AIMC Topic: Codon

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A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences.

Nucleic acids research
Species-specific differences in protein translation can affect the design of protein-based drugs. Consequently, efficient expression of recombinant proteins often requires codon optimization. Publicly available optimization tools do not always result...

Automated Machine Learning Tools to Build Regression Models for Schizosaccharomyces pombe Omics Data.

Methods in molecular biology (Clifton, N.J.)
Machine learning is a powerful tool for analyzing biological data and making useful predictions. The surge of biological data from high-throughput omics technologies has raised the need for modeling approaches capable of tackling such amounts of data...

Revealing determinants of translation efficiency via whole-gene codon randomization and machine learning.

Nucleic acids research
It has been known for decades that codon usage contributes to translation efficiency and hence to protein production levels. However, its role in protein synthesis is still only partly understood. This lack of understanding hampers the design of synt...

An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

Molecular bioSystems
Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems...

[Gene optimization and efficient expression of Trichoderma reesei Cel5A in Pichia pastoris].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Deficient activity of endo-1,4-beta-glucanase II (Cel5A) secreted by Trichoderma reesei is one of the challenges involved in effective cellulase saccharification of cellulosic substrates. Therefore, we expressed Cel5A in Pichia pastoris by constructi...