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{bio,medical} informatics

Wednesday, May 24, 2000

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HMS Beagle Seeking a molecule's genetic potential
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"The selective estrogen receptor (ER) modulators (SERMs) tamoxifen and raloxifene act primarily as estrogen antagonists in the mammary glands, and are therefore used in the treatment of estrogen-responsive breast cancer. They also act as agonists in the bone and cardiovascular systems, making them candidates for estrogen replacement therapy. The authors sought to identify additional SERMs by using a method of differential gene expression modulation. They analyzed 24 combinations of genes and cells to come up with an assay that could discriminate between estrogen, tamoxifen, raloxifene, and the pure ER antagonist ICI164384. They then used it to measure the activity of 38 compounds. Next, they obtained fingerprint gene expression profiles (GEFs) and used them to classify each into one of eight categories. Most compounds with similar GEFs produced similar effects, which demonstrated the utility of GEF-based screens in predicting the pharmacological profile of a compound.

Reference: Zajchowski, D.A., Kauser, K., Zhu, D. et al. 2000. Identification of selective estrogen receptor modulators by their gene expression fingerprints. J. Biol. Chem. 275(21):15885-15894."

Weinstein Genomics and Bioinformatics Group A cDNA microarray gene expression database for the molecular pharmacology of cancer
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"We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines of the National Cancer Institute's drug discovery program...we link the bioinformatics with chemoinformatics by correlating gene expression and drug activity patterns in the 60 cell types. Clustering the cells on the basis of gene expression yields a picture very different from that obtained when the cells are clustered on the basis of their response to drugs. Gene-drug relationships for the important clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes can relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on gene expression and molecular pharmacology. "

Nature One-stop shop for microarray data
"With the advent of DNA microarray and 'chip' technologies...gene expression in an organism can be examined on a genomic scale, allowing the transcription levels of many genes to be measured simultaneously2. For instance, we can study the effects of a compound (such as a drug) on the level of expression of many genes...With gene expression, context is everything: without it, the information is meaningless. For example, the precise stage of a tumour sample could have a crucial bearing on the interpretation of expression measurements. This context can be infinitely detailed, and it is this detail that must be captured in gene-expression studies.

The bioinformatics underlying the management of these huge volumes of data are crucial if any sense is to be made of gene-expression experiments. A single microarray experiment looking at 40,000 genes from 10 different samples, under 20 different conditions, produces at least 8,000,000 pieces of information."

"It is time to create a public repository for microarray data, with standardized annotation (see Box 2, overleaf). But this is a complex and ambitious project, and is one of the biggest challenges that bioinformatics has yet faced. Major difficulties stem from the detail required to describe the conditions of an experiment, and the relative and imprecise nature of measurements of expression levels. The potentially huge volume of data only adds to these difficulties. However, it is this very complexity that makes an organized repository necessary.

Important tasks to be undertaken include: (1) agreement on the essential information that should be reported for a microarray experiment; (2) definition of ontologies and an extensible, structured document format to capture these data and their semantics; (3) production of a database to store these documents; and (4) development of tools for searching documents in a database and using the semantic context to allow comparisons and sophisticated queries."

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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