Evidence map›Paper›PMID 35892929›Full record

ArticleBiotech (Basel (Switzerland))2022

Challenges and Limitations of Biological Network Analysis.

Marianna Milano, Giuseppe Agapito, Mario Cannataro

Abstract read
In one paragraph

Article in Biotech (Basel (Switzerland)), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  7. Discovering subnetworks in SBML models.Bioinformatics (Oxford, England) · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Complex Networks and Interacting Particle Systems.Entropy (Basel, Switzerland) · 2023
    Article
  15. Article
  16. Article
  17. 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.

Marianna MilanoDepartment of Medical and Clinical Surgery, University Magna Græcia, 88100 Catanzaro, Italy.ORCID 0000-0003-1561-725X
Giuseppe AgapitoData Analytics Research Center, University Magna Græcia, 88100 Catanzaro, Italy.ORCID 0000-0003-2868-7732
Mario CannataroDepartment of Medical and Clinical Surgery, University Magna Græcia, 88100 Catanzaro, Italy.ORCID 0000-0003-1502-2387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-Throughput technologies are producing an increasing volume of data that needs large amounts of data storage, effective data models and efficient, possibly parallel analysis algorithms. Pathway and interactomics data are represented as graphs and add a new dimension of analysis, allowing, among other features, graph-based comparison of organisms' properties. For instance, in biological pathway representation, the nodes can represent proteins, RNA and fat molecules, while the edges represent the interaction between molecules. Otherwise, biological networks such as Protein-Protein Interaction (PPI) Networks, represent the biochemical interactions among proteins by using nodes that model the proteins from a given organism, and edges that model the protein-protein interactions, whereas pathway networks enable the representation of biochemical-reaction cascades that happen within the cells or tissues. In this paper, we discuss the main models for standard representation of pathways and PPI networks, the data models for the representation and exchange of pathway and protein interaction data, the main databases in which they are stored and the alignment algorithms for the comparison of pathways and PPI networks of different organisms. Finally, we discuss the challenges and the limitations of pathways and PPI network representation and analysis. We have identified that network alignment presents a lot of open problems worthy of further investigation, especially concerning pathway alignment.

Indexed as

biological pathwayslocal and global alignmentnetworks alignmentprotein–protein interaction

Identifiers

PMID35892929
PMCPMC9326688

What OpenQuestion holds

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Registered trials

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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.