Evidence map›Paper›PMID 29854407›Full record

ArticleJournal of complex networks2017

Generating Bipartite Networks with a Prescribed Joint Degree Distribution.

Asma Azizi, Jeremy Dewar, Tong Wu, James M Hyman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of complex networks, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. What makes a reaction network "chemical"?Journal of cheminformatics · 2022
    Article
  2. 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

4 authors.

Asma AziziDepartment of Mathematics, Tulane University, New Orleans, LA 70118, USA.
Jeremy DewarDepartment of Mathematics, Tulane University, New Orleans, LA 70118, USA.
Tong WuDepartment of mathematics, North Carolina State University, Raleigh, NC 27695, USA.
James M HymanDepartment of Mathematics, Tulane University, New Orleans, LA 70118, USA.

Funding

Quantifying Model Uncertainty for Forecasting the Spread of Infectious DiseasesU01GM097658 · NIGMS · LOS ALAMOS NAT SECTY-LOS ALAMOS NAT LAB · PI DEL VALLE, SARA · 2011 to 2015
$3.3M
A new approach to controlling chlamydia transmission in young peopleR01HD086794 · NICHD · TULANE UNIVERSITY OF LOUISIANA · PI KISSINGER, PATRICIA J · 2016 to 2020
$2.9M
NICHD NIH HHS R01 HD086794NIGMS NIH HHS U01 GM097658
6 · The paper itself

Abstract

We describe a class of new algorithms to construct bipartite networks that preserves a prescribed degree and joint-degree (degree-degree) distribution of the nodes. Bipartite networks are graphs that can represent real-world interactions between two disjoint sets, such as actor-movie networks, author-article networks, co-occurrence networks, and heterosexual partnership networks. Often there is a strong correlation between the degree of a node and the degrees of the neighbors of that node that must be preserved when generating a network that reflects the structure of the underling system. Our bipartite 2

Indexed as

2K algorithm34K3035K5735Q8092D25B2K algorithmBipartite random networkBJD matrixdk network generation algorithmJDM matrixJoint-degree distribution

Identifiers

PMID29854407
PMCPMC5972839

What OpenQuestion holds

Textmetadata
LicenceTDM
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.