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Predicting gene sequences with AI to study codon usage patterns
Tomer Sidi
, Shir Bahiri-Elitzur
, Tamir Tuller
,
Rachel Kolodny
Department of Computer Science
Research output
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Contribution to journal
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Article
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peer-review
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Keyphrases
Gene Sequencing
100%
Codon
100%
Codon Usage
100%
Selective Pressure
40%
Evolutionary
40%
Prediction Accuracy
40%
Eukaryotes
40%
Saccharomyces Cerevisiae
40%
Heterologous Protein
40%
Amino Acid Sequence
20%
Expression Level
20%
Nave
20%
Rapid Evolution
20%
Escherichia Coli
20%
Deep Learning
20%
Unique Perspectives
20%
Gene Function
20%
Minor Effect
20%
Effective Population Size
20%
AI Models
20%
Bacillus Subtilis (B. subtilis)
20%
Gene Conservation
20%
Highly Expressed Gene
20%
Overlapping Signals
20%
Schizosaccharomyces Pombe
20%
Monotonic Relationship
20%
Endogenous Protein
20%
Prediction Tool
20%
Varying Length
20%
AI Methods
20%
Co-translational Folding
20%
Important Determinant
20%
Frequency-based Approach
20%
Immunology and Microbiology
Gene Sequence
100%
Codon
100%
Codon Usage
100%
Artificial Intelligence
100%
Bacterium
60%
Eukaryote
40%
Amino Acid Sequence
20%
Escherichia coli
20%
Saccharomyces cerevisiae
20%
Effective Population Size
20%
Saccharomyces cerevisiae
20%
Bacillus subtilis
20%
Schizosaccharomyces Pombe
20%