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Biotechnology

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A Study on the Application and Use of Artificial Intelligence to Support Drug Development.

Clinical therapeutics
PURPOSE: The Tufts Center for the Study of Drug Development (CSDD) and the Drug Information Association (DIA) in collaboration with 8 pharmaceutical and biotechnology companies conducted a study examining the adoption and effect of artificial intelli...

Biotechnology, Big Data and Artificial Intelligence.

Biotechnology journal
Developments in biotechnology are increasingly dependent on the extensive use of big data, generated by modern high-throughput instrumentation technologies, and stored in thousands of databases, public and private. Future developments in this area de...

Systems Metabolic Engineering Meets Machine Learning: A New Era for Data-Driven Metabolic Engineering.

Biotechnology journal
The recent increase in high-throughput capacity of 'omics datasets combined with advances and interest in machine learning (ML) have created great opportunities for systems metabolic engineering. In this regard, data-driven modeling methods have beco...

SignalP 5.0 improves signal peptide predictions using deep neural networks.

Nature biotechnology
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish ...

Deep Learning: Current and Emerging Applications in Medicine and Technology.

IEEE journal of biomedical and health informatics
Machine learning is enabling researchers to analyze and understand increasingly complex physical and biological phenomena in traditional fields such as biology, medicine, and engineering and emerging fields like synthetic biology, automated chemical ...

AI Paradigms for Teaching Biotechnology.

Trends in biotechnology
Artificial intelligence (AI) is profoundly changing biotechnological innovation. Beyond direct application, it is also a useful tool for adaptive learning and forging new conceptual connections within the vast network of knowledge for the advancement...

Deep Learning with Microfluidics for Biotechnology.

Trends in biotechnology
Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology researchers with vast amounts of data but not necessarily the ability to analyze complex data effectively. Over the past few years, deep artificial neural networks ...

Amine-Functionalized Sugarcane Bagasse: A Renewable Catalyst for Efficient Continuous Flow Knoevenagel Condensation Reaction at Room Temperature.

Molecules (Basel, Switzerland)
A biomass-based catalyst with amine groups (-NH₂), viz., amine-functionalized sugarcane bagasse (SCB-NH₂), was prepared through the amination of sugarcane bagasse (SCB) in a two-step process. The physicochemical properties of the catalyst were charac...

Ultrasound-assisted d-tartaric acid whole-cell bioconversion by recombinant Escherichia coli.

Ultrasonics sonochemistry
d-Tartaric acid has wide range of application in the pharmaceutical industry and scarcely exists in nature. In this study, cis-epoxysuccinate hydrolase (CESH)-containing Escherichia coli was used to perform whole-cell bioconversion of cis-epoxysuccin...

A β-mannanase from Paenibacillus sp.: Optimization of production and its possible prebiotic potential.

Biotechnology and applied biochemistry
A thermotolerant bacterium Paenibacillus thiaminolyticus with an ability to produce extracellular β-mannanase was isolated from a soil sample. Bacterium produced 45 U/mL β-mannanase at 50 °C. The culture conditions for high-level production of β-mann...