. Decrease the amount of RNA needed. In many cases probe material is limiting the experiments. Smaller sample sizes will allow the study of histological samples and developmental studies. Presently, about 100 microgram of total RNA is required to day a micro-array experiments. Optimizing the hybridization process will substantially reduce the sample size. A calculation indicates that currently only a small percentage (less than 1%) of transcripts even have an opportunity to hybridize to their target. This could be increased to close to 100% by efficient mixing and reducing the total area of the micro-array. . Increase the reliability of measurements. Typically, micro-array experiments are compared to a control. The two are simultaneously hybridized to the micro-array, but labeled with different color fluorophores. Results are expressed as a ratio of the two measurements. When a gene is rarely expressed in the control, the ratio is often unreliable. By building a three color scanner, and using genomic DNA as an internal control, I will be able to make an independent measurement of the DNA content of each spot in the micro-array. This will allow cross- comparison of measurements over time and between laboratories. . Provide new tools to interpret the data. A single experiment can easily generate data on 5,000-40,000 different genes. Software is needed to provide an interface to the wealth of data collected. New methods of analysis must be developed to make sense of the data.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Career Transition Award (K22)
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Ethical, Legal, Social Implications Review Committee (GNOM)
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Graham, Bettie
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California Institute of Technology
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