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Find video protocols related to scientific articles indexed in Pubmed.
HAMMER: Automated operation of Mass Frontier to construct in-silico mass spectral fragmentation libraries.
Bioinformatics
PUBLISHED: 12-11-2013
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Experimental MS(n) mass spectral libraries currently do not adequately cover chemical space. This limits the robust annotation of metabolites in metabolomics studies of complex biological samples. In-silico fragmentation libraries would improve the identification of compounds from experimental multi-stage fragmentation data when experimental reference data is unavailable. Here we present a freely-available software package to automatically control Mass Frontier software to construct in-silico mass spectral libraries, and to perform spectral matching. Based on two case studies we have demonstrated that HAMMER allows researchers to generate in-silico mass spectral libraries in an automated and high-throughput fashion with little or no human intervention required.
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Determination of ion structures in structurally related compounds using precursor ion fingerprinting.
J. Am. Soc. Mass Spectrom.
PUBLISHED: 08-29-2009
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Structurally-related alkaloids were analyzed by electrospray ionization/multiple stage mass spectrometry (ESI/MS(n)) at varying collision energies to demonstrate a conceptual algorithm, precursor ion fingerprinting (PIF). PIF is a new approach for interpreting and library-searching ESI mass spectra predicated on the precursor ions of structurally-related compounds and their matching product ion spectra. Multiple-stage mass spectra were compiled and constructed into "spectral trees" that illustrated the compounds product ion spectra in their respective mass spectral stages. The precursor ions of these alkaloids were characterized and their spectral trees incorporated into an MS(n) library. These data will be used to construct a universal, searchable, and transferable library of MS(n) spectra. In addition, PIF will generate a proposed structural arrangement utilizing previously characterized ion structures, which will assist in the identification of unknown compounds.
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Fragmentation trees for the structural characterisation of metabolites.
Rapid Commun. Mass Spectrom.
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Metabolite identification plays a crucial role in the interpretation of metabolomics research results. Due to its sensitivity and widespread implementation, a favourite analytical method used in metabolomics is electrospray mass spectrometry. In this paper, we demonstrate our results in attempting to incorporate the potentials of multistage mass spectrometry into the metabolite identification routine. New software tools were developed and implemented which facilitate the analysis of multistage mass spectra and allow for efficient removal of spectral artefacts. The pre-processed fragmentation patterns are saved as fragmentation trees. Fragmentation trees are characteristic of molecular structure. We demonstrate the reproducibility and robustness of the acquisition of such trees on a model compound. The specificity of fragmentation trees allows for distinguishing structural isomers, as shown on a pair of isomeric prostaglandins. This approach to the analysis of the multistage mass spectral characterisation of compounds is an important step towards formulating a generic metabolite identification method.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.