Better DNA Microarray Analysis

It monitors the behavior of thousands of genes over time by detecting changes in the expression of as many as 30,000 different genes on one small chip. The technique has been used to study some of the most important biologic systems, including how cells divide and immune responses to disease and infection.

The new procedure is based on a "check-sum” protocol initially developed to ensure that e-mail messages did not become garbled in transmission. In standard Internet protocol, bits of information that begin as one value (0 or 1) may flip to the opposite value as they move from one computer to the next via e-mail. This data loss is checked by counting the number of ones in the message. If this number is odd, then the last bit is set to one; otherwise, it is set to zero. By comparing the last bit on the receiving end, the recipient's computer can tell whether the message was accurately received. If not, the recipient's computer asks the sender's computer to forward the message again.

The new DNA microarray method carries out a similar analysis of the microarray snapshots by checking the sum of a set of DNA microarray data points over time against the summary of the temporal response. If the two sets of results are equal, then what is captured by the microarray time series is real. If the time series results produce a lower value than the microarray summary, the protocol indicates that the researchers have missed a gene's activation somewhere in their time series.

Just as important is whether a DNA microarray summary value exceeds its time sequence value. If that happens, then researchers have likely identified gene activity that should be attributed to changes taking place during an experiment, such as adding a chemical or changing the temperature. This part of the method provides the specificity required to weed out such introduced gene activation from gene activation pathways that form the hallmark of processes such as cancer or immunity.

The new DNA microarray method was developed by Ziv Bar-Joseph, assistant professor of computer science and biologic sciences at Carnegie Mellon University (Pittsburgh, PA, USA), together with collaborators at the Hebrew University (Jerusalem, Israel). Their work was described in the December 2005 issue of Nature Biotechnology.

To prove the effectiveness of their method, Dr. Bar-Joseph studied the human cell division cycle, which plays a major role in cancer. He and his colleagues identified many new human genes that were not previously found to be participants in this system. The new method also overcomes synchronization loss, which occurs as groups of cells become asynchronized in their activities.

"We are very excited about introducing this versatile, powerful method to the research community because it can be used to study a wide range of complex, dynamic systems more comprehensively,” observed Dr. Bar-Joseph. "Such systems under study include stress and drug response, cancer, and embryo development.”




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Carnegie Mellon U.