The Global Bioinformatics Market is projected to reach USD 23.89 billion in 2027 from USD 8.09 billion in 2018, at a CAGR of 14.5% during the forecast period.
Will the integration of machine learning and AI in healthcare create opportunities for players in the bioinformatics market?
Machine learning deals with the development and application of computer algorithms that improve with experience by analyzing and understanding large data sets and drawing conclusions. In genomics, machine learning can be used to learn and understand how to recognize the locations of transcription start sites (TSSs) in a genome sequence, which is expected to help in obtaining faster and automated results. Machine learning in genomics affects multiple touchpoints, including how genetic research is conducted, how clinicians provide patient care, and the accessibility of genomics to individuals interested in learning more about how their heredity may influence their health. Efforts are being made to implement AI to help accelerate the use of technology from bench-to-bedside and make precision medicine a more common practice in smart healthcare. The future of medicine is expected to rely on AI, as AI is likely to evolve in a way that helps doctors instead of replacing them.
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How do the effective management, processing, and analysis of a large volume of data constitute a major challenge in the bioinformatics market?
Rapid advancements in next-generation sequencing (NGS) technologies have generated large volumes of biological data. Data analysis is necessary, as a lot of information is still unexplored in genome analysis. Hence, data that remains after bioinformatics analysis carries huge importance and can be reused. However, most of the current solutions do not adequately solve the challenges of data management in bioinformatics.
The complexity of data results in a proportionate increase in the demand for physical storage, correct and rigorous analysis, and suitable software for visualization. Although Google has come up with Google cloud solutions to store and manage data, questions on the integration of the entire bioinformatics pipeline with different tools from different companies are unanswered. Considering these factors, the effective management, processing, and analysis of a large volume of data at a lower cost constitute a major challenge in the bioinformatics market.
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