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Editorial

Myths about Bioinformatics

Bioinformatics Review
Last updated: May 20, 2020 5:47 pm
Bioinformatics Review
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Bioinformatics is rapidly growing since the last few decades and has revolutionized biological research. Researchers are capable of developing therapeutic drugs efficiently, capable of getting rapid results, easy to generate predictions to be tested in an experimental lab, and it has broad applications in the future. However, alongside the increasing applications of the bioinformatics field, some myths have also arisen about it. 

Myth 1. “Bioinformatics is just about pushing buttons!”

Some biologists think that bioinformatics is all about pushing buttons and generating results. This, in fact, is not true. Firstly, bioinformatics experiments need the as same attention as the other experiments performed by experimental biologists. Bioinformaticians have to keep in mind each and every detail before performing any experiment or run the software. There are several default settings in the bioinformatics software which they have to understand in detail before starting any kind of analysis because these parameters affect the final results.

Myth 2. “Anybody can do this!”

As mentioned in the above myth, bioinformaticians don’t just push buttons all day. Bioinformaticians study, think, and analyze their data. Additionally, there are different kinds of methods/algorithms based on which bioinformatics software are developed. So, they have to closely analyze the software to select the best-suited one for their data. In the other scenario, when there is no such software available to fulfill the requirements of their own or the experimental biologists, bioinformaticists have to develop one.

Myth 3.  “Bioinformatics costs nothing!”

The general opinion about bioinformatics is that it is inexpensive. This is only true in the case of pharmaceutical research, where it helps in reducing the cost of drug development by selecting, identifying, designing, and testing drugs/protein activity. The truth is that bioinformatics is an expensive field of study. It is not just a biological field without any laboratory consumables. In fact, the cost associated with professional bioinformatics software development is high. It requires properly established workstations having a properly structured disk space and a large number of high speeding CPUs. The cost of activities increases exponentially as the following data. Generally, all these requirements are not fulfilled in every lab environment.

Myth 4. “Molecular Dynamics (MD) simulation is all about using commands and get the result!”

MD simulation is not an easy task. However, it may seem so to some experimental biologists as it requires a bioinformatics software and a series of commands associated with it. This is not true. Performing MD simulation does need software and commands to simulate a protein in an environment (temperature and pH). But at first, bioinformaticians have to study the protein in detail to know about its activities and behavior. Secondly, they have to select appropriate algorithms and parameters to get significant results. Even after getting results in the form of graphs/plots, they have to closely analyze them to know the effects on the protein. This, however, is also true in the case of other bioinformatics studies such as evolution, protein modeling, and so on.

Myth 5. “Bioinformatics is all about molecular docking and simulation!”

Bioinformaticians do not only know molecular docking and simulation. They also have a vast knowledge of other techniques as well. These might be the most applicable techniques of bioinformatics but this field is way beyond that.

Myth 6. “Bioinformatics is all about predictions!”

This is a phrase I have heard often that “bioinformatics is all about predictions”. We have also published an article regarding this earlier. This is a false narrative. Bioinformatics involves the predictions and simulations but it is not just all about that. There are real-world applications too. Predictions are made in the case of hypotheses which is not just the case with bioinformatics only. It is applicable to other fields as well as physics and chemistry.

 

 

 

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