Bioinformatics is the scientific discipline that includes the use of computers to collect, store and analyse information relating to biological data. This includes things like DNA and amino acid sequences or annotations about the sequences. It is an interdisciplinary field that includes a mix of biology, physics, computer science, and mathematics. Bioinformatics is used to increase peoples’ understanding of health and disease and is integral for the management of data in biology and medicine.
It has the potential to recognise patterns in huge amounts of data that would be impossible for humans to recognise without the help of software. By applying computers and analysis, researchers are able to capture, manage and interpret biological data from medicine and biology.
Bioinformatics is most useful in the field of genomics. There can be an overload of information found in genomics, and bioinformatics gives meaning to the data, which is crucial as it can be used to get a diagnosis, to monitor infectious diseases in the wider public and to identify the best treatment for certain diseases.
History of Bioinformatics
Bioinformatics began in the early 1960s when researchers were trying to decipher the molecular sequence of proteins, so they could better understand the structure of proteins and how they work.
The Human Genome Project was the first large-scale bioinformatic experiment that ran from 1990 to 2003. An international team of researchers sequenced and mapped 3.1 billion protein base pairs in the genes.
Analysis
After a patient's biological sample is collected, it is sequenced by a machine that produces sets of data files. These documents are then analysed by bioinformaticians, each with a specialised series of steps depending on the clinical question and the type of biological sample that has been taken. After a bioinformatician has finished organising and analysing the data, they are left with annotated variants which are then interpreted by a clinical scientist who produces a clinical report. Each report is personally tailored to the patient to help guide their treatment.
It is crucial to have computer databases that have fast assimilation, different formats and algorithm software programs that can efficiently manage data. Because of the diverse nature of the information collected, there have to be multiple databases that are able to organise all the data in an effective manner. These databases usually contain public repositories of gene data as well as information from private companies.
The information provided by these databases includes detailed descriptions of diseases, genetic mutations and disease susceptibility.
Bioinformatic Tools
The main tools for a bioinformatician include software programs and the internet. One of the main activities is the sequence analysis of DNA and proteins by using various software and databases on the internet. Anyone in the research or health sectors can now discover the composition of biological molecules (nucleic acids and proteins) simply by using basic bioinformatic tools. However, bioinformatics is continuously evolving, and more complex software programs are slowly becoming available.
Pharmaceutical companies employ bioinformaticians to maintain all the bioinformatic needs of the industries. And with global growth, more laboratories are also finding the need to employ their own in-house bioinformaticians.
Other Uses of Bioinformatics
Bioinformatics is now being used to carry out a wide range of other important activities like the function and detection of gene regulation networks, the analysis of gene variation and expression, the prediction of gene and protein structures and the presentation and analysis of molecular pathways so that gene-disease interactions are better understood.
Bioinformatics has made more areas of study possible through data management and analysis. Researchers are able to access and analyse huge amounts of invaluable data from around the world. Bioinformatics can improve the treatment and diagnosis of various diseases and allows researchers to better understand protein sequences.