Currently, only magicians in China have some understanding of the essence of magic.

They have taken the lead in the new generation of technological revolution.

Although this advantage is merely an informational advantage that can be easily overcome, having an advantage is better than having none.

"We'll first prepare a work report and submit it to the higher-ups for decision-making. Right now, the most important thing is to keep Zheng Li occupied and prevent him from going back too soon."

"Okay, I'll make the arrangements."

The Chinese government has conducted multiple psychological profiles and character portraits of Zheng Li, and knows that although Zheng Li seems ruthless, he is actually very loyal to his friends.

......

"Chairman Zheng, our main focus now is to introduce the concept of 'wortice parising' from the field of natural language processing into innovative drug development."

"Algorithm-designed small protein sequences are superior to traditional methods in terms of stability, protein expression levels, and production costs."

"This method was developed two years ago when Stemirna Therapeutics and QC researchers collaborated on AI sequence optimization algorithms for mRNA vaccines."

"Mr. Cheng is a shareholder and external director of Siwei Microbiology. He was responsible for connecting us with researchers in Singapore. Over the past two years, we have expanded the application of AI sequence optimization algorithms to innovative drug development."

"The iterative technology for designing the sequence of guarantees is still under development."

Zheng Li was at the R&D center of Kechuang Bio in Jiangcheng, where the R&D director was reporting to him.

The Jiangcheng R&D Center is primarily responsible for the research and development of some innovative drugs.

Since the rise of science and technology innovation in biology, the college entrance examination score for the biology department of Jiangcheng University has increased by at least 20 points.

Biology was originally considered Jiangcheng University's flagship major, but due to poor career prospects, its admission scores were much lower than those of the School of Economics and Management.

A high ranking in a major does not necessarily mean a high score requirement. The majors with the highest scores at Jiangnan University are Financial Engineering and Mathematics, which offer double degrees in Finance and Mathematics upon graduation.

The research center of Kechuang Biotechnology in Jiangcheng mainly recruits students from Jiangnan University and Jiangcheng University of Science and Technology.

They recruit a large number of master's and doctoral graduates in biology, and their salaries are half a level higher than those at the rice branch in Jiangcheng.

Meanwhile, the research center in Jiangcheng has also carried out many collaborative projects with the School of Life Sciences of Jiangnan University.

Private discussions within Jiangda University revealed that Zheng Li, as a graduate of the School of Mathematics, had the biggest share of the pie actually taken by the School of Biology.

"So this is an application of AI and computational biology, right?"

In response to Zheng Li's question, Jiang Cheng's R&D director nodded and said, "Yes."

"Our main work at present is sequence alignment and protein structure prediction."

"Computational biology is not limited to these two fields, but also includes gene recognition, evolutionary tree construction, and other areas."

"Since AI technology came into view, machine learning technology has greatly developed computational biology."

"Advances in genomics and imaging technologies have led to an explosion in molecular and cellular analysis data from large numbers of samples."

"The rapid increase in the dimensionality and collection rate of biological data poses challenges to traditional analysis strategies. Modern machine learning methods, such as deep learning, promise to use very large datasets to find hidden structures and make accurate predictions."

"For example, we have a group that specializes in predicting the viability of cancer cells under the influence of drugs."

"The input feature values ​​will capture somatic sequence variants of the cell line, the chemical composition of the drug, and a summary of its concentrations. These, along with the measured viability, can be used to train support vector machines, random forest classifiers, or related methods."

"Given a new cell line in the future, the learning function predicts its potential viability by calculating the function."

"Even though a function seems more like a black box to us, it is not easy to find the specific reasons behind its internal workings and why a particular combination of mutations affects cell growth."

"Two regressions and classifications can be viewed in this way."

"As an alternative, unsupervised machine learning methods aim to discover patterns from data samples x themselves without needing to output labels y."

“Similar clustering, principal component analysis and outlier detection methods are closer to black boxes, and we currently mainly apply them to unsupervised models of biological data.”

Zheng Li clapped his hands and said, "Very good."

In fact, the evolutionary path of computational biology has many similarities with the research of modern mages.

The monks used the high-frequency computing power of the bio-cloud to conduct qualitative and quantitative analyses of the basic elements that constitute life, such as genes and proteins.

The mages' advantage lies not only in the fact that carbon-based computers have higher computing power and higher limits than silicon-based computers, but also in their ability to directly interfere with the material world through their will.

This allows for the study of more specialized and targeted induced samples.

Zheng Li continued, "Actually, you're mainly using neural networks right now, right?"

"Convolutional neural networks, recurrent neural networks, and autoencoders."

The R&D director was well aware of Zheng Li's research capabilities and the breadth of his expertise, so he was not at all surprised that Zheng Li had hit the nail on the head regarding their key points:

"Yes, it's mainly the application of neural networks in the field of computational biology."

When it comes to research and development, Zheng Li always speaks his mind:

"Deep learning has been used in computational biology for a long time."

“Bengio started using neural networks to study genomics and bioimage analysis as early as 2012, linking sequence variations with molecular features.”

"In other words, the technology we use may seem very advanced to a layman, such as deep learning and artificial intelligence, but in reality, it is something that others have been playing with for ten years."

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