AIMC Topic: Biotechnology
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Machine learning to navigate fitness landscapes for protein engineering.
Current opinion in biotechnology
Apr 9, 2022
Machine learning (ML) is revolutionizing our ability to understand and predict the complex relationships between protein sequence, structure, and function. Predictive sequence-function models are enabling protein engineers to efficiently search the s...
Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.
Nature communications
Jan 27, 2022
Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning t...
Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network.
Bio Systems
Jan 19, 2022
In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibility of programming cells or unicellular organisms in order to enable them to perform certain tasks, wh...
Forty years of directed evolution and its continuously evolving technology toolbox: A review of the patent landscape.
Biotechnology and bioengineering
Jan 7, 2022
Generating functional protein variants with novel or improved characteristics has been a goal of the biotechnology industry and life sciences, for decades. Rational design and directed evolution are two major pathways to achieve the desired ends. Whi...
Improving the performance of machine learning models for biotechnology: The quest for deus ex machina.
Biotechnology advances
Oct 23, 2021
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
Oct 13, 2021
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
Oct 4, 2021
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...
Artificial intelligence and the future of life sciences.
Drug discovery today
Jul 8, 2021
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;...
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...
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