Version 1
: Received: 12 October 2023 / Approved: 12 October 2023 / Online: 12 October 2023 (15:41:56 CEST)
How to cite:
Dutta, S.; Teji, B.; Dutta, S.; Roy, S. NetRA: An IntegratedWeb Platform for Large-Scale Gene Regulatory Network Reconstruction and Analysis. Preprints2023, 2023100820. https://doi.org/10.20944/preprints202310.0820.v1
Dutta, S.; Teji, B.; Dutta, S.; Roy, S. NetRA: An IntegratedWeb Platform for Large-Scale Gene Regulatory Network Reconstruction and Analysis. Preprints 2023, 2023100820. https://doi.org/10.20944/preprints202310.0820.v1
Dutta, S.; Teji, B.; Dutta, S.; Roy, S. NetRA: An IntegratedWeb Platform for Large-Scale Gene Regulatory Network Reconstruction and Analysis. Preprints2023, 2023100820. https://doi.org/10.20944/preprints202310.0820.v1
APA Style
Dutta, S., Teji, B., Dutta, S., & Roy, S. (2023). NetRA: An IntegratedWeb Platform for Large-Scale Gene Regulatory Network Reconstruction and Analysis. Preprints. https://doi.org/10.20944/preprints202310.0820.v1
Chicago/Turabian Style
Dutta, S., Sourav Dutta and Swarup Roy. 2023 "NetRA: An IntegratedWeb Platform for Large-Scale Gene Regulatory Network Reconstruction and Analysis" Preprints. https://doi.org/10.20944/preprints202310.0820.v1
Abstract
Several effective online and offline inference tools offer an interactive platform for inference, visualization, and analysis of gene regulatory networks. However, a tool currently needs to offer a scalable, lightweight, integrated online platform for carrying out inference, visualization, benchmarking, and extensive network analysis in an integrated manner. We introduce NetRA (Network Reconstruction and Analysis for Gene Regulatory Network), a comprehensive web tool for network analysis, visualization, and inference of large expression networks. Additionally, a platform for benchmarking and evaluation is provided. In order to deliver a highly scalable, lightweight, and rich user interface, the tool is created using the most recent technologies. We incorporate the original code of eleven (11) inference algorithms (not limited to) from Bioconductor in the current version. We also report a qualitative comparison of 11 candidate methods regarding prediction accuracy and network characteristics which will shed light on their performance against 4000 sizes synthetic DREAM network. We believe the tool will significantly aid biologists' downstream system biology research. NetRA tool can be extensible to different kinds of complex network analyses. Availability: On request (sroy01@cus.ac.in).
Biology and Life Sciences, Biology and Biotechnology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
