Metabolic engineering: methodologies and applications
Metabolic engineering aims to improve the production of economically valuable molecules
through the genetic manipulation of microbial metabolism. While the discipline is a little over …
through the genetic manipulation of microbial metabolism. While the discipline is a little over …
Microbial production of advanced biofuels
Concerns over climate change have necessitated a rethinking of our transportation
infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced …
infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced …
Machine learning for metabolic engineering: A review
Abstract Machine learning provides researchers a unique opportunity to make metabolic
engineering more predictable. In this review, we offer an introduction to this discipline in …
engineering more predictable. In this review, we offer an introduction to this discipline in …
Review on machine learning-based bioprocess optimization, monitoring, and control systems
Abstract Machine Learning is quickly becoming an impending game changer for
transforming big data thrust from the bioprocessing industry into actionable output. However …
transforming big data thrust from the bioprocessing industry into actionable output. However …
Protein sequence design with deep generative models
Protein engineering seeks to identify protein sequences with optimized properties. When
guided by machine learning, protein sequence generation methods can draw on prior …
guided by machine learning, protein sequence generation methods can draw on prior …
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
C Selvaraj, I Chandra, SK Singh - Molecular diversity, 2021 - Springer
The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Developing new drug molecules to overcome …
development as intractable and hot research. Developing new drug molecules to overcome …
Machine learning in bioprocess development: from promise to practice
Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess
development provides large amounts of heterogeneous experimental data, containing …
development provides large amounts of heterogeneous experimental data, containing …
Synthetic biology in the clinic: engineering vaccines, diagnostics, and therapeutics
Synthetic biology is a design-driven discipline centered on engineering novel biological
functions through the discovery, characterization, and repurposing of molecular parts …
functions through the discovery, characterization, and repurposing of molecular parts …
Recent advances in machine learning applications in metabolic engineering
Metabolic engineering encompasses several widely-used strategies, which currently hold a
high seat in the field of biotechnology when its potential is manifesting through a plethora of …
high seat in the field of biotechnology when its potential is manifesting through a plethora of …
A versatile active learning workflow for optimization of genetic and metabolic networks
Optimization of biological networks is often limited by wet lab labor and cost, and the lack of
convenient computational tools. Here, we describe METIS, a versatile active machine …
convenient computational tools. Here, we describe METIS, a versatile active machine …