AIMC Topic: Biosynthetic Pathways

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Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP.

Nature communications
The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user-friendly toolkit, BioNavi-NP, is developed to predict the biosynthet...

Deep Learning to Predict the Biosynthetic Gene Clusters in Bacterial Genomes.

Journal of molecular biology
Biosynthetic gene clusters (BGCs) in bacterial genomes code for important small molecules and secondary metabolites. Based on the validated BGCs and the corresponding sequences of protein family domains (Pfams), Pfam functions and clan information, w...

NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products.

Journal of natural products
Computational approaches such as genome and metabolome mining are becoming essential to natural products (NPs) research. Consequently, a need exists for an automated structure-type classification system to handle the massive amounts of data appearing...

Applications of artificial intelligence to enzyme and pathway design for metabolic engineering.

Current opinion in biotechnology
Metabolic engineering for developing industrial strains capable of overproducing bioproducts requires good understanding of cellular metabolism, including metabolic reactions and enzymes. However, metabolic pathways and enzymes involved are still unk...

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits.

Journal of chemical information and modeling
The central challenge in automated synthesis planning is to be able to generate and predict outcomes of a diverse set of chemical reactions. In particular, in many cases, the most likely synthesis pathway cannot be applied due to additional constrain...

A deep learning approach to evaluate the feasibility of enzymatic reactions generated by retrobiosynthesis.

Biotechnology journal
Retrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective metho...

Classification of alkaloids according to the starting substances of their biosynthetic pathways using graph convolutional neural networks.

BMC bioinformatics
BACKGROUND: Alkaloids, a class of organic compounds that contain nitrogen bases, are mainly synthesized as secondary metabolites in plants and fungi, and they have a wide range of bioactivities. Although there are thousands of compounds in this class...

CGPS: A machine learning-based approach integrating multiple gene set analysis tools for better prioritization of biologically relevant pathways.

Journal of genetics and genomics = Yi chuan xue bao
Gene set enrichment (GSE) analyses play an important role in the interpretation of large-scale transcriptome datasets. Multiple GSE tools can be integrated into a single method as obtaining optimal results is challenging due to the plethora of GSE to...

Enhancement of Nucleoside Production in Based on Biosynthetic Pathway Analysis.

BioMed research international
To enhance nucleoside production in , the biosynthetic pathways of purine and pyrimidine nucleosides were constructed and verified. The differential expression analysis showed that , and genes involved in purine nucleotide biosynthesis were signifi...

Selected essential oils inhibit key physiological enzymes and possess intracellular and extracellular antimelanogenic properties in vitro.

Journal of food and drug analysis
Essential oils (EOs) extracted from six medicinal herbs and food plants [Cinnamomum zeylanicum (CZ), Psiadia arguta (PA), Psiadia terebinthina (PT), Citrus grandis (CGp), Citrus hystrix (CH), and Citrus reticulata (CR)] were studied for any inhibitor...