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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?01:36

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...
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...
Reporter Genes02:11

Reporter Genes

Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
Commonly used reporter...
Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Constitutive and Regulated Gene Expression01:27

Constitutive and Regulated Gene Expression

Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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pGQL: A probabilistic graphical query language for gene expression time courses.

Ruben Schilling1, Ivan G Costa, Alexander Schliep

  • 1Max Planck Institute for Molecular Genetics, Department of Computational Biology, Ihnestr, 63-73, 14195 Berlin, Germany. ruben.schilling@molgen.mpg.de.

Biodata Mining
|April 20, 2011
PubMed
Summary
This summary is machine-generated.

Probabilistic timeboxes offer a robust method for analyzing noisy time course data, improving upon traditional timeboxes. This approach facilitates easier, more powerful exploratory data analysis for complex datasets.

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Area of Science:

  • Computational Biology
  • Data Mining
  • Bioinformatics

Background:

  • Traditional timeboxes facilitate exploratory analysis of time course data but lack robustness against noise and fluctuations.
  • Gene expression time courses, often from noisy microarray data, present challenges due to sampling variability.
  • Robust statistical modeling is crucial for effective data mining of time course datasets.

Purpose of the Study:

  • To introduce probabilistic timeboxes for robust statistical queries on time course data.
  • To enhance exploratory data analysis capabilities for noisy and fluctuating time series.
  • To enable users to specify complex statistical models with ease.

Main Methods:

  • Developed probabilistic timeboxes, a class of Hidden Markov Models (HMMs).
  • Implemented the method within the Probabilistic Graphical Query Language (pGQL) software package.
  • Evaluated effectiveness using exploratory analysis on a yeast sporulation dataset.

Main Results:

  • Probabilistic timeboxes provide a statistically sound and robust approach to querying time course data.
  • The pGQL implementation facilitates interactive exploration of large datasets.
  • Demonstrated effectiveness on a real-world biological dataset (yeast sporulation).

Conclusions:

  • Introduced a novel approach for dynamic, statistical queries on time course data.
  • The method enhances interactive data exploration for users with varying expertise.
  • Probabilistic timeboxes offer greater expressivity and robustness compared to deterministic timeboxes.