Evidence map›Paper›PMID 26448899›Full record

ArticleIEEE ... International Conference on Computational Advances in Bio and Medical Sciences : [proceedings]. IEEE International Conference on Computational Advances in Bio and Medical Sciences2012

The use of graph matching algorithms to identify biochemical substructures in synthetic chemical compounds: Application to metabolomics.

Mai Hamdalla, David Grant, Ion Mandoiu, Dennis Hill, Sanguthevar Rajasekaran, Reda Ammar

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PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE ... International Conference on Computational Advances in Bio and Medical Sciences : [proceedings]. IEEE International Conference on Computational Advances in Bio and Medical Sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mai HamdallaComputer Science and Engineering Department, University of Connecticut, Connecticut, USA.
David GrantPharmaceutical Sciences Department, University of Connecticut, Connecticut, USA.
Ion MandoiuComputer Science and Engineering Department, University of Connecticut, Connecticut, USA.
Dennis HillPharmaceutical Sciences Department, University of Connecticut, Connecticut, USA.
Sanguthevar RajasekaranComputer Science and Engineering Department, University of Connecticut, Connecticut, USA.
Reda AmmarComputer Science and Engineering Department, University of Connecticut, Connecticut, USA.

Funding

Metabolomics Tools for BiomedicineR01GM087714 · NIGMS · UNIVERSITY OF CONNECTICUT STORRS · PI GRANT, DAVID FRANKLIN · 2010 to 2018
$3.1M
Efficient Algorithms for Motif SearchR01LM010101 · NLM · UNIVERSITY OF CONNECTICUT STORRS · PI RAJASEKARAN, SANGUTHEVAR · 2010 to 2013
$1.4M
NIGMS NIH HHS R01 GM087714NLM NIH HHS R01 LM010101
6 · The paper itself

Abstract

Metabolomics is a rapidly growing field studying the small-molecule metabolite profile of a biological organism. Studying metabolism has a potential to contribute to biomedical research as well as drug discovery. One of the current challenges in metabolomics is the identification of unknown metabolites as existing chemical databases are incomplete. We present a novel way of utilizing known mammalian metabolites in an effort to identify unknown ones. The system relies on a mammalian scaffolds database to aid the classification process. The results show that 96% of the mammalian compounds were identified as truly mammalian in a leave-one-out experiment. The system was also tested with a random set of synthetic compounds, downloaded from ChemBridge and ChemSynthesis databases. The system was able to eliminate 54% of the set, leaving 46% of the compounds as potentially unknown mammalian metabolites.

Indexed as

classificationmass spectrometrymetabolitesmetabolomicsmolecular similaritystructure matching

Identifiers

PMID26448899
PMCPMC4593623

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.