Evidence map›Paper›PMID 31986158›Full record

ArticlePloS one2020

NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families.

Hyun-Myung Woo, Hyundoo Jeong, Byung-Jun Yoon

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Pairwise Biological Network Alignment Based on Discrete Bat Algorithm.Computational and mathematical methods in medicine · 2021
    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 at 3 institutions in 2 countries.

Hyun-Myung WooDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.ORCID 0000-0002-5997-4059
Hyundoo JeongDepartment of Mechatronics Engineering, Incheon National University, Incheon, Republic of Korea.
Byung-Jun YoonDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.
Incheon National University · KRTexas A&M University · USTexas A&M University System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comparative network analysis provides effective computational means for gaining novel insights into the structural and functional compositions of biological networks. In recent years, various methods have been developed for biological network alignment, whose main goal is to identify important similarities and critical differences between networks in terms of their topology and composition. A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. In this work, we introduce NAPAbench 2-a major update of the original NAPAbench that was introduced in 2012. NAPAbench 2 includes a completely redesigned network synthesis algorithm that can generate protein-protein interaction (PPI) network families whose characteristics closely match those of the latest real PPI networks. Furthermore, the network synthesis algorithm comes with an intuitive GUI that allows users to easily generate PPI network families with an arbitrary number of networks of any size, according to a flexible user-defined phylogeny. In addition, NAPAbench 2 provides updated benchmark datasets-created using the redesigned network synthesis algorithm-which can be used for comprehensive performance assessment of network alignment algorithms and their scalability.

Indexed as

AlgorithmsComputational BiologyDatabases, FactualPhylogenyProtein Interaction Mapping

Identifiers

PMID31986158
PMCPMC6984706
OpenAlexW3002335812

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.