observation | the “genome for everyone era” is approaching. who will be able to efficiently and accurately read and understand the massive amount of life data?
2024-09-18
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before the arrival of the "genome for everyone era", the gene sequencing industry will first face the problem of "labor shortage" in the analysis and interpretation of life data.
"with the rapid development of sequencing technology, when everyone has the opportunity to obtain an exclusive personal whole genome data, how to efficiently and accurately interpret the mysteries of life from massive life data has become the focus of industry attention." recently, when bgi, the leader in the domestic sequencing industry, released two nanopore sequencers, zhao lijian, ceo of bgi (300676.sz), talked about the problems facing the industry.
it is worth mentioning that with the launch of the nanopore sequencer, bgi announced that it will enter the "seq all" stage, which means that it has achieved a closed loop of "full-length" sequencing products. similarly, the bgi team proposed the "generative bio-intelligent (gbi all)" innovation paradigm based on genetic testing big data and combined with advanced ai algorithms.
it is reported that the core of the gbi all concept is to achieve in-depth analysis of whole genome data through generative biological intelligence technology. among them, genet, a multimodal large model for genetic testing, is a major breakthrough of bgi in the field of ai large models.
liang lungang, deputy director of it at bgi, introduced that in the test of real clinical samples, the genet model showed extremely high accuracy and was able to quickly screen out pathogenic mutations associated with clinical phenotypes from millions of variant sites, providing support for clinical diagnosis and treatment.
in addition to the genet model for clinical use, bgi also launched the chatgenet genomic consultation platform for the public. ordinary users upload their own genetic test reports to the chatgenet platform and learn about the genetic risks and prevention suggestions of related diseases through dialogue.
in addition, bgi has also launched the intelligent disease prevention and control system 13311i, which uses ai algorithms and big data analysis to help predict individual health risks, develop personalized prevention plans, and promote the transition from passive treatment to active health management.
bgi said that the emergence of gbi all will push precision medicine into the digital era.
in fact, obtaining genome data is only the first step in solving many mysteries of life. how to process the massive data obtained by sequencing is the key to the effective application of this technology. this is also one of the directions for long-term improvement in this field.
kyle farh, vice president of artificial intelligence at global industry giant illumina, said at a conference held in nanjing, jiangsu last september that "algorithms based on artificial intelligence and large models are showing great potential in the field of genetic data. illumina's r&d team is working hard to promote the application and development of ai algorithms based on natural selection training in genetic data."
last june, illumina also announced the launch of a new artificial intelligence (ai) algorithm, primateai-3d, which can use primate genes and advanced artificial intelligence technology to improve genetic risk prediction and drug target discovery. "you can train generative language models such as chatgpt on existing texts from wikipedia and other places. we use a similar deep learning architecture, but our data comes from millions of years of natural selection." the company said at the time.
thepaper.cn reporter he liping
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