AIMC Topic: Biotechnology
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Addressing Biodisaster X Threats With Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights.
Journal of medical Internet research
May 25, 2021
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...
Learning on knowledge graph dynamics provides an early warning of impactful research.
Nature biotechnology
May 17, 2021
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
May 10, 2021
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 ...
Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.
Biotechnology progress
Feb 24, 2021
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...
Precision Regulation Approach: A COVID-19 Triggered Regulatory Drive in South Korea.
Frontiers in public health
Feb 1, 2021
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
Jan 22, 2021
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.
A machine learning toolkit for genetic engineering attribution to facilitate biosecurity.
Nature communications
Dec 8, 2020
The promise of biotechnology is tempered by its potential for accidental or deliberate misuse. Reliably identifying telltale signatures characteristic to different genetic designers, termed 'genetic engineering attribution', would deter misuse, yet i...
Sequence-to-function deep learning frameworks for engineered riboregulators.
Nature communications
Oct 7, 2020
While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules....
Biosystems Design by Machine Learning.
ACS synthetic biology
Jun 29, 2020
Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desi...
Future development of artificial organs related with cutting edge emerging technology and their regulatory assessment: PMDA's perspective.
Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs
Feb 28, 2020
Future development of innovative artificial organs is closely related with cutting edge emerging technology. These technologies include brain machine or computer interface, organs made by three dimensional bioprinting, organs designed from induced-pl...
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