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Biotechnology

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Precision Regulation Approach: A COVID-19 Triggered Regulatory Drive in South Korea.

Frontiers in public health
COVID-19 has triggered various changes in our everyday lives and how we conceptualize the functions of governments. Some areas require stricter forms of regulation while others call for deregulation. The challenge for the regulatory authorities is to...

Best practices for artificial intelligence in life sciences research.

Drug discovery today
We describe 11 best practices for the successful use of artificial intelligence and machine learning in pharmaceutical and biotechnology research at the data, technology and organizational management levels.

Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

Biotechnology progress
The production of recombinant therapeutic proteins from animal or human cell lines entails the risk of endogenous viral contamination from cell substrates and adventitious agents from raw materials and environment. One of the approaches to control su...

Learning on knowledge graph dynamics provides an early warning of impactful research.

Nature biotechnology
The scientific ecosystem relies on citation-based metrics that provide only imperfect, inconsistent and easily manipulated measures of research quality. Here we describe DELPHI (Dynamic Early-warning by Learning to Predict High Impact), a framework t...

Robotics for enzyme technology: innovations and technological perspectives.

Applied microbiology and biotechnology
The use of robotics in the life science sector has created a considerable and significant impact on a wide range of research areas, including enzyme technology due to their immense applications in enzyme and microbial engineering as an indispensable ...

Addressing Biodisaster X Threats With Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights.

Journal of medical Internet research
BACKGROUND: With advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is pa...

Artificial intelligence and the future of life sciences.

Drug discovery today
Over the past few decades, the number of health and 'omics-related data' generated and stored has grown exponentially. Patient information can be collected in real time and explored using various artificial intelligence (AI) tools in clinical trials;...

Improving the performance of machine learning models for biotechnology: The quest for deus ex machina.

Biotechnology advances
Machine learning is becoming an integral part of the Design-Build-Test-Learn cycle in biotechnology. Machine learning models learn from collected datasets such as omics data and predict a defined outcome, which has led to both production improvements...

Vital signal sensing and manipulation of a microscale organ with a multifunctional soft gripper.

Science robotics
Soft grippers that incorporate functional materials are important in the development of mechanically compliant and multifunctional interfaces for both sensing and stimulating soft objects and organisms. In particular, the capability for firm and deli...

Artificial intelligence for microbial biotechnology: beyond the hype.

Microbial biotechnology
It has been a landmark year for artificial intelligence (AI) and biotechnology. Perhaps the most noteworthy of these advances was Google DeepMind's AlphaFold2 algorithm which smashed records in protein structure prediction (Jumper et al., 2021, Natur...