et al. The KEGG resource for deciphering the genome , 2004, Nucleic Acids Res..
[19] Steven C. Lawlor,et al. MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data , 2003, Genome Biology.
[20] J. Bard,et al. Ontologies in biology: design, applications and future challenges , 2004, Nature Reviews Genetics.
[21] Joaquín Dopazo,et al. GEPAS: a web-based resource for microarray gene expression data analysis , 2003, Nucleic Acids Res..
[22] Avi Shoshan,et al. Large-scale protein annotation through gene ontology. , 2002, Genome research.
[23] Gavin MacBeath,et al. Protein microarrays and proteomics , 2002, Nature Genetics.
[24] Søren Brunak,et al. Prediction of human protein function according to Gene Ontology categories , 2003, Bioinform..
[25] Joaquín Dopazo,et al. Using gene ontology on genome-scale studies to find significant associations of biologically relevant terms to groups of genes , 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).
[26] Andrew J. Holloway,et al. Options available—from start to finish—for obtaining data from DNA microarrays II , 2002, Nature Genetics.
[27] T. Speed,et al. GOstat: find statistically overrepresented Gene Ontologies within a group of genes. , 2004, Bioinformatics.
[28] Joaquín Dopazo,et al. FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes , 2004, Bioinform..
[29] Alex Bateman,et al. The InterPro Database, 2003 brings increased coverage and new features , 2003, Nucleic Acids Res..
[30] B. Snel,et al. Predicting gene function by conserved co-expression. , 2003, Trends in genetics : TIG.
[31] Y. Benjamini,et al. THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .
[32] R. Altman,et al. Using text analysis to identify functionally coherent gene groups. , 2002, Genome research.
[33] Daniel L. Hartl,et al. GeneMerge - Post-genomic Analysis, Data Mining, and Hypothesis Testing , 2003, Bioinform..
[34] Alfonso Valencia,et al. A hierarchical unsupervised growing neural network for clustering gene expression patterns , 2001, Bioinform..
[35] Ioannis Xenarios,et al. DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions , 2002, Nucleic Acids Res..
[36] M. Vidal,et al. Integrating 'omic' information: a bridge between genomics and systems biology. , 2003, Trends in genetics : TIG.
[37] D. Barrell,et al. The Gene Ontology Annotation (GOA) project: implementation of GO in SWISS-PROT, TrEMBL, and InterPro. , 2003, Genome research.
[38] D. Botstein,et al. Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[39] William Stafford Noble,et al. Exploring Gene Expression Data with Class Scores , 2001, Pacific Symposium on Biocomputing.
[40] Alfonso Valencia,et al. Information extraction in molecular biology , 2002, Briefings Bioinform..
[41] N. H. Shah,et al. CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology , 2004, Bioinform..
[42] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .