Evidence map›Paper›PMID 33426052›Full record

ArticleBioMed research international2020

An Integrative Computational Approach for the Prediction of Human-

Kais Ghedira, Yosr Hamdi, Abir El Béji, Houcemeddine Othman

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

4 authors at 3 institutions in 2 countries.

Kais GhediraLaboratory of Bioinformatics, Biomathematics and Biostatistics (LR16IPT09), Pasteur Institute of Tunisia, 1002, University of Tunis El Manar, Tunis, Tunisia.ORCID https://orcid.org/0000-0002-3387-6493
Yosr HamdiLaboratory of Biomedical Genomics and Oncogenetics, LR16IPT05, Pasteur Institute of Tunis, University of Tunis El Manar, Tunis, Tunisia.ORCID https://orcid.org/0000-0002-2815-1834
Abir El BéjiLaboratory of Bioinformatics, Biomathematics and Biostatistics (LR16IPT09), Pasteur Institute of Tunisia, 1002, University of Tunis El Manar, Tunis, Tunisia.ORCID https://orcid.org/0000-0002-5293-4337
Houcemeddine OthmanSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0002-1159-6482
Institut Pasteur de Tunis · TNTunis University · TNUniversity of the Witwatersrand · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Host-pathogen molecular cross-talks are critical in determining the pathophysiology of a specific infection. Most of these cross-talks are mediated via protein-protein interactions between the host and the pathogen (HP-PPI). Thus, it is essential to know how some pathogens interact with their hosts to understand the mechanism of infections. Malaria is a life-threatening disease caused by an obligate intracellular parasite belonging to the

Indexed as

Host-Parasite InteractionsPlasmodium falciparumProtein Interaction MapsProtozoan ProteinsHumansMachine LearningMalaria, FalciparumProtein Interaction MappingProteomeProteomicsProteomeProtozoan Proteins

Identifiers

PMID33426052
PMCPMC7771252
OpenAlexW3118154749

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.