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Biotechnology

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Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes.

Proceedings of the National Academy of Sciences of the United States of America
The potential of engineered enzymes in industrial applications is often limited by their expression levels, thermal stability, and catalytic diversity. De novo enzyme design faces challenges due to the complexity of enzymatic catalysis. An alternativ...

The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.

Molecular biotechnology
Cervical cancer (CC) continues to be a major worldwide health concern, profoundly impacting the lives of countless females worldwide. In low- and middle-income countries (LMICs), where CC prevalence is high, innovative, and cost-effective approaches ...

Synthetic biology advances towards a bio-based society in the era of artificial intelligence.

Current opinion in biotechnology
Synthetic biology is a rapidly emerging field with broad underlying applications in health, industry, agriculture, or environment, enabling sustainable solutions for unmet needs of modern society. With the very recent addition of artificial intellige...

A roadmap for model-based bioprocess development.

Biotechnology advances
The bioprocessing industry is undergoing a significant transformation in its approach to quality assurance, shifting from the traditional Quality by Testing (QbT) to Quality by Design (QbD). QbD, a systematic approach to quality in process developmen...

Machine learning: an advancement in biochemical engineering.

Biotechnology letters
One of the most remarkable techniques recently introduced into the field of bioprocess engineering is machine learning. Bioprocess engineering has drawn much attention due to its vast application in different domains like biopharmaceuticals, fossil f...

Machine learning in microalgae biotechnology for sustainable biofuel production: Advancements, applications, and prospects.

Bioresource technology
This review explores the critical role of machine learning (ML) in enhancing microalgae bioprocesses for sustainable biofuel production. It addresses both technical and economic challenges in commercializing microalgal biofuels and examines how ML ca...

Physics-informed neural networks for biopharmaceutical cultivation processes: Consideration of varying process parameter settings.

Biotechnology and bioengineering
We present a new modeling approach for the study and prediction of important process outcomes of biotechnological cultivation processes under the influence of process parameter variations. Our model is based on physics-informed neural networks (PINNs...

PanKB: An interactive microbial pangenome knowledgebase for research, biotechnological innovation, and knowledge mining.

Nucleic acids research
The exponential growth of microbial genome data presents unprecedented opportunities for unlocking the potential of microorganisms. The burgeoning field of pangenomics offers a framework for extracting insights from this big biological data. Recent a...