Bioinformatics as an integrated science field that use lots of science as a basic to solve problems, can help you achieving you goal in job and finding a job opportunity near or exact place of your goals.

In the world of scientific fields, bioinformatics can be purely academic or can be combined with other sciences and applied directly to industry. Most institute with prestigious biology programs are adding bioinformatics courses. Professors and researches study a wide variety of applications, tools and programming language for bioinformatics at universities. Studies range from computer simulations of organic reactions, to computer modeling of proteins and toxins, to simulations of populations and evolution. The application of technology to biology is so diverse that most of them cannot be covered here.

In industry, bioinformatics is revolutionizing many industries. Such as the agricultural industry for example. It has taken botanists and farmers centuries to develop the crops we have today. They have previously done this by meticulously analyzing the crop, selecting varieties that faired the best, and reproducing only the best. Now, with bioinformatics technology, computers can be trained to analyze the genome of particular plants, track millions of plants at a time, and predict which plants will be the best. Revolutions in artificial intelligence will aid and speed this process. The same sorts of benefits are being seen by many industries.

The pharmaceutical industry relies heavily on bioinformatics. Not only do they need people to analyze and develop current drugs, but they need next level thinkers who can develop methods and software to predict the reactions certain drugs would cost. As computing power increases, the number and kinds of reactions which can be modeled increases dramatically. This could mean the end of animal testing and a new age of informed drug making. Other medical professions, including everything from doctors to biomedical device creators, are also embracing technology. Patient care in hospitals in now tracked through methods developed in bioinformatics, and can greatly improve the monitoring provided by doctors and hospitals. Many advanced imaging procedures and electrical activity tests of the heart and brain require analysis through computers because of their complex nature.

One of the first professions to employ bioinformatics, epidemiology, still uses technology as much as possible today. The recognition and identification of many patterns of common diseases would still be a mystery if not for computer modeling. Using computers and data gathered in the field, epidemiologists work to understand disease outbreaks and how we can reduce our exposure to communicable diseases. Various software is designed to do everything from track the geographic location of outbreaks, to assessing possible risk factors for disease, all the way to tracking the organisms which cause disease and monitoring how they evolve. This is done by the makers of the flu vaccine, who every year adjust their formula based on the expected mutations to the influenza virus. Bioinformatics provides the basis for these estimations.

Along the same lines, many population biologists track changes in a population over time using computers and specialized software. While this used to mean a scientist entered their observations into a spreadsheet and made a graph, it is now much more advanced. Scientists can measure and observe individual changes to a genome over time in a population using the advanced processing power of computers. While macro evolution may take millions of years, micro evolution happens every generation and scientists have now documented that with help from bioinformatics. On a larger scale, climate scientists use bioinformatics to make large calculations about the impact certain organism have on the environment. Thanks to bioinformatics analysis, we now know that a large majority of the oxygen we rely on comes from algae in the ocean. This science will keep increasing as technology advances and we are able to create more advanced models and process and collect more data.

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