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Related Concept Videos

¹H NMR: Complex Splitting01:13

¹H NMR: Complex Splitting

A proton M that is coupled to a proton X results in doublet signals for M. However, NMR-active nuclei can be simultaneously coupled to more than one nonequivalent nucleus. When M is coupled to a second proton A, such as in styrene oxide, each peak in the doublet is split into another doublet.
Splitting diagrams or splitting tree diagrams are routinely used to depict such complex couplings. While drawing splitting diagrams, the splitting with the larger coupling constant is usually applied first.
¹H NMR Signal Integration: Overview00:58

¹H NMR Signal Integration: Overview

The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a soft-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.To...
Mass Spectrometry: Long-Chain Alkane Fragmentation01:18

Mass Spectrometry: Long-Chain Alkane Fragmentation

The molecular ions of linear alkanes prefer to fragment at the carbon-carbon bond away from the end of the chain since the cleavage of an inner bond creates a stable carbocation and a stable radical. Consequently, the mass signals of linear alkanes feature intense peaks in the middle of the mass-to-charge ratio plot with weaker peaks on either end. The fragmentation of each carbon-carbon bond with the release of a methyl group in each splitting leads to prominent peaks in the mass spectra...

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Related Experiment Video

Updated: Jun 23, 2026

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline
11:09

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline

Published on: January 5, 2017

Validation of an STR peak area model.

Robert G Cowell1

  • 1Faculty of Actuarial Science and Insurance, Sir John Cass Business School, City University London, 106 Buhnill Row, London EC1Y 8TZ, UK. rgc@city.ac.uk

Forensic Science International. Genetics
|May 6, 2009
PubMed
Summary

This study evaluates gamma distributions for analyzing DNA mixture peak areas from polymerase chain-reaction (PCR) amplification. The gamma model is effective unless allelic dropout, common in low template DNA, becomes a significant issue.

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Analysis of SEC-SAXS data via EFA deconvolution and Scatter
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Analysis of SEC-SAXS data via EFA deconvolution and Scatter

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Last Updated: Jun 23, 2026

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline
11:09

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline

Published on: January 5, 2017

Analysis of SEC-SAXS data via EFA deconvolution and Scatter
10:59

Analysis of SEC-SAXS data via EFA deconvolution and Scatter

Published on: January 28, 2021

Area of Science:

  • Forensic Science
  • Statistical Genetics
  • Molecular Biology

Background:

  • DNA mixture analysis relies on allele peak areas from polymerase chain-reaction (PCR) amplification to infer contributor proportions.
  • Predicting unknown genetic profiles from mixtures is challenging due to the stochastic nature of PCR peak areas.
  • Probabilistic models, such as those using gamma distributions, have been proposed to address these challenges.

Purpose of the Study:

  • To statistically analyze the validity of using gamma distributions for modeling DNA mixture peak area data.
  • To assess the performance of the gamma distribution assumption under varying conditions, particularly concerning allelic dropout.

Main Methods:

  • Statistical analysis of synthetic peak area values generated by a separate PCR amplification simulation model.
  • Testing the goodness-of-fit of the gamma distribution assumption against simulated data.
  • Evaluating model performance with and without simulated allelic dropout.

Main Results:

  • The gamma distribution assumption provides a good model for peak area values when allelic dropout is absent.
  • The performance of the gamma distribution model degrades significantly as the rate of allelic dropout increases.
  • This degradation is particularly pronounced in scenarios mimicking Low Copy Template (LCT) amplifications.

Conclusions:

  • Gamma distributions are a useful tool for analyzing DNA mixtures amplified by PCR, especially in the absence of allelic dropout.
  • The presence of allelic dropout, common in forensic samples like LCT DNA, compromises the accuracy of the gamma distribution model.
  • Further research is needed to develop or refine models that robustly handle allelic dropout in DNA mixture analysis.