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Related Concept Videos

Translation01:31

Translation

155.7K
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...
155.7K
Translation01:31

Translation

17.6K
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
Proteins are...
17.6K
Initiation of Translation02:33

Initiation of Translation

38.4K
Initiating translation is complex because it involves multiple molecules. Initiator tRNA, ribosomal subunits, and eukaryotic initiation factors (eIFs) are all required to assemble on the initiation codon of mRNA. This process consists of several steps that are mediated by different eIFs.
First, the initiator tRNA must be selected from the pool of elongator tRNAs by eukaryotic initiation factor 2 (eIF2). The initiator tRNA (Met-tRNAi) has conserved sequence elements including modified bases at...
38.4K
Termination of Translation01:44

Termination of Translation

27.5K
The large ribosomal subunit has several important structures essential to translation. These include the peptidyl transferase center (PTC) - which is the site where the peptide bond is formed - and a large, internal, water-filled tube through which the nascent polypeptide moves. This latter structure is called the Peptide Exit Tunnel, and it begins at the PTC and spans the body of the large ribosomal subunit. During translation, as the nascent polypeptide chain is synthesized, it passes through...
27.5K
Termination of Translation01:44

Termination of Translation

6.6K
6.6K
Improving Translational Accuracy02:07

Improving Translational Accuracy

14.1K
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...
14.1K

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Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
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Query Translation Between AQL and CQL.

Georg Fette1,2, Mathias Kaspar2, Leon Liman1

  • 1Chair of Computer Science 6, University of Würzburg, Würzburg, Germany.

Studies in Health Technology and Informatics
|August 24, 2019
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Summary
This summary is machine-generated.

This study introduces a query translation method to connect multiple electronic health record data aggregation systems for clinical research. It addresses syntax and data model differences, enabling better data sharing across institutions.

Keywords:
Data WarehousingElectronic Health RecordsInformation Systems

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Area of Science:

  • Health Informatics
  • Clinical Research Informatics
  • Data Science

Background:

  • Secondary use of electronic health records (EHRs) via data aggregation systems (DAS) supports clinical research.
  • Connecting multiple DASs across institutions increases patient data volume but faces challenges.
  • Syntactical differences in query interfaces and data models hinder DAS interoperability.

Purpose of the Study:

  • To present an approach for translating queries between different DAS query languages.
  • To overcome syntactical and data model differences between DASs for research networks.
  • To enable seamless data aggregation from diverse EHR systems.

Main Methods:

  • Developed a query translation approach between openEHR's Archetype Query Language (AQL) and Clinical Quality Language (CQL).
  • Focused on translating queries expressible in both AQL and CQL.
  • Validated the feasibility of bidirectional query translation.

Main Results:

  • The proposed approach successfully translates queries between AQL and CQL.
  • Demonstrated feasibility for the subset of queries expressible in both languages.
  • Facilitates interoperability between DASs using different query languages.

Conclusions:

  • The developed translation method effectively addresses syntactic and data model heterogeneity in DASs.
  • This approach enhances the feasibility of connecting multiple DASs to research networks.
  • Enables more robust and scalable clinical research through improved EHR data aggregation.