Evidence map›Paper›PMID 32287404›Full record

ArticlePolymer2009

Study of peptide fingerprints of parasite proteins and drug-DNA interactions with Markov-Mean-Energy invariants of biopolymer molecular-dynamic lattice networks.

Lázaro Guillermo Pérez-Montoto, María Auxiliadora Dea-Ayuela, Francisco J Prado-Prado, Francisco Bolas-Fernández, Florencio M Ubeira, Humberto González-Díaz

Open access · bronzeAbstract read
In one paragraph

Article in Polymer, 2009. 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, top 91% of its field
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, 3 citations in OpenAlex.

  1. Review
  2. Article
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 at 3 institutions in 1 country.

Lázaro Guillermo Pérez-MontotoDepartment of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain.
María Auxiliadora Dea-AyuelaDepartamento de Atención Sanitaria, Salud Pública y Sanidad Animal, Facultad CC Experimentales y de La Salud, Universidad CEU Cardenal Herrera, 46113 Moncada (Valencia), Spain.
Francisco J Prado-PradoDepartment of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain.
Francisco Bolas-FernándezDepartment of Parasitology, Faculty of Pharmacy, Complutense University, 28040 Madrid, Spain.
Florencio M UbeiraDepartment of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain.
Humberto González-DíazDepartment of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain.
Universidade de Santiago de Compostela · ESUniversidad Cardenal Herrera CEU · ESUniversidad Complutense de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the advent of Molecular Dynamics (MD) in biopolymers science with the study by Karplus et al. on protein dynamics, MD has become the by foremost well established, computational technique to investigate structure and function of biomolecules and their respective complexes and interactions. The analysis of the MD trajectories (MDTs) remains, however, the greatest challenge and requires a great deal of insight, experience, and effort. Here, we introduce a new class of invariants for MDTs based on the spatial distribution of Mean-Energy values

Indexed as

Graph theoryLeishmaniaParasite proteomics

Identifiers

PMID32287404
PMCPMC7111648
OpenAlexW1984941037

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.