Microarray Informatics Resource Page

Under construction!

Literature

• Yuk Fai, Leung's functional genomics journal watch
• Introduction to microarray technology
  • M. Schena (editor): Microarray Biochip Technolog, Eaton publishing 2000
  • M. Schena (editor): DNA Microarrays: A Practical Approach, Oxford University Press 1999
  • Geschwind and Gregg (edotrs): Microarrays for the Neurosciences, MIT Press 2002
  • The chipping forecast from Nature Genetics
• Surveys and introductory papers on informatics aspects
  • A Brazma, J Vilo. 2000. Gene expression data analysis FEBS letters 480, 17-24.
  • R Brent. 1999. Functional genomics: learning to think about gene expression data. Current Biology 9:R338-R341.
  • J-M Claverie. 1999. Computational methods for the identification of differential and coordinated gene expression. Human Molecular Genetics 8, 1821-1832.
  • G Sherlock. 2000. Analysis of large-scale gene expression data. Current opinion in Immunology 12, 201-205.
  • Martin Vingron, Jörg Hoheisel. 1999. Computational aspects of expression data. J Mol Med 77, 3-7
  • MQ Zhang. 1999. Large-scale gene expression data analysis: a new challenge to computational biologists. Genome Research 9, 681-688.
  • G Zweiger. 1999. Knowledge discovery in gene-expression microarray data: mining the information output of the genome. TIBTECH 17, 429-436.
• Replication, normalization etc.
  • B Eickhoff, B Korn, M Schick, A Poustka, J van der Bosch. 1999. Normalization of array hybridization experiments in differential gene expression analysis. NAR 27, e33.
  • M-L T Lee, FC Kuo, GA Wihtmore, J Sklar. 2000. Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations. PNAS 97 (18) 9834-9839.
  • J Schuchhardt, D Beule, A Malik, E Wolski, H Eickhoff, H Lehrach, H Herzel. 2000. Normalization strategies for cDNA microarrays. Nucleic Acids Research 28, e47.
  • Cheng Li and Wing Hung Wong. 2001. Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection. PNAS 98, 31-36.
• Analysis of differential expression
• Clustering and unsupervised learning methods
  • B Dysvik, I Jonassen. 2000. J-Express: An interactive Java based tool for exploration of gene expression data. Bioinformatics, in press.
  • G Getz, E Levine, E Domany, MQ Zhang. 1999. Super-paramagnetic clustering o fyeast gene expression profiles. Preprint submitted to Elsevier Science 14 nov 1999.
  • P D'haeseleer, X Wen, S Fuhrman, R Somogyi. 1998. Mining the gene expression matrix: inferring gene reationships from large scale gene expression data. Inf Proc in Cells and Tissues 203-212.
  • LJ Heyer, S Kruglyak, S Yooseph. 1999. Exploring expression data: identification and analysis of coexpressed genes. Genome Research 9, 1106-1115.
  • P Tamayo, D Slonim, J Mesirov, Q Zhum S Kitareewan, E Dmitrovsky, ES Lander, TR Golub. 1999. Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. PNAS 96, 2907-2912.
  • R Tibshirani, T Hastie, M Eisen, D Ross, D Botstein, P Brown. 1999. Clustering methods for the analysis of DNA microarray data. Stanford University Oct 15, 1999.
  • P Toronen, M Koleehmainen, G Wong, E Castren. 1999. Analysis of gene expression data using self-organizing maps. FEBS 451, 142-146.
  • LE Peterson Factor Analysis of Cluster-specific Gene Expression Levels From cDNA Microarrays. Computer Methods and Programs in Biomedicine (in press). Web supplement including CLUSFAVOR program
• Supervised learning methods
  • MPS Brown WN Grundy, D Lin, N Cristianini, CW Sugnet, TS Furey, M Ares, D Haussler. 2000. Knowledge-based analysis of microarray gene expression data by using support vector machines. PNAS 97, 262-267.
• Discovery of regulatory signals using gene expression data
  • A. Brazma, I. Jonassen, J. Vilo, E. Ukkonen. 1998. Prediction of Regulatory Elements in Silico on a Genomic Scale Genome Research 8, 1202-1215.
  • J. Vilo, A. Brazma, I. Jonassen, A. Robinson, E. Ukkonen. 2000. Mining for putative regulatory elements in the yeast genome using gene expression data. Proceedings of the eighth internaional conference on intelligent systems for molecular biology, ISMB2000, AAAI Press, 384-394.
  • FP Roth, JD Hughes, PW Estep, GM Church. 1998. Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantification. Nature Biotechnology 16, 939-945.
  • S Tavazoie, JD Hughes, MJ Campbell, RJ Cho, GM Church. 1999. Systematic determination of genetic network architecture. Nature Genetics 22, 281-285.
  • J van Helden, Mli del Olmo, JE Perez-Ortin. 2000. Statistical analysis of yeast genomic downstream sequences reveals putative polyadenylation signals. NAR 28, no 4.
• Representation and reverse engineering of regulatory networks
  • Sessions at Pacific Symposium on Bioinformatics:1998, 1999, 2000
  • Gene Regulation Networks - a Finite State Linear Model slide presentation by Alvis Brazma, the EBI.
  • T. Akutsu, S. Miyano, and S. Kuhara. 1999. Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model, Pacific Symposium on Biocomputing 4:17-28.
  • A. J. Butte, I. S. Kohane. 2000. Mutual information relevance networks: Functional genomic clustering using pairwise entropy measurements. Pacific Symposium on Bioinformatics 2000.
  • B Dutilh. 1999. Gene Networks from Microarray Data. Literature thesis, Utrecht University
  • P D'Haeseleer, S. Liang, R. Somogyi. 2000. Genetic Network Inference: From Co-expression clustering to reverse engineering. Bioinformatics: in press.
  • P D'haeseleer, S. Liang, R. Somogyi. 1999. Gene Expression Analysis and Genetic Network Modeling. Tutorial session at Pacific Symposium on Bioinformatics 1999.
  • P D'haeseleer, S. Fuhrman. 2000. Gene network inference using a linear, additive regulation model. submitted to Bioinformatics.
  • S Huang. 1999. Gene expression profiling, genetic networks and cellular states: an integrating concept for tumorigenesis and drug discovery. J Mol Med 77, 469-480.
  • H de Jong, M Page. 2000. Qualitative simulation of lage and complex genetic regulatory systems. Proc of ECAI 2000, IOS Press.
  • P Smolen, DA Baxter, JH Byrne. 2000. Modelling transcriptional control in gene networks - methods, recent results, and future directions. Bulletin of Math. Biol. 62, 247-292.
  • M. Wahde, J. Hertz. 2000. Coarse-grained reverse engineering of genetic regulatory networks. BioSystems 55, 129-136.
  • D.C. Weaver, C.T. Workman, G.D. Stormo. 1999. Modeling Regulatory Networks with Weight Matrices, Pacific Symposium on Biocomputing 4:112-123.
• Applications
  • AA Alizadeh, et al. 2000. Distinct types of idffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503-511.
  • U Alon, N barkai, DA Notterman, K Gish, S Ybarra, D Mack, AJ Levine. 1999. Broad patterns of gene expression revealed by clustering analysis of tumour and normal colon tissues probed by oligonucleotide arrays. PNAS 96, 6745-6750.
  • JL DeRisi, VR Iyer, PO Brown. 1997. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278, 680-686.
  • TL Ferea, D Botstein, PO Brown, FR Rosezweig. 1999. Systematic changes in gene expression patterns following adaptive evolution in yeast. PNAS 96, 9721-9726.
  • CJ Roberts, B Nelson, MJ Marton, R Stoughton, MR Meyer, HA Bennett, YD He, H Dai, WL Walker, TR Hughes, M Tyers, C Boone, SH Friend. 2000. Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles. Science 287, 873-880.
  • PT Spellman, G Sherlock, MQ Zhang, VR Iyer, K Anders, MB Eisen PO Brown, D Botstein, B Futcher. 1998. Mol Biol Cell 9, 3273-3297.

Microarray Labs

• The Brown Lab, including Build your own arrayer
• NHGRI Microarry Project

Databases

• LIMS
  • UCspots
• Microarray databases on the web - collection
• Gene Expression Databases and Analytical Tools - colletion
• ArrayExpress, from EBI
• maxdSQL, SQL implementation of ArrayExpress (EBI), implementation by microarray group at Manchester University
• ChipDB, from Young lab
• AMAD, Another Microarray Database, flat file database
• GEO, Gene Expression Omnibus from NCBI
• Stanford Microarray Database, on-line access to datasets from Stanford
• ExpressDB from the Church Lab, Harvard
• GeneX, database with integrated tools from UC Irvine.
• MAT, Microarray Analysis Tools, Java applet with database access and tools for data mining and visualisation
• ArrayDB, relational database with Java applets and scripts for queryin and visualisation
• RAD, RNA Abundance Database from U Penn Center for bioinformatics

Software

• J-Express available from MolMine.com, trial version free for anybody
• VERA and SAM from Institute of Systems Biology

Public datasets

Link collections

• DNA Microarray (Genome Chip) - comprehensive and well organized collection.
• Large-Scale Gene Expression and Microarray Links and Resources, collected by Alan Robinson, EBI.
• Microarray based gene expression measurements, public data repositories collected by Alvis Brazma, EBI.
• Grid it, resources for microarray research