Let’s assume we have a species of bacteria that is part of the normal millions of ‘good’ bacteria living on and inside healthy human beings; we’ll call this Bacteria X.0. One day Bacteria X started making people very ill. What happened to Bacteria X.0 to make it become the harmful Bacteria X.1? Let’s see how we could answer this question using bioinformatics, along the way gaining insight into the wonderful world of bioinformatics.
Using traditional molecular biology techniques, we isolate Bacteria X and extract its DNA. Then we “sequence” this DNA. Cue the first link in the bioinformatics chain: acquiring data! Acquiring data is the process of generating useable data from a biological sample. In our case, deriving and determining the DNA sequence of the Bacteria X genome.
The next link in the chain is storing this sequence data. While bacterial genomes are typically small, other genomes, such as those of human beings, can produce terabytes (1000 gigabytes) of data.
Now we analyze this sequence data. There are people who specialize in developing computational tools to analyze and visualize data, versus people who actually analyze the information. A typical analysis for our sample case might be to first graphically visualize and compare the genome of the original, harmless Bacteria X.0 with the genome of the new, harmful Bacteria X.1. A scientist might observe a segment of DNA in Bacteria X.1 which is not present in the original Bacteria X.0. This new region of DNA may be responsible for the harmful effects, so the next analysis steps might be to drill down deeper into this region and see what genes lie there, what the function of those genes are, where they may have come from, etc.
[Remember: all assumptions made and conclusions drawn in this example are hypothetical and for illustrative purposes only.]
In this example, we encountered at least 4 different specialized areas within the field of bioinformatics:
1) Acquiring of data (working with machines and equipment, sequencing DNA)
2) Storing data (typically working with databases)
3) Developing tools to analyze and visualize data (programming)
4) Analyzing data (statistics, analysis)
Typically, individuals will specialize in one particular area rather than working simultaneously across all these fields. That, combined with all the different applications of bioinformatics, means you could ask 100 different “bioinformaticians” what they do and get 100 very different answers!
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