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Our Evolving Science

Sometimes, I’m totally astounded at how much our science has advanced since my days as a graduate student. Back then, the closest anyone got to “genomic” studies of eukaryotic organisms involved “melting” DNA and watching it come back together using CoT curves. Cloning and sequencing a single cDNA could get you a paper in Science or even (if it was especially important) Nature. As a classically trained molecular biologist, I was used to thinking about single genes. We ran northern blots and probed them with single cDNA probes. On a good day, our sequencing gels could resolve up to 300 nucleotides, maybe a few more if you did multiple loadings. Experiments were labor-intensive and not very quantitative. While we could generate some very pretty pictures, we certainly couldn’t do statistics. Back then, our science was limited by a lack of data.

Since that remote time (half-way back to the Pleistocene, as my kids would say), we have made incredible progress. We have sequenced the genomes of a growing list of diverse organisms. We can quantitatively assess the expression of not just one gene, but of every gene in an organism, all at the same time. We can ask global questions that we could never have asked just a few short years ago, and we can get answers to those questions in a relatively short period of time. In fact, today we have the opposite problem: far too much data! We used to spend months or even years gathering a few crucial data points that could be assessed by a mere glance at an autoradiogram. Today, we can do an experiment in a fraction of the time, but the analysis takes so much longer. Fortunately, our tools and skills are evolving along with our science.

The initial release of JMP Genomics in 2006 married the visualization capabilities and ease of use of JMP software with the power of SAS. It offered researchers more than 100 different processes for importing, manipulating and analyzing the vast amounts of data generated by the new technologies. The recent release of JMP Genomics 4.0, builds on an already strong platform of data management and analysis tools. We have added features to and enhanced the power of all of the existing processes. In addition, we have added 16 totally new processes. In fact, this latest release contains almost 200 different processes for importing, assessing, normalizing, annotating, and exploring genetic and microarray data. Every process is fully documented and available for you to use as is or to adapt to your particular needs. You can modify existing processes and workflows or build new ones and add them to your menus. In addition, if there is something special that you need, just let us know, and we’ll work with you to build it. As always, we remain committed to helping you meet your research goals.

We have come so far in such a short time. Where will our science go next? You will help decide, and JMP Genomics will help you take us there. We’re already hard at work on our next release. Stay tuned. The best is yet to come.

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