Successful research advances require dedication and commitment to the best use of the scientific method. Studies performed without a real understanding of the basis behind double blind testing produce inherently flawed results. When theoretical researchers do not have access to the information gained through actual testing, it slows the total development time.
The free flow of information is particularly important in medical research, where small mistakes cost lives. Research in genomics and proteomics shows promising results which may arrest neurological conditions, slow aging, improve overall health and eliminate cancer. Of course, those goals are years in the future, but without access to the latest and best quality data, researchers are hamstrung in the development process. Data analysis is a crucial part of pushing research boundaries and finding truly new avenues of research to pursue.
For many areas of science, researchers build on other known information. The study of DNA and genomes is a fairly young branch of science, meaning that there is relatively little factual information known about each sequence. Genetic mapping continues to give researchers insights into the specific functions of pieces of DNA and how they interact with proteins to determine physical characteristics. As a gene is mapped out and all facets become known, that information must be transmitted to current researchers as soon as it is available. The applications or genomics and proteomics are endless, making it crucial for research to be shared, rather than hoarded.
Data analysis pulls together data points from a variety of sources to provide a single unified picture of the specific item. Many research facilities may study the same gene sequence, but with different intentions. As each study collects data, that information can be put together to create a larger picture. A single gene sequence is so complex that years of study have failed to account for every aspect of any gene. The more information researchers have access to, the more progress they are able to make in their own specific avenue of study. Understanding human genetics leads to significant advances in prescription drug research as well.
With accurate data tracking, researchers are able to follow incidences of complications and reactions to specific drugs. They can then make comparisons of the patients, to find commonalities. Patients with similar genetic backgrounds often have similar reactions to prescription drugs. This in–depth knowledge of how genetics impacts drug interactions allows researchers to make changes specific for different ethnicities. Prescription drug research can now focus on providing targeted solutions for common medical conditions that provide better patient outcomes.
Not allowing researchers access to information about the results of trials, research methods used or results data limits their ability to make rapid discoveries. Research and development costs make up the bulk of the budget for many health companies. Prescription drug research takes years, with no guarantee of a product at the end of the expense. Quality data tracking and analysis helps more products reach the market more quickly and with fewer complications.
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