The invention of DNA chips revolutionized the ability of researchers to analyze changes in genes. However, a team of researchers from the Salk Institute, who intended to create a molecular map of the mouse brain, encountered a problem: the amount of information collected was much greater than they could manage and analyze with the means available at the time in the research institute's laboratories.
Micah Rosen

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Dr. Karoli Barlow, loves mice. She is surrounded by them every day, hour by hour, as part of her work at the Salk Institute, one of the most well-known research medical institutions in the world. According to Dr. Barlow, who specializes in molecular analysis of disorders related to the activity of the human brain, the use of mice actually, It follows that it is easy for researchers of her kind to identify and make changes to the identical genes in mice and humans. "Genetically, and to a certain extent physiologically, we are not that different from the common mouse. I can identify a genetic mutation in a person, create an identical mutation in a mouse, 'engineer' from that mouse a whole group of mice with the same mutation and from there the way is open for analysis and research." To implement her research, Dr. Barlow performs analyzes based on the sequence of the 3 billion chemical bonds that make up human DNA. And that's a lot of calculations.
Until recently, Dr. Barlow and her fellow professionals were limited by the amount of information they could process and produce. The situation changed with the introduction of DNA chips, which are composed of combinations of nucleic acids and allow the activity associated with a single gene to be checked with great precision. Before the era of DNA chips The analysis could be performed, but it was limited to one gene at a time. Today, 12000 genes can be analyzed at once Before Dr. Barlow and her friends, he led her to try to create a molecular map of the mouse brain. The study was joined by Dr. David Lockhart, a leading researcher in the field of genomics, and Matthew Zappala. The common goal: to collect all the data in a database format that could be used by the entire scientific community. And this is where the team encountered a problem: the amount of information collected was much greater than they could manage and analyze with the available means At that time in the laboratories of the research institute.
The solution was soon found in the form of an organizational data warehouse, when the task was to create a platform through which information could not only be stored, but also, above all, one that would allow researchers to 'enrich' algorithms within the database itself.
Quite a few large organizations and businesses around the world implement data warehouse systems (DataWarehouse). A data warehouse is a particularly large repository of various types of detailed data held by the organization, collected by the organization in the course of its ongoing work, over a period of time. Data collection is done within the normal operational systems of the organization. The collected data is regularly transferred to the data warehouse (a combination of powerful hardware and dedicated software) and stored there in its individual form, that is: not in a summarized form, and this in order not to lose information. In a data warehouse built with appropriate technology, this data is edited in a way that reflects reality in a real way and allows it to be analyzed quickly - even when the amount of data in the warehouse is very large. This possibility of handling large amounts of detailed data is of great importance, since the more the analysis is done on a larger amount of detailed data, the more reliable the results of the analysis increase. Due to the nature of such analysis work, the data warehouse must also be built with technology that allows the execution of queries that are not only pre-planned, that is: before starting the data analysis. There may certainly be situations in which some stage of the analysis will lead to the conclusion that the analysis must be continued by a query that was not observed in advance - but only after observing the results of an earlier stage of the analysis.
After examining a number of solution providers and encountering raised eyebrows and a great deal of skepticism regarding the ability to handle the project, Dr. Barlow arrived at Teradata, the data warehouse division of NCR. "The benefits of using a data warehouse capable of high-level parallel processing were immediate," says Dr. Barlow. "In most cases, the queries sent by researchers are ad hoc queries, as they examine the data during a 'hunt' for genes that cause or prevent certain diseases. The questions are not always known in advance. Moreover, the use of Teradata allowed the researchers to make regular use of all the data collected in the genomic experiments, which were sometimes expressed in about 400000 different measurements, which sometimes have to be compared with measurements from other experiments."
"The use of the data warehouse jumped the research team several steps forward," says Dr. Lockhart. "Now we can distinguish changes in genes between healthy and diseased tissues. Our researchers now spend 3 hours in front of the computer instead of 3 months, as it was before. The use of the data warehouse can affect the lives of millions around the world and the story of how this genetic research institution began to use the platform, which is usually associated with business analysis, is fascinating."
* The writer is a manager of selected clients and an expert in the fields of data warehouses at the company Y.A. Mittovach and Sons, NCR representative
For information on the Terra-Data website
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