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Related Concept Videos

Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Translation01:31

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Translation01:31

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Translational Regulation01:29

Translational Regulation

Translational regulation in prokaryotes ensures efficient protein synthesis by controlling ribosome access to mRNA. This regulation is mediated by secondary RNA structures, including translational riboswitches, RNA thermometers, and small RNAs (sRNAs), which respond to intracellular and environmental signals to modulate gene expression.Translational RiboswitchesRiboswitches in the leader region of mRNAs can regulate translation by altering the accessibility of the Shine-Dalgarno (SD) sequence,...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

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Related Experiment Video

Updated: May 13, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

A meta-composite software development approach for translational research.

Rajani S Sadasivam1, Murat M Tanik

  • 1Division of Health Informatics and Implementation Science, Quantitative Health Sciences, University of Massachusetts Medical School, 55 Lake Avenue N, Worcester, MA, 01655-0002, USA, rajani.sadasivam@umassmed.edu.

Journal of Medical Systems
|March 19, 2013
PubMed
Summary
This summary is machine-generated.

Translational researchers need better software tools. This study introduces a new meta-composite software development approach, empowering researchers to lead tool integration and model complex interactions for improved efficiency.

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Analysis of Translation in the Developing Mouse Brain using Polysome Profiling
08:38

Analysis of Translation in the Developing Mouse Brain using Polysome Profiling

Published on: May 22, 2021

Related Experiment Videos

Last Updated: May 13, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

Analysis of Translation in the Developing Mouse Brain using Polysome Profiling
08:38

Analysis of Translation in the Developing Mouse Brain using Polysome Profiling

Published on: May 22, 2021

Area of Science:

  • Biomedical informatics
  • Software engineering
  • Translational science

Background:

  • Translational researchers operate in data-intensive, dynamic environments requiring diverse tools.
  • Current software solutions are fragmented and inefficient for integrating these tools.
  • A need exists for adaptable software development supporting dynamic research needs.

Purpose of the Study:

  • To propose a novel meta-composite software development approach for translational research.
  • To enhance the integration and adaptability of disparate research tools.
  • To empower researchers in the software development process.

Main Methods:

  • Developed a concept-map and agent-based meta-composite software development approach.
  • Leveraged composite services development principles for system integration.
  • Focused on user-led process modeling and incorporating complex user interactions.

Main Results:

  • Demonstrated the feasibility of the proposed approach with a real-world translational research case.
  • Showcased a method enabling researchers, not just technicians, to lead process modeling.
  • Enabled the modeling of intricate user interactions within research workflows.

Conclusions:

  • The proposed concept-map and agent-based approach effectively addresses the need for meta-composite software development in translational research.
  • Empowering researchers in process modeling enhances efficiency and accuracy.
  • The approach overcomes limitations of current tools by integrating complex user interactions.