Bioinformatics refers to the research, development, and application of computational tools for expanding the use of biological, medical, behavioral, and health data, including steps to acquire, organize, archive, store, analyze, or visualize such data. Simply put, bioinformatics employs the latest technology to maximize the power of biological research.
Since the advent of the computer age, digital technology has played a bigger and bigger part in every industry. Computers have helped scientists make major breakthroughs in the realms of biological research, because they have accelerated the rate at which scientists can acquire and analyze data. With more data produced more rapidly every year, there is a greater need to efficiently store, organize, and archive this information. This sharp increase in data volume has brought about the need for faster, more efficient analysis and visualization tools.
Each area of bioinformatics—whether focused on acquiring data or storing and analyzing it—faces unique challenges. It is not uncommon for advances in one area to spark advancements in several others. Bioinformatics relies on techniques from the following fields:
- Applied mathematics
- Chemistry and biochemistry
- Computer science
- Artificial intelligence
How did the field of bioinformatics begin?
Human beings have been trying to understand the human body for thousands of years prior to the invention of modern computing technology in the mid-20th century. However, computers became important in molecular biology during the 1950s, after Frederick Sanger determined the protein sequence of insulin—these sequences were long and complicated, making it extremely time-consuming to compare several sequences manually. It might be said that the discipline of bioinformatics began in the last half of the 20th century through the combined efforts of Margaret Oakley Dayhoff, Russell F. Doolittle, and Walter M. Fitch, three scientists who pioneered the use of databases and other computational methods to analyze protein and DNA sequences.
What is bioinformatics used for?
The broad, primary objective of bioinformatics is to increase our understanding of biological processes. Bioinformatics utilizes computationally intensive techniques in order to attain this objective, using data mining, pattern recognition, and machine learning algorithms as well as visualization technologies. Major research efforts in the field of bioinformatics include:
- protein structure alignment
- protein structure prediction
- gene finding
- genome assembly
- gene expression
- drug design
- drug discovery
- genome-wide association studies
- modeling of evolution
In short, bioinformatics focuses on the development of statistical and computational techniques, databases, theories, and algorithms to analyze and manage biological data.
Bioinformatics has led to numerous groundbreaking discoveries in the medical world. In 2016, a team of researchers used bioinformatics in making a major breakthrough in the transformation of human cells. Julian Gough, Professor of Bioinformatics at the UK’s University of Bristol, explained to the press that his team’s discovery could allow experimental biologists to bypass the need to create stem cells for research. The use of stem cells has created a great deal of controversy, as it can involve the use, development, and destruction of human embryos.
The University of Bristol discovery could potentially open the door to developing a new range of treatments for a variety of medical conditions—from macular degeneration to arthritis to heart disease—and could pave the way for medical advances which could not only improve the quality of millions of patients’ lives, but which could be lifesaving.
Bioinformatics and the fight against cancer
Bioinformatics has also led to groundbreaking developments in the field of cancer research. Cancer remains a major threat in the US and globally, with an estimated 38.4% of the US population predicted to be diagnosed with cancer at some point in their lifetime, according to the National Cancer Institute (NCI).
The sheer volume of biological data collected in the course of biomedical research has exploded, thanks largely to powerful research technologies. Mining the sheer volume of data to answer complex biological questions has grown more and more challenging. Nowhere is this more evident than in the fight against cancer, but government and other organizations are working to meet this challenge. For example, the NCI created the Genomic Data Commons in 2016, in order to provide a single source of data from research funded by the NCI, as well as the analytical tools needed to mine this information. It was created by the NCI as a centralized “knowledge system” for cancer.
Cancer is a complex disease in which understanding the development of the disease, as it presents in each patient, is critical to the patient’s treatment and prognosis. Bioinformatics can be an important element in addressing such challenges in cancer diagnosis, treatment, and predictive prognosis. For example, semantic models containing transcriptomic, genomic, and epigenomic data from melanoma samples have been used in anti-cancer therapy. Bioinformatics is also expected to play a critical role in identifying new biomarkers to monitor the progress of cancer and its response to various therapies, as well as in providing predictors for improvement of the patient’s quality of life.
In sum, bioinformatics is one of the most critical and useful systems for clinical research and applications in the fight against cancer, for the potential benefit of millions of cancer sufferers around the world.