What is it ?
In short, bioinformatics is an interdisciplinary skill-set that combines computer science and mathematics with the various flavors of biological sciences, ranging from genetics, microbiology and ecology, to epidemiology and pharmacology.
Young field in turmoil, innovative, hybrid and dynamic!!
A window to the future
We have entered an era of unprecedented progress in the biological and biomedical sciences. The recent reports on the human genome sequence have received most public interest and have brought into focus the vast opportunities now open to identify and characterize genes. But the human genome is by no means the only genome that has been determined. The genomes of fruit fly, flatworm, thale cress, baker’s yeast and other single-celled eukaryotes, numerous bacteria and archaebacteria, as well as of mitochondria and chloroplasts that are comprised in the eukaryotic cell have also been sequenced entirely.
Because many of the genes that participate in the processes of human cells are also found in organisms that are easier to study, much can be learned about how our cells work by comparison to these simpler systems. In addition to sequence data, genome-wide gene function data are becoming available for a number of organisms. These include data on gene expression, protein-protein interactions and gene ablation (or knock-out).
* How can we analyze the data from large-scale, genome-wide experiments and interpret them in terms of biological function?
* What do we need to know in order to design such experiments in the most rational way?
What does it deal with ?
First, there are the obvious questions that bear on the extraction of meaningful information from huge data sets. For example, specialized bioinformatics tools allow us to reconstruct the evolutionary history and trends that have shaped today’s genomes on the basis of a broad sampling of genome sequence data. Likewise, the two-dimensional structure of RNA molecules can be predicted and complex epidemiological data can, when organized and categorized in an structured way, make possible systematic analyses of cause and effect.
Questions in biology can be addressed by studying how things work today, as well as asking how they evolved. Comparisons of networks of interacting genes, how they function and how they have evolved different functions during evolution, provide the broad understanding needed to describe how organisms work today.
But bioinformatics can also address questions at a much more general level. For example, are there defined and efficient principles or are living cells like “Rube Goldberg” devices, that is, the most complicated machineries possible to perform simple tasks? What we know today would suggest the later over the former. Biochemical networks (e.g. chemotactic signaling pathways) seem to have developed once and then diversified to take on new functions. These networks are robust on small time scales, but variable on evolutionary time scales. Further, progressive evolutionary selection of increasingly favorable outcomes seems to occur by repeated cycles of selection. Examples of such behavior include protein folding, assembly of the chromosome segregation machinery, chemotaxis, nervous systems, and evolution of organisms.