Bioinformatics experiments. Introduction

(The image above was created by me with the help of PyMol (open-source tool for molecules visualization/exploration). You can use the image if you want)

The purpose of this series of posts is to demonstrate the power/beauty of bioinformatics (I’m just an amateur, though).
There’re 2 terms, most biologists are familiar with, namely “In vivo” and “In vitro”.
"In vitro" is used to describe the studies of living/dead organisms done outside of their normal context/environment (like in test-tubes).
"In vivo" is used to describe the studies of living organisms done in their normal context/environment.
And with the advent of computers one more term was introduced -> “In silico”.
“In silico” is used to describe experiments done with biological data with the help of computer power.
[2, 3, 4]
Bioinformatics is an interdisciplinary field of study, taking advantage of mathematics, statistics, computer science, computational linguistics and some others [1].

And the purpose is to help scientists to understand biological data.

All you need to do “In silico” experiments is your desire, internet-connection and computer.

With biochemistry/molecular biology moving forward, a huge amount of data was collected. This was one of the impulses for bioinformatics development. Not only we have nowadays a huge amount of information about protein/DNA/RNA sequences, but we also have a huge amount of literature. And it’s impossible to read all that and to investigate all that biochemical information manually.

(The image above was created by me with the help of Clustal Omega. You can use the image if you want)

Even though we see “informatics” in “bioinformatics”, you don’t need to be a programmer to do bioinformatics (but that might be useful). For all those biological data stored on serves a huge amount of web-tools was developed. One of the central resource for bioinformatics knowledge is National Center for Biotechnology Information (NCBI).

It’s hard to describe the whole range of opportunities bioinformatics gives to its users.

With bioinformatics there’s no need to waste a lot of resources to carry out lots of those experiments done in test-tubes, which saves us a lot of reagents and, most importantly, bioinformatics saves us a lot of time.

You can “feel” the power of bioinformatics especially when it comes to Cyc.

…the world’s largest smartest common sense knowledge base.
Cyc helped the Cleveland Clinic sift through five million patient records to find the perfect 82 drug trial candidates for a new cardiovascular therapy.
A search like this usually takes 10 weeks.
It took Cyc 10 minutes.
[source – "Meet Cyc" video on YouTube]

For more information about Cyc watch "Meet Cyc" video on YouTube (or read about Lucid.AI).

In this series of posts we are going to explore some biochemical/bioinformatics concepts and some tools for bioinformaticians.
I’m not going to provide explanations/definitions for such common-used terms like proteins, enzymes, but I will try to provide them for some bioinformatics-specific terms and, possibly, some analogies from non-biochemical/bioinformatics-related life.

References:

1. https://en.wikipedia.org/wiki/Bioinformatics

2. https://en.wikipedia.org/wiki/In_vitro

3. https://en.wikipedia.org/wiki/In_vivo

4. https://en.wikipedia.org/wiki/In_silico