Evidence map›Paper›PMID 19513596›Full record

ReviewDie Naturwissenschaften2009

A review on molecular topology: applying graph theory to drug discovery and design.

José María Amigó, Jorge Gálvez, Vincent M Villar

Abstract readReview
PubMed Publisher
In one paragraph

Review in Die Naturwissenschaften, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

3 authors.

José María AmigóOperation Research Center, Miguel Hernández University, Elche, Alicante, Spain. jm.amigo@umh.es
Jorge Gálvez
Vincent M Villar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular topology is an application of graph theory and statistics in fields like chemistry, biology, and pharmacology, in which the molecular structure matters. Its scope is the topological characterization of molecules by means of numerical invariants, called topological indices, which are the main ingredients of the molecular topological models. These are statistical models that are instrumental in the discovery of new applications of naturally occurring molecules, as well as in the design of synthetic molecules with specific chemical, biological, or pharmacological properties. In this review, we focus on pharmacology, which is a novel field of application of molecular topology. Besides summarizing some recent developments, we also seek to bring closer this interesting biomedical application of mathematics to an interdisciplinary readership.

Indexed as

Molecular StructureComputer GraphicsDrug DiscoveryMathematicsModels, MolecularModels, TheoreticalQuantum Theory

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.