• Role of Bioinformatics Databases in Research on Medicinal, Aromatic and Economical Plants
Dr. Mohammed Ali, Assistant Professor of Crop Genetic and Breeding at Plant Genetic Resources Department, Ecology and Dry Lands Agricultural Division. Desert Research Center (DRC), Egypt.
Data mining for genomics, transcriptomics and proteomics belongs to an interdisciplinary and relatively new field of bioinformatics, which evolves so rapidly that it is difficult to predict the extent and pace of the changes. Biology, or more generally life sciences, can now be considered information sciences. They are changing from disciplines that deal with relatively small data sets to research fields overwhelmed by a large number of huge data sets. Today, hardly any study involving high throughput gene or protein expression data is performed exclusively by biologists or biochemical scientists. Although few research groups realize the importance of including data miners in their studies, the role of a relatively new breed of scientists called bioinformaticians is indisputable. The bioinformaticians are not necessarily data miners, although data mining should be one of their required skills. There is a small but growing population of scientists who were majoring in bioinformatics. However, most of the experienced bioinformaticians are still either biologists who learned computer science and statistics, or computer scientists familiar with biology. The interdisciplinary nature of this field is expansive and involves many other disciplines, like physiology, clinical sciences, mathematics, physics, and chemistry. So in this lecture we define data mining as the efficient ways of extracting new information or new knowledge from large data sets or databases. Some more classical definitions limit data mining to extraction of ‘useful information.’ However, in biotechnology and biochemical research any new information reflecting underlying biological processes can be potentially useful. Furthermore, translating the extracted new information into new biotechnology knowledge is often a nontrivial task and the data mining definition (and methods) should be extended as well to include the information-to-knowledge stage of investigations.
