We will accelerate the development of life science innovation

In early December, "Melting supercomputing Momentum, Creating a New chapter of Simulation - 2021 Supercomputing Innovation Application Conference" was held in Guangzhou. The conference adopted the way of "main forum +4 parallel sub-forums", and the report content was wonderful. Among them, the "Life and health" sub-forum attracted the attention of many participants. Around the national "Healthy China 2030" strategy, the integration and innovation of supercomputing, big data and artificial intelligence continue to enable the development of cutting-edge technologies in life and health. Let's review the wonderful content of the sub-forum together.

▲ Life and Health sub-forum

The "Life and Health" sub-forum was chaired by Professor Yang Yuedong, Deputy chief engineer of the National Supercomputing Guangzhou Center of Sun Yat-sen University, and Engineer Chen Pin of the High Performance Computing Department. Experts, scholars and industry elites from universities, research institutes and enterprises were invited to discuss the latest application practice and development trend of high-performance computing, big data and artificial intelligence integration and innovation technology in the field of life and health.

1. AI accelerates life and health science research

With the development of artificial intelligence technology, researchers rely on supercomputing for RNA structure prediction, pathological diagnosis, and new drug research and development, which has brought new breakthroughs in related fields.

▲RNA structure prediction

The fundamental reason for the seemingly endless discovery of new Rnas is that each genome has a huge library of non-coding Rnas with unknown functions. Although more and more non-coding Rnas have been found to play key roles in various life processes and to be involved in many diseases, the vast majority remain unknown. Zhou Yaoqi, a senior researcher from Shenzhen Bay Laboratory, brought a report titled "RNA: The Never-ending Frontier report introduced the challenges faced by deep learning in RNA structure prediction, including how to find reliable homologous sequences to better capture sequence information, how to improve the accuracy of secondary structure prediction through deep learning, etc. Zhou Yaoqi, a senior researcher, conducted an in-depth analysis on these issues, and mentioned that for the problem of too little data, Transfer learning can be used to approximate the secondary structure data and add 3D structure sequence information to increase the sequence information and improve the effect. In using sequence prediction RNA, adding artificially generated sequences can replace natural sequences to improve accuracy.

▲ Pathological diagnosis

"Pathology is the foundation of medicine", pathology is the gold standard of clinical diagnosis, traditional clinical diagnosis is faced with complex diagnostic process, diagnosis cycle is too long, automation level is not high and over-dependence on pathologists and other phenomena, therefore, "digital pathology +AI" (that is, computational pathology) technology came into being. Associate Professor Yu Jinguang of South China University of Technology introduced the concept and development history of computational pathology in a simple way in the report "The Foundation of Artificial Intelligence Enabling Medicine", and summarized and summarized a series of problems faced by current computational pathology research institutes, such as huge data volume, strong data heterogeneity, and high cost of data annotation. At the same time, Professor Yu also shared some typical cases of applying deep learning to pathological diagnosis research. Finally, Professor Yu said that the research of computational pathology has just started, and the analysis of the microenvironment of cancer cells and the research of multi-center multi-modal algorithms may become a hot spot in the future.

2. Large-scale computing helps solve life science problems

The powerful computing power of supercomputers has injected new momentum into the discovery of new targets and the development of innovative drugs. Xu Yong, a researcher from Guangzhou Institute of Biomedicine and Health, Chinese Academy of Sciences, presented a report entitled "Application of High performance Computing in anti-tumor drug Research". In response to the bottleneck problem of the current shortage of new targets for original drugs, researcher Xu Yong introduced a method to explore original innovative targets from clinical samples. Using computational biology and molecular simulation as means, the team carried out research on new targets and new drugs for prostate cancer by relying on supercomputing. Aiming at the characteristics of key androgen receptor proteins in the treatment of prostate cancer, the research team analyzed the characteristics of potentially effective small molecule drugs, used algorithms to screen out tens of thousands of molecular libraries from hundreds of millions of molecules, and further screened out molecules with protein target specificity and suitable for clinical use. After layers of screening and optimization, the research team finally obtained a drug with high anti-tumor activity, providing an important target and drug candidate for overcoming clinical resistance.

▲ New drug research and development

Personalized hemodynamic simulation is widely used in the fields of virtual surgery, surgical planning, disease diagnosis and evaluation. Due to the computational power, the current hemodynamic analysis mainly focuses on the simulation of single organs, while many clinical diseases, such as cardiogenic stroke and secondary hypertension, need to consider the interaction of multiple organs at the same time. Chen Rongliang, Associate researcher of Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, introduced the great role played by Tianhe-2 supercomputer in the coupled hemodynamic simulation of human multi-organs, and introduced the rationality, feasibility, accuracy and parallel performance of the numerical simulation of blood vessels by non-Newtonian fluid dynamics combined with finite element method. He pointed out that the simulation method can simulate multi-organ hemodynamics, and looked forward to the wide application prospect of personalized hemodynamic simulation in the field of disease diagnosis and evaluation.

▲ Hemodynamic simulation

3. Technology leads the construction of big data +AI application platform

Gao Wei, general manager of China Unicom Medical Base, brought a report entitled "New Technologies Help the Construction of National Medical Center", introducing the basic situation of the National Respiratory Medicine Center and some achievements of the construction of respiratory big data platform. Through the cloud network collaboration, China Unicom helps improve the business development efficiency of the National Medical center. The platform integrates big data, cloud computing, AI, Internet of Things, VR and other applications, builds information cooperation based on medical cloud + private network, and builds a national regional clinical diagnosis and treatment guidance, research and collaboration center for difficult respiratory diseases. According to reports, in the future, the platform will continue to rapidly build Internet medical applications based on 5G+ cloud technology, quickly connect alliance units through data intelligence, build new applications of big data +AI, achieve innovation in medicine, education and research, and further promote the overall development of national medicine.

▲ Breathe big data platform

Su Jian, technical director of Guangdong Amethyst Information Storage Technology Co., Ltd. introduced the solutions provided by Amethyst Storage for life and health information protection in the report. According to the needs of life big data storage, Amethyst Storage has launched a high-performance magneto-optical fusion storage platform, which adopts the concept of magneto-optical intelligent layered storage to meet the storage needs of the complete life cycle of data from hot to cold in terms of total cost, main storage space, power consumption and hot data consumption. The platform can also greatly improve the security of customer data and reduce the overall storage cost of customers. In the future, Amethyst Storage will cooperate with Guangzhou Supercomputer to provide a wealth of hierarchical storage options for the majority of supercomputer users, and will also carry out research in the fields of big data processing, smart medical treatment, and data security based on supercomputing.

The panel discussion session of the sub-forum was chaired by Professor Yang Yuedong, with "meta-universe" as the core topic, focusing on the future development of supercomputing, meta-universe related data platform construction, artificial intelligence algorithm optimization and other hot topics, the report experts and participants warmly discussed and expressed their views. We believe that the meta-universe, the digitalization of medical diagnosis and treatment, and the construction of big data platforms are inseparable from the support of supercomputing power. In the future, the supercomputing Center will actively carry out innovation in the fields of medical and health big data and medical artificial intelligence, further strengthen industry-university-research cooperation in the field of big health, and jointly promote the implementation of the "Healthy China" strategy.