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Related Concept Videos

Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
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...
Inductive Effects on Chemical Shift: Overview01:27

Inductive Effects on Chemical Shift: Overview

The protons in unsubstituted alkanes are strongly shielded with chemical shifts below 1.8 ppm. Methine, methylene, and methyl protons appear at approximately 1.7, 1.2 and 0.7 ppm, while the proton signal from methane appears at 0.23 ppm. An electronegative substituent, such as chlorine, withdraws the electron density from the protons, increasing their chemical shift. Progressive substitution of the hydrogens in methane by chlorine shifts the proton signals increasingly downfield, to 3.05 ppm in...
Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

The non-destructive nature and ability to provide valuable chemical information make IR spectroscopy a versatile technique with broad applications in various scientific and industrial fields. IR spectroscopy is commonly used to identify and characterize organic and inorganic compounds. It provides information about the functional groups present in a molecule and the bonding between atoms. This helps in the structural elucidation of compounds during organic synthesis, pharmaceutical research,...
NMR Spectroscopy: Chemical Shift Overview01:15

NMR Spectroscopy: Chemical Shift Overview

The position of the absorption signal of a sample is reported relative to the position of the signal of tetramethylsilane (TMS), which is added as an internal reference while recording spectra. The difference between the absorption frequencies of the sample and TMS (in Hz) is divided by the spectrometer operating frequency (in MHz) to obtain a dimensionless quantity called the chemical shift. It is reported on the δ (delta) scale and expressed in parts per million.
For instance, the proton...

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Related Experiment Video

Updated: May 14, 2026

Multimodal Nonlinear Hyperspectral Chemical Imaging Using Line-Scanning Vibrational Sum-Frequency Generation Microscopy
08:49

Multimodal Nonlinear Hyperspectral Chemical Imaging Using Line-Scanning Vibrational Sum-Frequency Generation Microscopy

Published on: December 1, 2023

Multi-view spectral clustering and its chemical application.

Adeshola A Adefioye1, Xinhai Liu, Bart De Moor

  • 1Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven, Belgium. tunde.adefioye@esat.kuleuven.be

International Journal of Computational Biology and Drug Design
|February 23, 2013
PubMed
Summary

This study introduces a novel tensor-based spectral clustering algorithm for chemical compound analysis. The method effectively groups diverse chemical compounds, revealing potential chemogenomic relationships for medicinal chemistry applications.

Related Experiment Videos

Last Updated: May 14, 2026

Multimodal Nonlinear Hyperspectral Chemical Imaging Using Line-Scanning Vibrational Sum-Frequency Generation Microscopy
08:49

Multimodal Nonlinear Hyperspectral Chemical Imaging Using Line-Scanning Vibrational Sum-Frequency Generation Microscopy

Published on: December 1, 2023

Area of Science:

  • Chemoinformatics
  • Computational Chemistry
  • Data Science

Background:

  • Clustering is a key unsupervised learning technique in chemoinformatics for analyzing chemical compounds.
  • Understanding relationships between compounds aids in predicting biological, chemical, and physical properties.
  • Existing methods may not fully leverage multi-source data for robust chemical clustering.

Purpose of the Study:

  • To present a novel, improved spectral clustering algorithm tailored for chemical compound data.
  • To apply a tensor-based, multi-view approach for enhanced compound clustering.
  • To demonstrate the value of this method for the medicinal chemistry community.

Main Methods:

  • Utilized tensor-based spectral clustering, a multi-view approach.
  • Applied the algorithm to chemical compound datasets, including GSK-Chembl Malaria and Zinc.
  • Evaluated the robustness and statistical significance of the clustering results.

Main Results:

  • The tensor-based spectral clustering algorithm yielded chemically appropriate and statistically significant results.
  • Robust performance was observed on mid-size chemical compound sets.
  • Demonstrated successful clustering of compounds with highly dissimilar chemotypes.

Conclusions:

  • The developed tensor-based multi-view spectral clustering method is valuable for medicinal chemistry.
  • The algorithm's ability to group diverse chemotypes suggests potential in chemogenomics.
  • This approach offers a powerful tool for exploring chemical space and drug discovery.