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Related Concept Videos

What is Gene Expression?01:42

What is Gene Expression?

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
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What is Gene Expression?01:36

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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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Chromatin Position Affects Gene Expression02:35

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Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
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Cell Specific Gene Expression01:58

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Regulation of Expression Occurs at Multiple Steps02:24

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Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
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The human body maintains a narrow pH range regulated through acid-base balance. This balance is crucial as changes in the hydrogen ion concentration can disrupt cell membrane stability, alter protein structures, and change enzyme activities. The normal pH of arterial blood is 7.4, venous blood and interstitial fluid is 7.35, and intracellular fluid averages 7.0.
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Related Experiment Video

Updated: Jan 29, 2026

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers
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ColiFormer: A Transformer-Based Codon Optimization Model Balancing Multiple Objectives for Enhanced E. coli Gene

Saketh Baddam1, Omar Emam2, Abdelrahman Elfikky3

  • 1Cedar Falls High School, Cedar Falls, IA 50613, USA.

Bioengineering (Basel, Switzerland)
|January 28, 2026
PubMed
Summary
This summary is machine-generated.

ColiFormer is a new AI tool that optimizes gene sequences for better protein production in E. coli. It balances multiple biological factors, outperforming existing methods in computational tests.

Keywords:
Escherichia coliGC content controlaugmented Lagrangian optimizationcodon adaptation index (CAI)codon optimizationmulti-objective optimizationrecombinant protein production

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Area of Science:

  • Synthetic Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Codon optimization enhances heterologous gene expression in Escherichia coli.
  • Existing methods often prioritize only the codon adaptation index (CAI), overlooking crucial biological context.

Purpose of the Study:

  • Introduce ColiFormer, a novel transformer-based framework for codon optimization.
  • Improve gene expression by simultaneously considering multiple biological parameters.

Main Methods:

  • Fine-tuned a transformer model (ColiFormer) on 3676 high-expression E. coli genes.
  • Utilized self-attention mechanisms and augmented Lagrangian optimization.
  • Balanced CAI, GC content, tRNA adaptation index (tAI), RNA stability, and cis-regulatory elements.

Main Results:

  • ColiFormer showed improved CAI and tAI values in silico evaluations.
  • Maintained optimal GC content and reduced inhibitory cis-regulatory motifs.
  • Outperformed established methods in computational benchmarks with competitive runtime.

Conclusions:

  • ColiFormer offers a more comprehensive approach to codon optimization.
  • Computational predictions suggest significant potential for enhanced gene expression.
  • The tool and datasets are open-source for further research and validation.