Bioinformatics is altering the landscape of healthcare, as well as other major sectors, including agriculture, animal health, environmental health, and more. Bioinformatics allows scientists to analyze and interpret the role of biological molecules in various processes. Often, bioinformatics is seen as the linguistic side of genetics. The fundamental objectives of the discipline are to identify genes and proteins involved in certain processes, determine their functions, and develop an understanding of their evolutionary importance.
As technology has developed that has allowed us to collect a wealth of fine-grain biological data, thus bioinformatics has emerged as scientists have begun to analyze, organize, manage, and share such data. Tools of data analysis, interpretation, and modeling are materializing across a range of sectors. Here, we discuss the applications, recent developments, and current global bioinformatics market, as well as how the field may develop in the future.
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Application Areas of Bioinformatics
Bioinformatics is vitally important for genomic and molecular biology research. Additionally, it significantly influences a diverse range of sectors, including medicine, pharmaceuticals, genetics, proteomics, metabolomics, agriculture, biotechnology and bioengineering, computational biology, computer modeling, animal health, and environmental health.
For example, several new bioinformatics tools have emerged that are being used to further the field of personalized and preventative medicine. One of the most important new tools for personalized medicine is next-generation sequencing (NGS), a high-throughput tool that runs base-pair sequencing in DNA or RNA. With this tool, scientists can run full sequencing of numerous genomes, examine gene expression profiles, study mutations, and epigenetic changes, and run molecular analyses, thus advancing the field of personalized medicine.
NGS is also heavily relied on in agriculture, where the exploration of the function of genetics in plants and animals has become vitally important for ensuring healthy and bountiful crop yields as well as healthy and disease-resistant animals. Other tools that are helping the agricultural industry better understand the DNA of their plants and animals include genome sequencing tools such as Phred/Phrap/Consed, genome comparison tools such as SynBrowse and VISTA, sequence profile alignment tools such as Position-Specific Iterative (PSI)-BLAST, and many more. These tools are helping scientists understand how genetics allow crops to become more resistant to pests and drought.
Read Here: Advancing Personalized Health through Bioinformatics
Recent Developments in Bioinformatics
Research in the field of bioinformatics is booming. Already, it is being used in a wide range of applications, of which scientists are continuing to develop the sophistication of bioinformatics technology used in these applications. Additionally, bioinformatics's success across sectors encourages further research into how bioinformatics can be leveraged in other fields.
Of recent, there have been numerous developments across sectors. For example, research published this year has successfully incorporated machine learning with bioinformatics to identify 8 autophagy-related biomarkers and construct gene regulatory networks in dilated cardiomyopathy - a condition that has a poor prognosis and is defined by impaired ventricular remodeling and systolic diastole.
Additionally, bioinformatics has recently been leveraged to compile a database to link drugs with potential drug targets for rare skin diseases, for which there is an urgent need for effective approved drugs to treat the range of over 800 diseases affecting 6.8 million people worldwide.
Bioinformatics has also recently been used to help scientists understand the role of viral infections in cervical cancer at a molecular level, which may lead to better preventative, diagnostic, and treatment options.
The application of bioinformatics in medicine and pharmaceuticals seems to be gaining the most traction. However, there is also much research in biotechnology and bioengineering, computational biology, and computer modeling.
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Current Global Market of Bioinformatics
According to Precedence Research, the global bioinformatics market was worth $13.2 billion in 2021. The global market is predicted to grow rapidly at a CAGR of 16.3% from 2022 to 2030 to reach a value of $45.6 billion.
Currently, North America represents the largest segment of the global bioinformatics market. Within North America, it is the US that dominates the region. This is due to favorable government rules in favor of key market players, which is helping to grow the market in the US.
Europe is currently the fastest-growing region, and the UK and Germany hold the highest market share in this region.
Government bodies and key market players in developed nations invest large sums of money into the technology and information sector. This is helping to propel the market in key regions. Additionally, research and development is strongly funded and motivated by the goal of establishing new market-ready products.
The current biggest players in the bioinformatics sector are Bio Rad (US), Agilent Technologies (US), Thermo Fisher Scientific (US), and Illumina (US).
The most commonly used tools include BLAST, EMBOSS and Staden, THREADER, PHD, RasMol, and WHATIF, among others.
Future Directions of Bioinformatics
The bioinformatics sector has gained much traction and has many motivations to succeed. Research and development is revealing more and more potential important applications of the technology, particularly in the healthcare sector. In the coming years, we will likely see further developments in this field, with novel preventative, diagnostic, and therapeutic applications emerging due to this work. Other key sectors currently benefiting from bioinformatics technology will also see continued development.
There are two key barriers to growth; however, that must be overcome for the bioinformatics sector to reach its full potential. First, due to the growing collection, storage, and distribution of biological data, there are growing concerns surrounding data privacy and security. As bioinformatics technology becomes more sophisticated, so must the security technology that protects it. Second, bioinformatics tools and equipment are still relatively costly. Set-up costs are high, which is a limiting factor to the widespread adoption of the technology. These high costs must be addressed before bioinformatics can reach its full potential.
The field of bioinformatics is showing strong growth, and many publications are emerging demonstrating the importance of the technology within several sectors. In particular, the landscape of medicine and pharmaceuticals will be greatly impacted. Although a couple of barriers to growth must be overcome, new bioinformatics applications will likely emerge in the coming years.
- 2022. Bioinformatics Market Size to Hit Around US$ 45.6 Bn by 2030 [Online]. Global Newswire. Available at: www.globenewswire.com/.../...ize-to-Hit-Around-US-45-6-Bn-by-2030.html (Last accessed September 2022).
- Aarthy, M., Muthuramalingam, P., Ramesh, M. and Singh, S., 2022. Unraveling the multi-targeted curative potential of bioactive molecules against cervical cancer through integrated omics and systems pharmacology approach. Scientific Reports, 12(1). https://www.nature.com/articles/s41598-022-18358-7
- Branco, I. and Choupina, A., 2021. Bioinformatics: new tools and applications in life science and personalized medicine. Applied Microbiology and Biotechnology, 105(3), pp.937-951. https://pubmed.ncbi.nlm.nih.gov/33404829/
- Esposito, A., Colantuono, C., Ruggieri, V. and Chiusano, M., 2016. Bioinformatics for agriculture in the Next-Generation sequencing era. Chemical and Biological Technologies in Agriculture, 3(1). chembioagro.springeropen.com/articles/10.1186/s40538-016-0054-8
- Kuo, T., Wang, P., Wang, Y., Chang, C., Chang, C. and Tseng, Y., 2022. RSDB: A rare skin disease database to link drugs with potential drug targets for rare skin diseases. Scientific Data, 9(1). https://www.nature.com/articles/s41597-022-01654-2
- Zhang, F., Xia, M., Jiang, J., Wang, S., Zhao, Q., Yu, C., Yu, J., Xian, D., Li, X., Zhang, L., Liu, Y. and Peng, M., 2022. Machine learning and bioinformatics to identify 8 autophagy-related biomarkers and construct gene regulatory networks in dilated cardiomyopathy. Scientific Reports, 12(1). https://www.nature.com/articles/s41598-022-19027-5#Sec9