Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

General Transcription Factors01:30

General Transcription Factors

6.5K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
6.5K
Transcription Factors02:16

Transcription Factors

81.9K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
81.9K
The Eukaryotic Promoter Region02:40

The Eukaryotic Promoter Region

18.4K
The eukaryotic promoter region is a segment of DNA located upstream of a gene. It contains an RNA polymerase binding site, a transcription start site, and several cis-regulatory sequences.  The proximal promoter region is located in the vicinity of the gene and has cis-regulatory sequences and the core promoter. The core promoter is the binding site for RNA polymerase and is usually located between -35 and +35 nucleotides from the transcription start site. The distal promoter regions are...
18.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

MGAPep: LLM-Augmented Multimodal Graph Attention for Protein-Peptide Binding Site Prediction and Cross-Domain Transfer.

IEEE journal of biomedical and health informatics·2026
Same author

ReMol: A Chemical Reaction Knowledge-guided Self-supervised Molecular Image Representation Learning Framework.

IEEE journal of biomedical and health informatics·2026
Same author

Learnable dendrite neural P systems and applications in survival prediction of glioblastoma patients.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

A systematic review of molecular representation learning foundation models.

Briefings in bioinformatics·2026
Same author

MaskMol: knowledge-guided molecular image pre-training framework for activity cliffs with pixel masking.

BMC biology·2025
Same author

Introduction.

International journal of neural systems·2025

Related Experiment Video

Updated: Dec 15, 2025

Methods to Discover Alternative Promoter Usage and Transcriptional Regulation of Murine Bcrp1
11:02

Methods to Discover Alternative Promoter Usage and Transcriptional Regulation of Murine Bcrp1

Published on: May 27, 2016

8.4K

Monodirectional Tissue P Systems With Promoters.

Bosheng Song, Xiangxiang Zeng, Min Jiang

    IEEE Transactions on Cybernetics
    |July 11, 2020
    PubMed
    Summary
    This summary is machine-generated.

    Monodirectional tissue P systems with promoters, inspired by cellular transport, demonstrate significant computational power. These bio-inspired systems can solve complex problems like the Boolean satisfiability problem, even with directional communication constraints.

    More Related Videos

    An Efficient Strategy for Generating Tissue-specific Binary Transcription Systems in Drosophila by Genome Editing
    10:01

    An Efficient Strategy for Generating Tissue-specific Binary Transcription Systems in Drosophila by Genome Editing

    Published on: September 19, 2018

    9.4K
    Applying an Inducible Expression System to Study Interference of Bacterial Virulence Factors with Intracellular Signaling
    08:51

    Applying an Inducible Expression System to Study Interference of Bacterial Virulence Factors with Intracellular Signaling

    Published on: June 25, 2015

    9.5K

    Related Experiment Videos

    Last Updated: Dec 15, 2025

    Methods to Discover Alternative Promoter Usage and Transcriptional Regulation of Murine Bcrp1
    11:02

    Methods to Discover Alternative Promoter Usage and Transcriptional Regulation of Murine Bcrp1

    Published on: May 27, 2016

    8.4K
    An Efficient Strategy for Generating Tissue-specific Binary Transcription Systems in Drosophila by Genome Editing
    10:01

    An Efficient Strategy for Generating Tissue-specific Binary Transcription Systems in Drosophila by Genome Editing

    Published on: September 19, 2018

    9.4K
    Applying an Inducible Expression System to Study Interference of Bacterial Virulence Factors with Intracellular Signaling
    08:51

    Applying an Inducible Expression System to Study Interference of Bacterial Virulence Factors with Intracellular Signaling

    Published on: June 25, 2015

    9.5K

    Area of Science:

    • * Computational biology
    • * Theoretical computer science
    • * Bio-inspired computing

    Background:

    • * Tissue P systems are bio-inspired computational models.
    • * Promoters regulate object exchange between regions in tissue P systems.
    • * Cellular biology features molecule transport from high to low concentration across membranes.

    Purpose of the Study:

    • * To introduce and investigate monodirectional tissue P systems with promoters.
    • * To explore their computational power and characteristics.
    • * To analyze their efficiency in solving problems like the Boolean satisfiability problem.

    Main Methods:

    • * Theoretical analysis of monodirectional tissue P systems.
    • * Examination of symport rules, cell count, and promoter usage.
    • * Investigation of maximally parallel and flat maximally parallel modes.
    • * Incorporation of cell division rules for efficiency analysis.

    Main Results:

    • * Monodirectional tissue P systems can produce finite sets of numbers.
    • * Turing universality is achieved with specific configurations (e.g., two cells, maximal length 2).
    • * Regular sets of natural numbers are characterized under specific conditions.
    • * Efficient solutions for the Boolean satisfiability problem (SAT problem) are provided.

    Conclusions:

    • * Monodirectional tissue P systems remain computationally powerful despite directional constraints.
    • * The incorporation of cell division rules enhances computational efficiency.
    • * These systems offer potential for developing membrane algorithms.