How The Common Consensus Framework Could Help Bring Personalized Medicine to Real World

“All Your Base Are Belong To Us,” by Kevin Mitnick, a recent online article in Popular Science listed Bio-defense Application of PLOS Computational Biology Impact Factor

Mitnick asserts that computing modeling is reducing biological research to a science of computing and biology is moving toward information analysis, data mining, and personalized medicine, which means there is a higher probability writing expert of accurate genetic testing, personalized medicine, personalized genomics, personalized nutrition, personalized biotechnology, personalized medicine based on personalized genetics.

To continue the good things said in the article, we’ll just quote this part. He claims:

“Using computer software, genomics research will be able to increase its efficiency. Many current computational biology tools are not all that efficient.” In other words, if researchers are only using a fraction of their computing power for the generation expert writers of DNA data, it’s doubtful that they’ll have much of a work force. He believes that if more computing power is used in genomics research, more scientists will be able to do more work.

As far as I know, Plos Computational Biology Impact Factor was never mentioned. At first, I did check out the plo’s website but couldn’t find anything like that, so I assumed he had misspelled it. However, it may have been edited to reflect the content of the article.

Anyway, let’s observe how a number of people available knew from Popular Science concerning this informative article – why don’t? Therefore, I have a notion – please place the link from the comments beneath, if you know of anyone who did!

I recall being educated in a conference https://en.wikipedia.org/wiki/Species the moment by some one who functions together the Common Consensus frame-work their schooling and collaboration have served them better understand how to use the diversity and complexity of biodiversity. He explained he considered this method can help individuals make educated decisions regarding what things to do global healthcare. There were the others found that voiced similar thoughts.

What could monitor applications do in terms of assessing and analyzing statistics and forecasts for wellbeing? It is clear it may and ought to be used for generating personal genomic medicine alternatives and empowering treatment and prediction of genetic disorders.

If the very first rung on the ladder into this achievement of any research endeavor would be always to have enough information then we have really succeeded, because we’ve this information. We need more of it, and more of this can be found by way of genomics – just one manner or another.

A second step to the success of a plan for personalized medicine is to find out the individual genetic ‘preferences’ or genetic endowments of patients with disease. This could involve identifying biological and environmental factors that interact to influence a patient’s susceptibility to disease. These factors are called ‘gene-environment interactions’ (GIE) and are known to be heterogeneous in the context of human genetics and disease, and in the future may be used to find the molecular constituents that vary between individuals to make personalized medicine.

If we want to talk about a third step towards personalized medicine, then we could also use computational software, in combination with genomic data from individual genetic profiles, to predict or ‘program’ the molecular responses of the cells to environmental stresses. For example, it could identify genes that are involved in the production of reactive oxygen species and other oxidative stress-related molecules that are observed in and around cancer tumors and/or on the tissues of such tumors.

Another step towards personalized medicine is to develop new high-tech software programs for health monitoring. It is just a question of time before we have this kind of program, which will integrate the best available genomic data with recent technologies in computing power and knowledge, bioinformatics and the computer modelling systems.

These are just some of the steps that can be taken to understand the proper biochemistry and molecular signalling in combination with real-time health monitoring and personalized medicine. By all the metrics of tomorrow’s future, we are definitely closer to that goal than we may think.

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