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of software, databases, and other products to support the analysis of genetic information. The first component of their activities is a large database called LiveSeq that contains more than 3 million human-gene sequences and expression records. Clients of the company buy a subscription to the database and receive monthly updates that include all of the new sequences identified since the last update. All of these sequences can be considered as candidate genes that might be important for future genome mapping. This information has been derived from DNA sequencing and bioanalysis of gene fragments extracted from cell and tissue samples. The tissue libraries contain different types of tissues including normal and diseased tissues, which are very important for comparison and analyses.

To help impose a conceptual structure of the massive amount of information contained in LifeSeq, the data has been coded and linked to several levels. Therefore, DNA sequences can be grouped into many different categories, depending on the level of generalization. LifeSeq has been organized to permit comparisons of classes of sequence information within a hypothesis-testing mode. For example, a researcher could compare gene sequences isolated from diseased and non-diseased tissue from an organ. One of the most important tools that are provided in LifeSeq is a measure of similarity among sequences that are derived from specific sources. If there is a difference between two tissue groups for any available sequences, this might indicate that these sequences should be explored more fully. Sequences occurring more frequently in the diseased sample might reflect genetic factors in the disease process. On the other hand, sequences occurring more frequently in the non-diseased sample might indicate mechanisms that protect the body from the disease.

Although it has proved invaluable to the company and their clients in its current incarnation, additional features are being planned and implemented to extend the LifeSeq functionality into research areas such as

identifying co-occurring gene sequences,

tying genes to disease stage, and

using LifeSeq to predict molecular toxicology.

Although the LifeSeq database is an invaluable research resource, queries to the database often produce very large data sets that are difficult to analyze in text format. For this reason, Incyte developed the LifeSeq 3-D application that provides visualization of data sets, and also allows users to cluster or classify and display information about genes. The 3-D version has been developed using the Silicon Graphics MineSet tool. This version has customized functions that let researchers explore data from LifeSeq and discover novel genes within the context of targeted protein functions and tissue types.

Maine Medical Center (USA)

Maine Medical Center—a teaching hospital and the major community hospital for the Portland, Maine, area—has been named in the U.S. News and World Report Best Hospitals list twice in orthopedics and heart care. In order to improve quality of patient care in measurable ways, Maine Medical Center has used scorecards as key performance indicators. Using SAS, the hospital creates balanced scorecards that measure everything from staff hand washing compliance to whether a congestive heart patient is actually offered a flu vaccination. One hundred percent of heart failure patients are getting quality care as benchmarked by national organizations, and a medication error reduction process has improved by 35%.

http://www.sas.com/success/mainemedicalcenter.html

In November 2009, the Central Maine Medical Group (CMMG) announced the launch of a prevention and screening campaign called “Saving Lives Through Evidence-Based Medicine.” The new initiative is employed to redesign the ways that it works as a team of providers to make certain that each of our patients undergoes the necessary screening tests identified by the current medical literature using data-mining techniques. In particular, data-mining process identifies someone at risk for an undetected health