How to Code a Genetic Algorithm For the Human Genome Project

When I was a student I loved looking at genetic algorithms and trying to solve them. It seemed very complicated but it took a while to work out. I liked the subject and always wanted to know how to code a genetic algorithm for the travelling salesman. The one thing I realized is that no one had put all the pieces together. I had no idea how it worked but I could figure it out if I could get enough information.

Now, thanks to Internet and technology it’s so easy to get the information you need. The internet is packed full of information about all sorts of subjects. In the computer industry especially things like genetic algorithms and programming have become very popular. There are many books out there on these topics. For the most part they teach you how to use genetic algorithms with a basic software program. You might even be able to get a short course on programming genetic algorithms.


I’m going to cover what a genetic algorithm is in this article. A genetic algorithm is a mathematical model that shows how certain environments can alter the expression of certain genes in organisms. Most of the time, an environment causes a slight variation in the expression of the gene it was designed to function with. It then produces an offspring by inheriting traits from its parents.


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Let me give you a real life example of how to code a genetic algorithm. Lets say we have this simple genetic disease called Huntington’s Disease. The gene we want to work on is called gapped DNA. It stands for the very area where two strands cross over. The problem with this genetic disease is whenever there is any damage done to the DNA, it produces a faulty cell.


Let’s say there was an effective gene therapy treatment developed for this particular genetic disease. The treatment was using a form of DNA therapy called transcribed RNA (or RNA). This form of DNA was taken from the patient’s own blood and injected into the patient through an incision in their back. The tv RNA traveled down the inheritance ladder and became the genetic disease free copy of DNA in the new place.


This was the beginning of the end for the genetic disease Huntington’s. This form of gene therapy was the first successful application of genetic algorithms. Today there are many other genetic diseases that use genetic algorithms. As I mentioned earlier, there are genetic diseases that are still waiting for the correct application of the gene therapy treatments.


These genetic algorithms and the DNA used to implement them are being used in many clinical trials to find a cure for certain medical conditions. Some of these genetic algorithms are even being tested for use in preventing and slowing the development of certain diseases. It is my contention that if we can solve the problems associated with most common genetic diseases, then we have the potential to solve many more complex problems as well. Thus, we have the potential to solve the problem on how to code a genetic algorithm for the Human genome project in the near future.


Perhaps the most amazing part of how to code a genetic algorithm for the Human genome project is that the Human genome project may just be the key to solving the world’s health problems. In fact, at least one company has already raised millions of dollars based upon the promise of finding a cure for all diseases. However, it is also very important to understand that solving the problems associated with genetic disorders will take time. Hopefully, after the completion of the Human genome project, there will be many researchers around the world solving other complex problems in the future.