Evidence map›Paper›PMID 37260512›Full record

ArticleNAR genomics and bioinformatics2023

Bacterial Wars-a tool for the prediction of bacterial predominance based on network analysis measures.

Anastasis Oulas, George Minadakis, Margarita Zachariou, Marios Tomazou, Alexios Vlamis-Gardikas, George M Spyrou

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Anastasis OulasCyprus Institute of Neurology and Genetics, Bioinformatics Department, 6 International Airport Avenue, 2370 Nicosia, Cyprus, P.O.Box 23462, 1683, Nicosia, Cyprus.ORCID https://orcid.org/0000-0002-9350-7577
George MinadakisCyprus Institute of Neurology and Genetics, Bioinformatics Department, 6 International Airport Avenue, 2370 Nicosia, Cyprus, P.O.Box 23462, 1683, Nicosia, Cyprus.ORCID https://orcid.org/0000-0002-7752-2208
Margarita ZachariouCyprus Institute of Neurology and Genetics, Bioinformatics Department, 6 International Airport Avenue, 2370 Nicosia, Cyprus, P.O.Box 23462, 1683, Nicosia, Cyprus.
Marios TomazouCyprus Institute of Neurology and Genetics, Bioinformatics Department, 6 International Airport Avenue, 2370 Nicosia, Cyprus, P.O.Box 23462, 1683, Nicosia, Cyprus.
Alexios Vlamis-GardikasDepartment of Chemistry, Division of Organic Chemistry, Biochemistry and Natural Products, University of Patras, 26504, Rion, Greece.ORCID https://orcid.org/0000-0002-2470-3363
George M SpyrouCyprus Institute of Neurology and Genetics, Bioinformatics Department, 6 International Airport Avenue, 2370 Nicosia, Cyprus, P.O.Box 23462, 1683, Nicosia, Cyprus.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial Wars (BW) is a network-based tool that applies a two-step pipeline to display information on the competition of bacterial species found in the same microbiome. It utilizes antimicrobial peptide (AMP) sequence similarities to obtain a relationship between species. The working hypothesis (putative AMP defense) is that friendly species share sequence similarity among the putative AMPs of their proteomes and are therefore immune to their AMPs. This may not happen in competing bacterial species with dissimilar putative AMPs. Similarities in the putative AMPs of bacterial proteomes may be thus used to predict predominance. The tool provides insights as to which bacterial species are more likely to 'die' in a competing environmental niche.

Identifiers

PMID37260512
PMCPMC10227370

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.