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A comparison of four clustering methods for brain expression microarray data

Alexander L Richards, Peter Holmans, Michael C O'Donovan, Michael J Owen, Lesley Jones
2008 BMC Bioinformatics  
Conclusion: Considered alone, k-means clustering is the most effective of the four methods on typical microarray brain expression datasets.  ...  DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool.  ...  We would also like to thank Seth Dobrin for access to his data, and the two anonymous reviewers for their suggestions and constructive criticism.  ... 
doi:10.1186/1471-2105-9-490 pmid:19032745 pmcid:PMC2655095 fatcat:6vmhtqrzz5cbdf7c4w3kszkjoe

A genome-scale map of expression for a mouse brain section obtained using voxelation

Mark H. Chin, Alex B. Geng, Arshad H. Khan, Wei-Jun Qian, Vladislav A. Petyuk, Jyl Boline, Shawn Levy, Arthur W. Toga, Richard D. Smith, Richard M. Leahy, Desmond J. Smith
2007 Physiological Genomics  
We have reconstructed two-dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at  ...  A genomescale map of expression for a mouse brain section obtained using voxelation. pression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases  ...  ACKNOWLEDGMENTS We thank Steve Anderson, Allan Mackenzie-Graham, and Daniel Sforza at LONI for help in importing the voxelation data into MBAT.  ... 
doi:10.1152/physiolgenomics.00287.2006 pmid:17504947 pmcid:PMC3299369 fatcat:iak6cxqpgjevvko3xcosdbmp3i

Comparison and consolidation of microarray data sets of human tissue expression

Jenny Russ, Matthias E Futschik
2010 BMC Genomics  
Results: We present here the first comparison and integration of four freely available tissue expression data sets generated using three different microarray platforms and containing a total of 377 microarray  ...  Several recent studies addressed this formidable task using microarray technologies. These large tissue expression data sets have provided us an important basis for biomedical research.  ...  Acknowledgements We thank John Castle from Rosetta Inpharmatics LLC for providing us the tissue expression data sets (i.e. Rosetta1 and Rosetta2) and the reviewers for the valuable suggestions.  ... 
doi:10.1186/1471-2164-11-305 pmid:20465848 pmcid:PMC2885367 fatcat:fllxkgkpqbh7riekocfnntphcq

Methods for Evaluating Agglomerative Hierarchical Clustering for Gene Expression Data: A Comparative Study

Md. Bipul Hossen
2015 Computational Biology and Bioinformatics  
This paper compared the performance of seven AHC methods for clustering gene expression data with respect to five major proximity measures.  ...  All of the authors concretely suggested complete linkage method to further researchers to determine the best method for clustering their gene expression data.  ...  Acknowledgement The authors would like to thank the anonymous reviewers for their helpful comments.  ... 
doi:10.11648/j.cbb.20150306.12 fatcat:vfe7hwhf5jc4fbvmnjlzoedc7e

Cross-Species Analysis of Gene Expression and Function in Prefrontal Cortex, Hippocampus and Striatum

Wei Chen, Xiayu Xia, Nan Song, Ying Wang, Hua Zhu, Wei Deng, Qi Kong, Xianmin Pan, Chuan Qin, Bernd Sokolowski
2016 PLoS ONE  
Methods We systematically compared, based on large scale integrated microarray data, the transcriptomes of three anatomically distinct brain regions; prefrontal cortex (PFC), hippocampus (HIP) and striatum  ...  Hierarchical clustering and principal component analysis (PCA) were selected for expression pattern analysis.  ...  Robert A. Haas for a careful review of the manuscript.  ... 
doi:10.1371/journal.pone.0164295 pmid:27716781 pmcid:PMC5055290 fatcat:gmhk56lltng4ldcmr3hl2wr7ye

Picturing gene expression in the brain

Agnieszka M Lichanska
2002 Genome Biology  
By combining the data for the entire surface of a volume of a brain section they can generate a threedimensional spatial pattern of gene expression.  ...  Voxelation is used as a novel method for three-dimensional imaging of gene expression in the brain Significance and context The brain is a very complex organ, containing various cell types, many millions  ...  Analysis of the microarray data has identified two clusters of genes co-regulated in the two samples.  ... 
doi:10.1186/gb-2002-3-5-reports0025 fatcat:ssvkzqgk7fbfdnvgcxbvmnhqbe

Shambhala: a platform-agnostic data harmonizer for gene expression data

Nicolas Borisov, Irina Shabalina, Victor Tkachev, Maxim Sorokin, Andrew Garazha, Andrey Pulin, Ilya I. Eremin, Anton Buzdin
2019 BMC Bioinformatics  
Here we present a new bioinformatic tool termed Shambhala for harmonization of multiple human gene expression datasets obtained using different experimental methods and platforms of microarray hybridization  ...  platform-independent biologically meaningful clustering for the data obtained from multiple experimental platforms.  ...  All the gene expression data that were used for research, including the datasets from MAQC, SEQC and GTEx projects, were taken from publicly available repository Gene Expression Omnibus (GEO), and had  ... 
doi:10.1186/s12859-019-2641-8 fatcat:eldsaomt3vcylestzlm7wfvoia

Discovery of tissue-specific exons using comprehensive human exon microarrays

Tyson A Clark, Anthony C Schweitzer, Tina X Chen, Michelle K Staples, Gang Lu, Hui Wang, Alan Williams, John E Blume
2007 Genome Biology  
Large-scale methods for monitoring gene expression must adapt in order to accurately detect the transcript variation generated by this splicing.  ...  expression outside of known exons and well annotated genes and a high frequency of alternative splicing events.  ...  Acknowledgements We would like to thank Yan Cao, Linda Hsie, and Sophie Wu for their work developing the target preparation assay.  ... 
doi:10.1186/gb-2007-8-4-r64 pmid:17456239 pmcid:PMC1896007 fatcat:j4hirr7cv5hitokvj53rhf6a3u

Detecting tissue-specific regulation of alternative splicing as a qualitative change in microarray data

Keith Le, Katherine Mitsouras, Meenakshi Roy, Qi Wang, Qiang Xu, Stanley F. Nelson, Christopher Lee
2004 Nucleic Acids Research  
distinct from those obtained by hierarchical clustering of gene expression from the same microarray data.  ...  We have tested this analysis method on microarray data for five human tissues, generated using a standard microarray platform and experimental protocols shown previously to be sensitive to alternative  ...  Collins for helpful comments on this work, and Agilent for kindly providing microarrays.  ... 
doi:10.1093/nar/gnh173 pmid:15598820 pmcid:PMC545471 fatcat:soop3ivcgngufbhdwwuta3rx5m

Gene Expression Profiling in Postmortem Rett Syndrome Brain: Differential Gene Expression and Patient Classification

Carlo Colantuoni, Ok-Hee Jeon, Karim Hyder, Alex Chenchik, Anis H. Khimani, Vinodh Narayanan, Eric P. Hoffman, Walter E. Kaufmann, SakkuBai Naidu, Jonathan Pevsner
2001 Neurobiology of Disease  
Using multiple cDNA microarray technologies, subtractive hybridization, and conventional biochemistry, we generated comprehensive gene expression profiles of postmortem brain tissue from RTT patients and  ...  Although previously achieved in cancers, our results constitute the first report of human disease classification using gene expression profiling in a complex tissue source such as brain.  ...  ACKNOWLEDGMENTS We thank the individuals and families who made donations to the brain banks, and the Brain and Tissue Bank for Developmental Disorders at the University of Maryland and the Harvard Brain  ... 
doi:10.1006/nbdi.2001.0428 pmid:11592853 fatcat:nrvst4ity5drxcwjrepo2qijta

Congruence of tissue expression profiles from Gene Expression Atlas, SAGEmap and TissueInfo databases

Lukasz Huminiecki, Andrew T Lloyd, Kenneth H Wolfe
2003 BMC Genomics  
Additional insights may be derived by data integration and cross-platform comparisons of expression profiles.  ...  These are repositories of oligonucleotide microarray, Serial Analysis of Gene Expression and Expressed Sequence Tag human gene expression data respectively.  ...  Keith Ching, Genome Informatics Group, Novartis Genomics Institute for providing us with mapping of Affymetrix microarray probes to UniGene clusters, and Dr. Greg Singer for helpful discussions.  ... 
doi:10.1186/1471-2164-4-31 pmid:12885301 pmcid:PMC183867 fatcat:rch2es6oevb6hlmol4c6gblxma

The microarray data analysis process: From raw data to biological significance

N. Eric Olson
2006 NeuroRx  
using cutoff of 5% PCER -using a 5% PCER means a 5% chance of error for each comparison, so perhaps 50 errors for 1000 comparisons.  ...  Partitioning methods partition the data (list of genes) into a prespecified number (K) of mutually exclusive groups based on feature vector (expression profile).  ...  Innate Immune Responses of Drosophila Resources Monthly Webinar Series Archived -Microarray Analysis of Gene Expression in Huntington's Disease Peripheral Blood -a Platform Comparison Archived -Using  ... 
doi:10.1016/j.nurx.2006.05.005 pmid:16815220 pmcid:PMC3593381 fatcat:j45gumtz4fenlntn75d7zbno6i

Microarray analysis of microRNA expression in the developing mammalian brain

Eric A Miska, Ezequiel Alvarez-Saavedra, Matthew Townsend, Akira Yoshii, Nenad Sestan, Pasko Rakic, Martha Constantine-Paton, H Robert Horvitz
2004 Genome Biology  
We used this method to determine the microRNA expression profile during mouse brain development and observed a temporal wave of gene expression of sequential classes of microRNAs.  ...  Next, we developed a microarray technology suitable for detecting microRNAs and printed a microRNA microarray representing 138 mammalian microRNAs corresponding to the sequences of the microRNAs we cloned  ...  We also thank Sanchita Bhattacharya, Xuan Shirley Li and Sean Milton from the MIT BioMicroCenter for help with microarray printing and data analysis and Lucila Scimone and Justin Lamb for help with the  ... 
doi:10.1186/gb-2004-5-9-r68 pmid:15345052 pmcid:PMC522875 fatcat:x4zqgcbwgvgzheo6swglmri6ya

MicroRNA Expression Profiling Reveals MiRNA Families Regulating Specific Biological Pathways in Mouse Frontal Cortex and Hippocampus

Juuso Juhila, Tessa Sipilä, Katherine Icay, Daniel Nicorici, Pekka Ellonen, Aleksi Kallio, Eija Korpelainen, Dario Greco, Iiris Hovatta, Eliana Saul Furquim Werneck Abdelhay
2011 PLoS ONE  
We have developed a miRNA-Seq approach with a bioinformatic analysis workflow that is suitable for studying miRNA expression patterns from specific brain nuclei.  ...  To visualize the clusters, we developed support for viewing genomic alignments of miRNA-Seq reads in the Chipster genome browser.  ...  Acknowledgments We thank Sari Hannula from FIMM Technology Centre for help in cluster generation and sequencing, the Biomedicum Genomics core facility for microarray hybridization, and Hovatta lab members  ... 
doi:10.1371/journal.pone.0021495 pmid:21731767 pmcid:PMC3120887 fatcat:sghfwurturdgrouyrdz2mjjpjq

On the Selection of Appropriate Proximity Measurement for Gene Expression Data

Md. Bipul Hossen
2017 International Journal of Biomedical Materials Research  
measures for the analysis of gene expression data.  ...  In the computational analysis of gene expression data, the main aspect is to finding co-expressed genes as the proximity (similarity or dissimilarity) measures that are used in the clustering method.  ...  effective as a similarity measure for gene expression data.  ... 
doi:10.11648/j.ijbmr.20170505.11 fatcat:c5jioc6id5gzzmp7yynuct43om
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