BENviewer: a gene interaction network visualization server based on graph embedding model

Abstract BENviewer is a brand-new online gene interaction network visualization server based on graph embedding models. With mature graph embedding algorithms applied on several interaction network databases, it provides human-friendly 2D visualization based on more than 2000 biological pathways, and these results present not only genes involved but also tightness of interactions in an intuitive way. As a unique visualization server introducing graph embedding application for the first time, it is expected to help researchers gain deeper insights into biological networks beyond generating results explainable by existing knowledge. Additionally, operation flow for users is simplified to greater extent in its current version; meanwhile URL optimization contributes to data acquisition in batch for further analysis. BENviewer is freely available at http://www.bmeonline.cn/BENviewer, besides it is open-sourced at https://github.com/SKLB-lab/BENviewer, http://benviewer.bmeonline.cn.

[1]  Jure Leskovec,et al.  node2vec: Scalable Feature Learning for Networks , 2016, KDD.

[2]  Palash Goyal,et al.  Graph Embedding Techniques, Applications, and Performance: A Survey , 2017, Knowl. Based Syst..

[3]  Tim Angus,et al.  Visualisation of BioPAX Networks using BioLayout Express 3D , 2014, F1000Research.

[4]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[5]  Ralf Herwig,et al.  ConsensusPathDB: toward a more complete picture of cell biology , 2010, Nucleic Acids Res..

[6]  Mingzhe Wang,et al.  LINE: Large-scale Information Network Embedding , 2015, WWW.

[7]  Canglin Wu,et al.  RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse , 2015, Database J. Biol. Databases Curation.

[8]  Srinivasan Parthasarathy,et al.  Graph embedding on biomedical networks: methods, applications and evaluations , 2019, Bioinform..

[9]  Marc R Wilkins,et al.  Four‐dimensional visualisation and analysis of protein–protein interaction networks , 2011, Proteomics.

[10]  Leland McInnes,et al.  UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction , 2018, ArXiv.

[11]  Timothy M. D. Ebbels,et al.  springScape: visualisation of microarray and contextual bioinformatic data using spring embedding and an "information landscape" , 2006, ISMB.

[12]  Wenwu Zhu,et al.  Structural Deep Network Embedding , 2016, KDD.

[13]  Henning Hermjakob,et al.  The Reactome pathway knowledgebase , 2013, Nucleic Acids Res..

[14]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[15]  Songting Shi,et al.  Visualizing Data using GTSNE , 2021, ArXiv.

[16]  Howard Y. Chang,et al.  Lineage-specific and single cell chromatin accessibility charts human hematopoiesis and leukemia evolution , 2016, Nature Genetics.

[17]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.