AIMC Topic: Biotechnology

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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...

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...

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 ...

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...

Machine learning for functional protein design.

Nature biotechnology
Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and structure data have radically transformed computational protein design. New methods promise to escape the constraints of natural and laboratory evolution, accelera...

Protein design meets biosecurity.

Science (New York, N.Y.)
The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine. DNA...

Graph Neural Networks With Multiple Prior Knowledge for Multi-Omics Data Analysis.

IEEE journal of biomedical and health informatics
With the development of biotechnology, a large amount of multi-omics data have been collected for precision medicine. There exists multiple graph-based prior biological knowledge about omics data, such as gene-gene interaction networks. Recently, the...

Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology.

International journal of biological macromolecules
Lignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile perox...