AIMC Topic: Synthetic Biology

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BioTRY: A Comprehensive Knowledge Base for Titer, Rate, and Yield of Biosynthesis.

ACS synthetic biology
Synthetic biology is rapidly evolving into a data-intensive science that increasingly relies on massive data sets; one of its applications is the evaluation of the economic viability of fermentation processes. However, the key economic indicators, na...

Neonatal bioethics, AI, and genomics.

Early human development
Artificial intelligence (AI) and synthetic biology will transform civilization. The only question is how. In this paper, I explore some recent developments in medical AI, genomics, and synthetic biology. I speculate about the implications of these te...

Engineering Sequestration-Based Biomolecular Classifiers with Shared Resources.

ACS synthetic biology
Constructing molecular classifiers that enable cells to recognize linear and nonlinear input patterns would expand the biocomputational capabilities of engineered cells, thereby unlocking their potential in diagnostics and therapeutic applications. W...

Multicellular artificial neural network-type architectures demonstrate computational problem solving.

Nature chemical biology
Here, we report a modular multicellular system created by mixing and matching discrete engineered bacterial cells. This system can be designed to solve multiple computational decision problems. The modular system is based on a set of engineered bacte...

SeqImprove: Machine-Learning-Assisted Curation of Genetic Circuit Sequence Information.

ACS synthetic biology
The progress and utility of synthetic biology is currently hindered by the lengthy process of studying literature and replicating poorly documented work. Reconstruction of crucial design information through post hoc curation is highly noisy and error...

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences.

ACS synthetic biology
N-terminal coding sequence (NCS) influences gene expression by impacting the translation initiation rate. The NCS optimization problem is to find an NCS that maximizes gene expression. The problem is important in genetic engineering. However, current...

AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors.

Molecules (Basel, Switzerland)
The rational design, activity prediction, and adaptive application of biological elements (bio-elements) are crucial research fields in synthetic biology. Currently, a major challenge in the field is efficiently designing desired bio-elements and acc...

Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review.

ACS synthetic biology
Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically breaking down molecules into readily available building block compounds. Having a long history in chemistry, retro-biosynthesis has also been used in the fi...

Cell factory design with advanced metabolic modelling empowered by artificial intelligence.

Metabolic engineering
Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a b...

Machine learning for the advancement of genome-scale metabolic modeling.

Biotechnology advances
Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the interrelations between genotype, phenotype, and external environment. The recent advancement of high-throughput experimental approaches and multi-omics strategies...