Interpreting microarray data: towards the complete bioinformatics toolkit for cancer.
Functional genomics has been applied in the study of human malignancies since the inception of this field nearly a decade ago. Microarray analysis has been specifically used in an attempt to re-classify carcinomas at the molecular level, to aid in diagnosis/prognosis and to predict how various types of tumour respond to different therapeutic agents. Bioinformatics is now at the forefront of the post-genomics era and is providing a number of tools with which to mine the large datasets produced by genome-wide analysis. Of particular importance is the emergence of techniques that give the ability to reveal the transcription regulatory networks that are active in the cell in response to environmental stimuli or disease states. Deciphering the transcription networks that function in malignant cells not only will provide the knowledge to understand how carcinomas progress, but would also allow the construction of useful therapeutic tools for their effective treatment. In this review the recent advances that have been made in functional genomics that allow microarray data to be more fully interpreted and reveal the transcription networks that have gone awry in transformed cells are described.
Roberts
Michael L
ML
Regulon A.E., Afxentiou 7, Athens 11525, Greece. michael@regulon.org
Kottaridis
Stavros D
SD
D019295:Computational Biology / Q000295:instrumentation* / Q000379:methods; D004273:DNA, Neoplasm / Q000235:genetics*; D030562:Databases, Protein; D023281:Genomics; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D014157:Transcription Factors / Q000235:genetics; D014158:Transcription, Genetic
D004273:DNA, Neoplasm; D014157:Transcription Factors