Evidence map›Paper›PMID 31485005›Full record

ArticleScientific reports2019

CDAP: An Online Package for Evaluation of Complex Detection Methods.

Ali M A Maddi, Fatemeh Ahmadi Moughari, Mohammad Mehdi Balouchi, Changiz Eslahchi

Abstract read
In one paragraph

Article in Scientific reports, 2019. 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
–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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Ali M A MaddiSchool of biological sciences, Institute for research in fundamental sciences(IPM), Tehran, 193955746, Iran.
Fatemeh Ahmadi MoughariDepartment of Computer Sciences, Faculty of Mathematics, Shahid Beheshti University, G.C., Tehran, 1983963113, Iran.
Mohammad Mehdi BalouchiDepartment of Computer Sciences, Faculty of Mathematics, Shahid Beheshti University, G.C., Tehran, 1983963113, Iran.
Changiz EslahchiSchool of biological sciences, Institute for research in fundamental sciences(IPM), Tehran, 193955746, Iran. Ch-Eslahchi@sbu.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methods for detecting protein complexes from protein-protein interaction networks are of the most critical computational approaches. Numerous methods have been proposed in this area. Therefore, it is necessary to evaluate them. Various metrics have been proposed in order to compare these methods. Nevertheless, it is essential to define new metrics that evaluate methods both qualitatively and quantitatively. In addition, there is no tool for the comprehensive comparison of such methods. In this paper, a new criterion is introduced that can fully evaluate protein complex detection algorithms. We introduce CDAP (Complex Detection Analyzer Package); an online package for comparing protein complex detection methods. CDAP can quickly rank the performance of methods based on previously defined as well as newly introduced criteria in various settings (4 PPI datasets and 3 gold standards). It has the capability of integrating various methods and apply several filterings on the results. CDAP can be easily extended to include new datasets, gold standards, and methods. Furthermore, the user can compare the results of a custom method with the results of existing methods. Thus, the authors of future papers can use CDAP for comparing their method with the previous ones. A case study is done on YGR198W, a well-known protein, and the detected clusters are compared to the known complexes of this protein.

Indexed as

AlgorithmsComputational BiologyDatabases, ProteinProtein Interaction MappingProteinsSoftwareProteins

Identifiers

PMID31485005
PMCPMC6726630

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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.