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CORRECTION article

Front. Genet., 18 June 2024
Sec. Computational Genomics
Volume 15 - 2024 | https://doi.org/10.3389/fgene.2024.1440665

Corrigendum: Bipartite networks represent causality better than simple networks: Evidence, algorithms, and applications

This article is a correction to:

  1. Bipartite networks represent causality better than simple networks: evidence, algorithms, and applications

    1. Read original article
Bingran ShenBingran Shen1Gloria M. CoruzziGloria M. Coruzzi2Dennis Shasha Dennis Shasha1*
  • 1Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, United States
  • 2Center for Genomics and Systems Biology, Department of Biology, New York University, New York, United States

A Corrigendum on
Bipartite networks represent causality better than simple networks: evidence, algorithms, and applications

by Shen, B., Coruzzi, G., and Shasha, D. (2024). Front. Genet. 15:1371607. doi: 10.3389/fgene.2024.1371607

In the published article, an Author name was incorrectly written as “Gloria Curozzi.” The corrected author name should read as “Gloria M. Coruzzi.”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: RNA sequencing, gene regulatory network, causal inference, random forest, bipartite network

Citation: Shen B, Coruzzi GM and Shasha D (2024) Corrigendum: Bipartite networks represent causality better than simple networks: Evidence, algorithms, and applications. Front. Genet. 15:1440665. doi: 10.3389/fgene.2024.1440665

Received: 29 May 2024; Accepted: 31 May 2024;
Published: 18 June 2024.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2024 Shen, Coruzzi and Shasha. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Dennis Shasha, shasha@cims.nyu.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.