Evidence map›Paper›PMID 34706638›Full record

ArticleBMC bioinformatics2021

ANAT 3.0: a framework for elucidating functional protein subnetworks using graph-theoretic and machine learning approaches.

L F Signorini, T Almozlino, R Sharan

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Signing protein-protein interaction networks.Bioinformatics (Oxford, England) · 2026
    Article
  2. Article
  3. Article
  4. D'or: deep orienter of protein-protein interaction networks.Bioinformatics (Oxford, England) · 2024
    Article
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  6. Article
  7. 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

3 authors.

L F SignoriniBlavatnik School of Computer Science, Tel Aviv University, 6997801, Tel Aviv, Israel.
T AlmozlinoBlavatnik School of Computer Science, Tel Aviv University, 6997801, Tel Aviv, Israel.
R SharanBlavatnik School of Computer Science, Tel Aviv University, 6997801, Tel Aviv, Israel. roded@tauex.tau.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundANAT is a Cytoscape plugin for the inference of functional protein-protein interaction networks in yeast and human. It is a flexible graphical tool for scientists to explore and elucidate the protein-protein interaction pathways of a process under study.

resultsHere we present ANAT3.0, which comes with updated PPI network databases of 544,455 (human) and 155,504 (yeast) interactions, and a new machine-learning layer for refined network elucidation. Together they improve network reconstruction to more than twofold increase in the quality of reconstructing known signaling pathways from KEGG.

conclusionsANAT3.0 includes improved network reconstruction algorithms and more comprehensive protein-protein interaction networks than previous versions. ANAT is available for download on the Cytoscape Appstore and at https://www.cs.tau.ac.il/~bnet/ANAT/ .

Indexed as

ProteinsSoftwareAlgorithmsHumansMachine LearningProtein Interaction MappingProtein Interaction MapsProteinsInteractomicsMachine learningNetwork biologyNetwork inferenceProtein–protein interaction networksSystems biology

Identifiers

PMID34706638
PMCPMC8555137

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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.