Applications of Bioinformatics in Medicine and Biotechnology

In simple words, bioinformatics is the application of information technology to study living things (or biological processes) at the molecular level (gene or protein level). The term Bioinformatics was coined by Paulien Hogeweg, Dutch Theoretical Biologist, along with Ben Hesper in 1970. In this article, we will look at the applications of bioinformatics in medicine and biotechnology.

What is Bioinformatics?

Bioinformatics (also termed as Biological Informatics) is an interdisciplinary field that leverages computation methods such as mathematical modeling, statistics, programming, simulation studies or analytical methods to analyze large sets of biological data. The data could be genetic sequences, protein samples or cell populations. The ultimate goal of bioinformatics is to discover (or identify) the biological process or make new predictions (could be disease mechanism, the yield of new crops or drug therapeutics).

Applications of Bioinformatics in Medicine and Biotechnology

What is the Need for Bioinformatics?

The human body is composed of billions (rather trillions) of cells, which are involved in various complex processes. The cells are controlled by DNA (De-oxyribo Nucleic Acid – the central processing machinery). Understanding DNA can reveal a lot about the organism as well as the chances of diseases in the future.

Chronic diseases are rapidly expanding all across the globe. The traditional drug discovery process and drugs are not working as effectively as they should. According to a study published in Nature, the top 10 highest grossing drugs prescribed in the US help only a small percentage (< 25%) of the patients. For cholesterol drugs, the success rate is even lower (only 2% of patients). So the probability of success is very lower compared to the expenditure made on research, approval, and marketing activities.

Hence, the associated healthcare costs are increasing at an astronomical rate. This is why the world needs personalized treatments tailored to the genetics of increasingly diverse patient populations, segregated by clinical & family history, lifestyle & diet, environmental factors and many other parameters. This requires a vast amount of data collection, integration, processing, and analysis.

Current technologies like Next Generation Sequencing (NGS), genome sequencing, microarray profiling have generated a large amount of data. These data, or rather Big Data, derived from Genome, Transcriptome, Proteome, and Metabolome need to be organized into databases and analyzed. This is where Bioinformatics can be a very powerful & effective tool. The outcomes of analysis of these large data (aka Big Data) are utilized in healthcare, preventive medicine, and drug discovery. Learn more about the applications of big data in medicine and healthcare.

Bioinformatics vs Biotechnology

Source: NAU-ACM

As mentioned earlier, bioinformatics is an interdisciplinary field that involves disciplines such as statistics, maths, computer sciences, and engineering to collect and analyze complex biological data.

Biotechnology is any technological application that uses biological systems, living organisms, or derivatives thereof, to make or modify products or processes for specific use. At its core, biotechnology involves genetic manipulation of microorganisms for the production of specific products for industrial purposes.

Related Post: Biotechnology vs Biomedical Science vs Biomedical Engineering (Bioengineering)


Applications of Bioinformatics in Medicine and Biotechnology


Applications of Bioinformatics in Genomics:

Bioinformatics plays a vital role in the areas of structural genomics, functional genomics, and nutritional genomics. Genomics is an interdisciplinary field of science focusing on the structure, function, evolution, mapping, and editing of genomes. A genome is an organism’s complete set of DNA, including all of its genes. Each genome contains all of the information needed to build and maintain that organism.

Don’t confuse genomics with genetics. Genetics is the study of individual genes and their roles in inheritance. In contrast, genomics aims at the collective characterization and quantification of genes, which direct the production of proteins with the assistance of certain enzymes and messenger molecules.

The field of genomics generates a vast amount of data from gene sequences, their interrelation, and functions. Bioinformatics plays a very important role to manage this vast amount of data. Bioinformatics provides both theoretical bases and practical methods for detecting systemic functional behaviors of the cell and the organism.

Applications of Bioinformatics in Proteomics:

Proteomics has evolved from genomics and the successful sequencing and mapping of the genomes of a wide variety of organisms, including humans. Proteomics is the large-scale study of proteins. It covers emerging scientific research and the exploration of proteomes from the overall level of intracellular protein composition (protein profiles), protein structure, protein-protein interaction, and unique activity patterns (e.g. post-translational modifications).

Proteomics is an important component of functional genomics, genetics, biochemistry, and molecular biology. Proteomics involves systematic, high-throughput approach to protein expression analysis of a cell or an organism.

Typical results of proteomics studies are inventories of the protein content of differentially expressed proteins across multiple conditions. This can be achieved by deploying peptide mass fingerprinting and peptide fragmentation fingerprinting, gel technology, HPLC, and mass spectrometry. The vast protein data (proteomics results) can be managed and access easily by using bioinformatics tools, software, and databases.

Applications of Bioinformatics in Transcriptomics

Transcriptomics is the study of the transcriptome – the complete set of RNA transcripts that are produced by the genome under specific conditions or in a specific cell.

This can also be called as Expression Profiling where DNA microarray is used to determine the expression level of mRNA in a given cell population. The microarray technique generates a vast amount of data, a single run generates thousands of data value and one experiment requires hundreds of runs.

Bioinformatics is used for transcriptome analysis where mRNA expression levels can be determined.

Applications of Bioinformatics in Cheminformatics

Cheminformatics (aka chemical informatics or chemoinformatics) focuses on storing, indexing, searching, retrieving, and applying information about chemical compounds. Cheminformatics involves organization of chemical data in a logical form to facilitate the retrieval of chemical properties, structures and their relationships.

Bioinformatics is used to identify and structurally modify a natural product, to design a compound with the desired properties and to assess its therapeutic effects, theoretically. Cheminformatics analysis includes analyses such as similarity searching, clustering, QSAR modeling, virtual screening, etc.

Applications of Bioinformatics in Drug Discovery

Bioinformatics is playing an increasingly important role in almost all aspects of drug discovery and drug development. Bioinformatics tools are very effective in prediction, analysis and interpretation of clinical and preclinical findings.

Applications of Bioinformatics in Drug Discovery

The traditional methods (pharmacology and chemistry-based drug discovery approaches) are not proving to be very effective in finding new drugs and/or achieving desired treatment outcome.

A successful and reliable drug design process significantly reduce the time and cost of the drug discovery & development process. Computational methods and bioinformatics tools are used to predict the drug-likeness. It basically means the identification and elimination of candidate molecules that are unlikely to survive the later stages of discovery and development. More importantly, bioinformatics is also laying the foundation for the evolution of the field of Computation Synthetic Biology (CSB).

Applications of Bioinformatics in Personalized Medicine

Personalized medicine is medical care customized to each patient’s genetic makeup. Drugs are often given in combination in order to improve the therapy success rate. The relationship between the molecular data pertaining to a patient and their disease phenotype are complex and cannot be determined manually.

Bioinformatics is an essential component in basic research, in the development of new concepts for diagnosis and therapy as well as in clinical practice. Bioinformatics can play a central role in interpreting the molecular data and as an instrument for providing recommendations for the practicing physician.

Applications of Bioinformatics in Personalized Medicine
Source: PubMed

Applications of Bioinformatics in Other Fields of Biotechnology & Life Sciences

Apart from the above fields, bioinformatics has also got vital roles to play in the following verticals of Life Sciences & Biotechnology:

  • Agricultural Science (Crop Improvement)
  • Veterinary Science
  • Forensic Science
  • Evolutionary Biology
  • Biodefense
  • Waste Clean-up
  • Climate Change
  • Biofuels & Bioenergy

Coming Soon: Careers in Bioinformatics: Job Prospects, Salaries, Required Skills, Higher Studies, Top Universities, and Q&A with Experts. Stay tuned!

In the meantime, check out the following online courses on Bioinformatics:

Bioinformatics – UC San Diego

Bioinformatic Methods 1 – University of Toronto

Bioinformatic Methods 2 – University of Toronto

Big Data, Genes, and Medicine – State University of New York

Introduction to Genomic Technologies – Johns Hopkins University

Genomics – University of Illinois at Urbana-Champaign

Genomic Sequencing – UC San Diego

Comparing Genes, Proteins, and Genomes – UC San Diego

Genomic and Precision Medicine – UC San Francisco

Statistics for Genomic Data Science – Johns Hopkins University

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