As I have already said several times here on the blog, bioinformatics allows us to answer questions and understand biological phenomena by analyzing the data obtained from experimental tests performed in the laboratory. But what are the general methods by which bioinformatics analyzes data in order to achieve the desired knowledge?
There are two main methods by which bioinformatics investigates:
- comparative methods
- predictive methods
The comparative methods, as can be deduced from the name, allow you to give answers regarding a biological question studied by comparing the data under examination with data already interpreted present in special databases.
Let's take a quick example to better understand their mechanism of action:
Let's say we are analyzing a DNA sequence of a gene and our goal is to define the function of this gene, or to answer the following questions: for which protein does it code? what is the structure of the protein?
To answer these questions we can compare, with appropriate algorithms, such as alignment algorithms, the sequence of the gene under examination with sequences of genes whose functions are already known and placed in the reference database. Basically it is possible to infer the function of the gene, as well as the structure of the protein for which it encodes, from genes and similar proteins already characterized.
The predictive methods, on the other hand, are capable of answering biological questions by predicting the answer on the basis of previously acquired knowledge. In fact, these methods follow approaches based on machine learning, that is, they exploit algorithms capable of learning from existing data and deducing something still unknown from this knowledge.
Let's take another example:
If our intention is to trace the protein-coding genes present in a genome, we can exploit algorithms capable of identifying them, taking into account that the genes have a characteristic structure. In fact, inside the genes we find a 5'UTR and a 3'UTR region, exons separated by introns, a transcription start codon and an end codon and so on. Therefore by teaching to the algorithm it is possible to predict the genes present in the genome on the basis of previously acquired knowledge.
Well, for today we say goodbye here. As you have noticed this article is shorter than usual but don't be fooled, it is full of meaning. In fact, understanding how bioinformatics investigates biological data also allows us to understand how in general certain problems are solved by the algorithms used.
I remind you to leave a comment for any questions or clarifications, also if you liked the article and it seemed useful to you, I would really like to know it through a "like".
Bye-bye and see you soon.
Ciao mi puoi dire come si sta evolvendo il mondo della bioinformatica in Italia? Ma soprattutto dove lavora il bioinformatico?
Italian version:
Ciao. Il mercato della bioinformatica in Italia, cosi come nel resto del mondo, e’ in costante crescita. Sicuramente l’Italia rispetto ad altri paesi e’ un po’ indietro ma le possibilità di crescita sono molteplici. Se ti interessa ho parlato di questo anche nell’articolo “The bioinformatics market is growing” qui sul blog riferendomi al mercato della bioinformatica a livello mondiale. Credo comunque che l’aumento costante dei dati biologici porterà ad una crescente domanda di bioinformatici che possano analizzarli. Il bioinformatico riesce a lavorare in diversi contesti, dalle università , quindi enti di ricerca pubblici, alle aziende private nell’ambito biotecnologico e non solo. Sono davvero moltissime le possibilità !
English version:
Hi! The bioinformatics market in Italy, as well as in the rest of the world, is constantly growing. Certainly Italy is a bit behind compared to other countries, but the possibilities for growth are many. If you are interested I talked about this also in the article “The bioinformatics market is growing” here on the blog referring to the global bioinformatics market. However, I believe that systematic biological data will lead to a growing demand for bioinformaticians who can be analyzed. The bioinformatician is able to work in different contexts, from universities, therefore public research bodies, to private companies in the biotechnology field and beyond. There are so many possibilities!