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Related Concept Videos

What is Gene Expression?01:42

What is Gene Expression?

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
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
What is Gene Expression?01:42

What is Gene Expression?

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
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
What is Gene Expression?01:36

What is Gene Expression?

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 processed and...
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is formed in...
Deconvolution01:20

Deconvolution

Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...

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Related Experiment Video

Updated: May 11, 2026

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Deconer: An Evaluation Toolkit for Reference-based Deconvolution Methods Using Gene Expression Data.

Wei Zhang1, Xianglin Zhang2, Qiao Liu3

  • 1Center of Intelligent Medicine, School of Control Science and Engineering, Shandong University, Jinan 250061, China.

Genomics, Proteomics & Bioinformatics
|February 18, 2025
PubMed
Summary

A new toolkit, Deconvolution Evaluator (Deconer), offers comprehensive evaluation for reference-based cell deconvolution methods. It aids researchers in selecting optimal tools for gene expression analysis and clinical applications.

Keywords:
Cell-type proportionDeconerDeconvolution benchmarkGene expressionReference-based deconvolution

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics

Background:

  • Reference-based deconvolution methods accurately quantify cell type proportions from transcription data.
  • A lack of comprehensive evaluation and guidance exists for these methods.

Purpose of the Study:

  • Introduce Deconvolution Evaluator (Deconer), a toolkit for evaluating reference-based deconvolution methods.
  • Provide systematic comparisons and insights into cell proportion deconvolution algorithms.

Main Methods:

  • Developed Deconer with simulated and real gene expression datasets (bulk and single-cell).
  • Conducted systematic comparisons of 16 deconvolution methods.
  • Analyzed method robustness, rare component deconvolution, signature gene selection, and external reference building.

Main Results:

  • Performed in-depth analysis of application scenarios and challenges.
  • Provided constructive suggestions for selecting and developing deconvolution algorithms.
  • Demonstrated Deconer's utility in comparing diverse deconvolution methods.

Conclusions:

  • Deconer offers valuable insights for researchers choosing deconvolution tools.
  • Facilitates clinical applications and advances deconvolution tool development for gene expression data.
  • The toolkit, code, and data are publicly available.