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Related Concept Videos

pre-mRNA Processing02:01

pre-mRNA Processing

57.6K
In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a “cap” to the 5’ end of the growing transcript. In this process, a 5’ phosphate is replaced by modified guanosine that has a methyl group attached to it (7-Methyl...
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Pre-mRNA Processing: Modification of pre-mRNA Ends01:35

Pre-mRNA Processing: Modification of pre-mRNA Ends

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In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a cap to the 5' end of the growing transcript. In this process, a 5' phosphate is replaced by modified guanosine that has a methyl group attached (7-methyl guanosine). This 5' cap helps...
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Chromatin Structure Regulates pre-mRNA Processing02:41

Chromatin Structure Regulates pre-mRNA Processing

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In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
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Pre-mRNA Processing: RNA Splicing01:36

Pre-mRNA Processing: RNA Splicing

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¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
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¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR01:15

¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR

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The axial and equatorial protons in cyclohexane can be distinguished by performing a variable-temperature NMR experiment. In this process, except for one proton, the remaining eleven protons are replaced by deuterium. The deuterium substitution avoids the possible peak splitting caused by the spin-spin coupling between the adjacent protons. The remaining proton flips between the axial and equatorial positions.
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Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
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PepsNMR for 1H NMR metabolomic data pre-processing.

Manon Martin1, Benoît Legat2, Justine Leenders3

  • 1Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA/IMMAQ), Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium.

Analytica Chimica Acta
|April 8, 2018
PubMed
Summary

Data pre-processing is crucial for accurate 1H NMR spectral analysis in metabolomics. The PepsNMR R package enhances information recovery and predictive power, offering reproducible and automated solutions beyond standard proprietary software.

Keywords:
(1)H nuclear magnetic resonanceData pre-processingMetabolomicsPre-processing quality evaluationR package

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Area of Science:

  • Analytical Chemistry
  • Metabolomics
  • Bioinformatics

Background:

  • 1H NMR spectroscopy is vital for biological sample analysis.
  • Data pre-processing significantly impacts the accuracy and robustness of 1H NMR spectral data.
  • Current reliance on proprietary software limits methodological transparency, automation, and objective quality assessment.

Purpose of the Study:

  • To introduce PepsNMR, an R package for comprehensive 1H NMR data pre-processing.
  • To address limitations of proprietary software in metabolomic data analysis.
  • To improve information recovery and predictive power in 1H NMR studies.

Main Methods:

  • Development of the PepsNMR R package, encompassing solvent suppression, internal calibration, phase, baseline, and misalignment corrections, bucketing, and normalization.
  • Methodological evaluation of PepsNMR's routines.
  • Comparative analysis against gold-standard procedures using two metabolomic case studies.

Main Results:

  • PepsNMR demonstrates superior information recovery and predictive power compared to standard methods.
  • The package provides objective and quantitative quality criteria for pre-processing evaluation.
  • PepsNMR offers enhanced workflow processing speed, reproducibility, and flexibility.

Conclusions:

  • PepsNMR provides a robust, reproducible, and automated solution for 1H NMR data pre-processing in metabolomics.
  • The package overcomes drawbacks associated with proprietary software, enabling better data analysis.
  • PepsNMR facilitates maximal information recovery and improved predictive modeling from biological samples.