The tenet of computational biology is fast expanding, fast merging with mainstream biology. Riding on the wave of neural networks, the next-gen biological research in expected to pivot on the use of mathematical, statistical, and computational methods. The dizzying array of candidate experimental targets contain information-rich resources, the key to lies to computation biology. The need for multiscale biological modelling is a key drive for the expansion of the computational biology market. The vast transcriptomic, proteomic data, and genomic data that once unrivalled pave way to identification and classification of the disease-associated genes.
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Brain Modelling New Avenue, Role in Understanding Complexity of Diseases Increases
Computational biology holds an incredible potential in situ structural biology studies. A key avenue attractive industry research and development funding is the use of computational biology in brain modelling. Understanding network signalling in cells through computational biology is another emerging applications in the computational biology market.
This signalling holds a vast potential for understanding the epidemiology of the diseases. Unravelling the complexity of emergent infectious diseases such as in Sars-Cov may be possible by utilizing the cutting-edge tools of computational biology, such as in understanding the mutant variant.
Advances made nanobiology are expanding the canvas for players in the computational biology market. These will be increasingly propelled and accelerated by strides in machine learning technologies and the big data. Computational structural biology will open new directions in the market. The discovery of new statistical models used by computational biologists is a key trend in the computational biology market. New techniques based on mathematical theories will help expand the capabilities of computational biology in understanding protein biology. New deep learning approaches are expected to boost the market.
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