Gene expression profiling in osteoblast biology: bioinformatic tools.
This review focuses on using microarray data on a clonal osteoblast cell model to demonstrate how various current and future bioinformatic tools can be used to understand, at a more global or comprehensible level, how cells grow and differentiate. In this example, BMP2 was used to stimulate growth and differentiation of osteoblast to a mineralized matrix. A discussion is included on various methods for clustering gene expression data, statistical evaluation of data, and various new tools that can be used to derive deeper insight into a particular biological problem. How these tools can be obtained is also discussed. New tools for the biologists to compare their datasets with others, as well as examples of future bioinformatic tools that can be used for developing gene networks and pathways for a given set of data are included and discussed.
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Department of Oral Biology, University of Missouri at Kansas City, School of Dentistry, 64108, USA. harrisse@umkc.edu
Harris
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D000818:Animals; D055396:Bone Morphogenetic Protein 2; D019485:Bone Morphogenetic Proteins / Q000235:genetics / Q000494:pharmacology; D002454:Cell Differentiation / Q000235:genetics; D002455:Cell Division / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D016172:DNA Fingerprinting / Q000379:methods* / Q000639:trends; D005786:Gene Expression Regulation / Q000187:drug effects; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000639:trends; D010006:Osteoblasts / Q000166:cytology* / Q000378:metabolism*; D016212:Transforming Growth Factor beta
C525719:Bmp2 protein, mouse; D055396:Bone Morphogenetic Protein 2; D019485:Bone Morphogenetic Proteins; D016212:Transforming Growth Factor beta