In 2016, there were more than 14 million new cancers worldwide and 9 million deaths. Cancer has become one of the leading causes of death in developed countries, and one in five people who died each year in the United States died of cancer. According to the American Cancer Society and the International Cancer Society, the sooner all cancers are treated, the better the treatment. The early detection of cancer can win more time for pathological diagnosis and treatment, which can greatly improve the cure rate and patient life cycle and quality. Early screening for cancer is a trillion-level market.

The popularity of the capital market has benefited from the rapid development of gene sequencing technology in the past ten years, especially in the field of cancer. On the other hand, the extensive application of machine learning technology in gene big data processing has accumulated unprecedented knowledge. These new knowledge and combinations open the door to a new world for the medical community, giving medical workers new channels and information on the understanding, screening and treatment of many diseases.

机器学习技术推动基因分析的进步

Advances in gene sequencing technology make genetic analysis more efficient and faster

People can be regarded as an extremely sophisticated instrument. During a lifetime, trillions of cells are constantly replicating and renewing in the body. Each generation of replication is strictly the same, but there is a very small error rate, causing so-called genetic mutations. The vast majority of mutations are irrelevant, with a small number of mutations causing dysfunction of genes that inhibit growth, or activating growth genes that turn into cancer cells. Once the cancer cells escape the monitoring of the immune system, the growth is out of control and becomes cancerous tissue.

A person's genome sequence is 3 billion, printed on A4 paper in normal layout, probably as high as the Washington Monument. There will be less than one-thousandth of a difference between people, and there will be subtle differences between cancer cells and their normal cell genome sequences. Advances in gene sequencing have made identifying these differences a fast, efficient, and low-cost thing.

The development of computer computing speed and ability further promotes the progress of genetic analysis

Due to the complexity of the human genome, the amount of sequencing data is very large, and a person's whole genome sequencing data can reach hundreds of G. Ordinary computer technology and statistical methods cannot handle this information well in a short period of time, and the development of machine learning and the advancement of GPU computing have gradually solved this problem for researchers. Now only need to input the data of gene sequencing into the model of machine learning and repeated training, the computer can quickly analyze whether there is variation in the target area, and then find the possible genetic point to provide doctors with more diagnostics and Treatment information. It is precisely because of the maturity of machine learning and gene sequencing technology that early screening projects for various diseases, including cancer screening and diagnosis, have gradually become a hot spot for research and venture capital.

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