CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components
Open accessPublished version of a preprint
Abstract
BACKGROUND: The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. RESULTS: Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CONCLUSIONS: CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Studies have integrated protein-protein interaction networks with subcellular organization by partitioning a network into subnetworks according to subcellular location.
“At a larger scale, studies have integrated protein-protein interaction networks with subcellular organization by partitioning a network into subnetworks according to subcellular location (Barsky et al., 2007; Heberle et al., 2017; Nagasaki et al., 2011; Ofran et al., 2006; Zhang et al., 2012a).”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Heberle et al., 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · cited 6× · see citing works
“Mosaic is a Cytoscape (desktop) plugin which partitions a network into subnetworks based on GO Biological Process annotation.”
BackgroundMethodInfluentialGene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · cited 1× · see citing works
“The tool displays the network over a standard cell graphical representation showing the main partitions and organelles according to the Gene Ontology (GO) cellular component database [26].”
MethodGephi: An Open Source Software for Exploring and Manipulating Networks
Bastian, M., Heymann, S., & Jacomy, M. (2009) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v3i1.13937 · Cited by 11,675 · cited 2× · see citing works
“Using as basis the figures [1][2][3] displayed on Mosaic web page, section Navigating the results, CellNetVis performed better, since nodes did not overlap on any of the displayed subnetworks and their topology was clear.”
BackgroundMethodThe eyes have it: a task by data type taxonomy for information visualizations
Shneiderman, B. (2002) · IEEE Symposium on Visual Languages · doi:10.1109/vl.1996.545307 · Cited by 4,588 · cited 1× · see citing works
“The positioning algorithm of CellNetVis works well with both small and large networks and supports more directly the visualization pipeline described by Schneiderman [48]: overview, followed by zoom and filter, then details on demand.”
MethodBostock, M., Ogievetsky, V., & Heer, J. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.185 · Cited by 3,165 · see citing works
Towards a knowledge-based Human Protein Atlas
Uhlen, M., Oksvold, P., Fagerberg, L., Lundberg, E., Jonasson, K., Forsberg, M., Zwahlen, M., Kampf, C., Wester, K., Hober, S., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1210-1248 · Cited by 2,440 · cited 2× · see citing works
“We used 2097 proteins from the Human Protein Atlas [40] supportive data (Additional file 2) to construct a first neighbors network on IIS.”
MethodThe Quadtree and Related Hierarchical Data Structures
Samet, H. (1984) · ACM Computing Surveys · doi:10.1145/356924.356930 · Cited by 2,205 · cited 1× · see citing works
“This verification is done after each iteration of the D3 force placement and queries a quad-tree data structure [35].”
MethodThe KEGG databases at GenomeNet
Kanehisa, M., Goto, S., Kawashima, S., & Nakaya, A. (2002) · Nucleic Acids Res. · doi:10.1093/nar/30.1.42 · Cited by 1,547 · cited 4× · see citing works
“We used 257 proteins from the human MAPK signaling pathway in the KEGG database (Additional file 4) to construct a first neighbors network on IIS.”
BackgroundInfluentialUniProt Knowledgebase: a hub of integrated protein data
Magrane, M. (2011) · Database · doi:10.1093/database/bar009 · Cited by 1,455 · see citing works
Pajek - Program for Large Network Analysis
Batagelj, V., & Mrvar, A. (1999) · Cited by 1,393 · see citing works
Yates, A. D., Akanni, W. A., Amode, M. R., Barrell, D. G., Billis, K., Carvalho‐Silva, D., Cummins, C. A., Clapham, P., Fitzgerald, S. F., Gil, L., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1157 · Cited by 1,246 · cited 1× · see citing works
“In this case, nodes must have an attribute that identifies the gene or protein ID in the Ensembl [30], Entrez [31], InnateDB [29] or UniProt [32] format.”
BackgroundInnateDB: systems biology of innate immunity and beyond—recent updates and continuing curation
Breuer, K., Foroushani, A. B. K., Laird, M. R., Chen, C. C. L., Sribnaia, A., Lo, R., Winsor, G. L., Hancock, R. E. W., Brinkman, F. S. L., & Lynn, D. J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1147 · Cited by 1,224 · cited 6× · see citing works
“Additionally, the tool supports the retrieval of cellular components for human, mouse and bovine genes from the InnateDB web service.”
BackgroundInfluentialColorBrewer.org: An Online Tool for Selecting Colour Schemes for Maps
Harrower, M., & Brewer, C. A. (2003) · The Cartographic Journal · doi:10.1179/000870403235002042 · Cited by 1,134 · cited 1× · see citing works
“The cell diagram is colored using a ColorBrewer [33] “BrBG” diverging scheme, characterized by colors that can be easily differentiated.”
MethodGraphviz— Open Source Graph Drawing Tools
Ellson, J., Gansner, E. R., Koutsofios, L., North, S. C., & Woodhull, G. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45848-4_57 · Cited by 784 · see citing works
NodeTrix: a Hybrid Visualization of Social Networks
Henry, N., Fekete, J., & McGuffin, M. J. (2007) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2007.70582 · Cited by 556 · cited 1× · see citing works
“Nodetrix [39] and Power Graphs [40], are scope for future work.”
BackgroundForce‐Directed Edge Bundling for Graph Visualization
Holten, D., & van Wijk, J. J. (2009) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2009.01450.x · Cited by 534 · cited 1× · see citing works
“ForceBundle) of ForceDirected Edge Bundling [36] in CellNetVis.”
MethodBarsky, A., Gardy, J. L., Hancock, R. E. W., & Munzner, T. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm057 · Cited by 175 · see citing works
GOlorize: a Cytoscape plug-in for network visualization with Gene Ontology-based layout and coloring
Garcia, O., Saveanu, C., Cline, M., Fromont‐Racine, M., Jacquier, A., Schwikowski, B., & Aittokallio, T. A. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl605 · Cited by 104 · cited 1× · see citing works
“describe an extension to the forcedirected layout to place nodes according to their connection and class structure [12].”
BackgroundA layout algorithm for undirected compound graphs
Doğrusöz, U., Giral, E., Çetintaş, A., Çivril, A., & Demir, E. (2008) · Information Sciences · doi:10.1016/j.ins.2008.11.017 · Cited by 103 · cited 1× · see citing works
“Other approaches that group nodes in two-dimensional space have been proposed, such as constrained force-directed layout [13], constrained projections [14], hierarchical graph placement [15, 16, 17] and others [18, 19, 20, 21].”
BackgroundScalable, Versatile and Simple Constrained Graph Layout
Dwyer, T. (2009) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2009.01449.x · Cited by 93 · see citing works
Cell Illustrator 4.0: A Computational Platform for Systems Biology
Nagasaki, M., Saito, A., Jeong, E., Li, C., Kojima, K., Ikeda, E., & Miyano, S. (2010) · In Silico Biology · doi:10.3233/isb-2010-0415 · Cited by 92 · cited 3× · see citing works
“The new version, Cell Illustrator Online [25], is a tool that enables drawing, visualization and modeling of biological pathways.”
BackgroundMethodBastian, F., Chibucos, M. C., Gaudet, P., Giglio, M. G., Holliday, G. L., Huang, H., Lewis, S., Niknejad, A., Orchard, S. E., Poux, S., et al. (2015) · Database · doi:10.1093/database/bav043 · Cited by 60 · see citing works
Carazzolle, M. F., de Carvalho, L. M., Slepicka, H., Vidal, R. O., Pereira, G. A. G., Kobarg, J., & Meirelles, G. V. (2014) · PLoS ONE · doi:10.1371/journal.pone.0100385 · Cited by 51 · cited 10× · see citing works
“CellNetVis is being used by the IIS as its main visualization system.”
BackgroundInfluentialEntourage: Visualizing Relationships between Biological Pathways using Contextual Subsets
Lex, A., Partl, C., Kalkofen, D., Streit, M., Gratzl, S., Wassermann, A. M., Schmalstieg, D., & Pfister, H. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2013.154 · Cited by 47 · cited 1× · see citing works
“Other software systems, like Extended LineSets [9], Entourage [10], and ReactionFlow [11], focus on the analysis of pathways and their mechanisms.”
MethodReactionFlow: an interactive visualization tool for causality analysis in biological pathways
Dang, T. N., Murray, P., Aurisano, J., & Forbes, A. G. (2015) · BMC Proceedings · doi:10.1186/1753-6561-9-s6-s6 · Cited by 39 · cited 1× · see citing works
“Other software systems, like Extended LineSets [9], Entourage [10], and ReactionFlow [11], focus on the analysis of pathways and their mechanisms.”
MethodNetVenn: an integrated network analysis web platform for gene lists
Wang, Y., Thilmony, R. L., & Gu, Y. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku331 · Cited by 38 · cited 2× · see citing works
“Nodetrix [39] and Power Graphs [40], are scope for future work.”
BackgroundFast layout computation of clustered networks: Algorithmic advances and experimental analysis
Didimo, W., & Montecchiani, F. (2013) · Information Sciences · doi:10.1016/j.ins.2013.09.048 · Cited by 35 · cited 1× · see citing works
“Other approaches that group nodes in two-dimensional space have been proposed, such as constrained force-directed layout [13], constrained projections [14], hierarchical graph placement [15, 16, 17] and others [18, 19, 20, 21].”
BackgroundMcEntyre, J. (1998) · Trends in Genetics · doi:10.1016/s0168-9525(97)01325-5 · Cited by 34 · cited 1× · see citing works
“In this case, nodes must have an attribute that identifies the gene or protein ID in the Ensembl [30], Entrez [31], InnateDB [29] or UniProt [32] format.”
BackgroundTugging Graphs Faster: Efficiently Modifying Path-Preserving Hierarchies for Browsing Paths
Archambault, D., Munzner, T., & Auber, D. (2010) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2010.60 · Cited by 30 · see citing works
Cell Illustrator 4.0: A Computational Platform for Systems Biology
Masao, N., Ayumu, S., Euna, J., Li, C., Kojima, K., Ikeda, E., & Satoru, M. (2011) · Studies in health technology and informatics · doi:10.3233/978-1-60750-704-8-160 · Cited by 24 · see citing works
Extended LineSets: a visualization technique for the interactive inspection of biological pathways
Paduano, F., & Forbes, A. G. (2015) · BMC Proceedings · doi:10.1186/1753-6561-9-s6-s4 · Cited by 23 · cited 1× · see citing works
“Other software systems, like Extended LineSets [9], Entourage [10], and ReactionFlow [11], focus on the analysis of pathways and their mechanisms.”
MethodMulti-circular Layout of Micro/Macro Graphs
Baur, M. N., & Brandes, U. (2008) · Springer eBooks · doi:10.1007/978-3-540-77537-9_26 · Cited by 23 · cited 1× · see citing works
“Other approaches that group nodes in two-dimensional space have been proposed, such as constrained force-directed layout [13], constrained projections [14], hierarchical graph placement [15, 16, 17] and others [18, 19, 20, 21].”
BackgroundMosaic: making biological sense of complex networks
Zhang, C., Hanspers, K., Kuchinsky, A., Salomonis, N., Xu, D. H., & Pico, A. R. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts278 · Cited by 23 · see citing works
Multidimensional Projections for Visual Analysis of Social Networks
Martins, R. M., Andery, G. F., Heberle, H., Paulovich, F. V., Lopes, A. D. A., Pedrini, H., & Minghim, R. (2012) · Journal of Computer Science and Technology · doi:10.1007/s11390-012-1265-5 · Cited by 22 · cited 1× · see citing works
“Among those are Graphviz [1], Gephi [2], Pajek [3], PEx-Graph [4], Cystocape [5] and Tulip [6].”
BackgroundBiographer: web-based editing and rendering of SBGN compliant biochemical networks
Krause, F., Schulz, M., Ripkens, B., Flöttmann, M., Krantz, M., Klipp, E., & Handorf, T. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt159 · Cited by 17 · cited 1× · see citing works
“Biographer [22] is a web-based tool to edit and render reaction networks.”
MethodDidimo, W., & Montecchiani, F. (2012) · Proceedings · doi:10.1109/iv.2012.14 · Cited by 16 · cited 1× · see citing works
“Other approaches that group nodes in two-dimensional space have been proposed, such as constrained force-directed layout [13], constrained projections [14], hierarchical graph placement [15, 16, 17] and others [18, 19, 20, 21].”
BackgroundFast grid layout algorithm for biological networks with sweep calculation
Kojima, K., Nagasaki, M., & Miyano, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn196 · Cited by 15 · cited 4× · see citing works
“The new version, Cell Illustrator Online [25], is a tool that enables drawing, visualization and modeling of biological pathways.”
BackgroundInfluentialCluE: An Algorithm for Expanding Clustered Graphs
AlTarawneh, R., Schultz, J., & Humayoun, S. R. (2014) · IEEE Pacific Visualization Symposium · doi:10.1109/pacificvis.2014.18 · Cited by 11 · cited 1× · see citing works
“Other approaches that group nodes in two-dimensional space have been proposed, such as constrained force-directed layout [13], constrained projections [14], hierarchical graph placement [15, 16, 17] and others [18, 19, 20, 21].”
BackgroundAuber, D., Archambault, D., Bourqui, R., Delest, M., Dubois, J., Pinaud, B., Lambert, A., Mary, P., Mathiaut, M., & Mélançon, G. (2014) · Springer eBooks · doi:10.1007/978-1-4614-6170-8_315 · Cited by 11 · cited 1× · see citing works
“Among those are Graphviz [1], Gephi [2], Pajek [3], PEx-Graph [4], Cystocape [5] and Tulip [6].”
Background(2010) · Lecture notes in computer science · doi:10.1007/978-3-642-11805-0 · Cited by 11 · see citing works
Layout with Circular and Other Non-linear Constraints Using Procrustes Projection
Dwyer, T., & Robertson, G. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-11805-0_37 · Cited by 9 · cited 1× · see citing works
“Other approaches that group nodes in two-dimensional space have been proposed, such as constrained force-directed layout [13], constrained projections [14], hierarchical graph placement [15, 16, 17] and others [18, 19, 20, 21].”
BackgroundCerebralWeb: a Cytoscape.js plug-in to visualize networks stratified by subcellular localization
Frias, S., Bryan, K. R., Brinkman, F. S. L., & Lynn, D. J. (2015) · Database · doi:10.1093/database/bav041 · Cited by 9 · cited 3× · see citing works
“Cerebral [7, 23], originally designed as a Cytoscape [5] plugin and extended to work with Cytoscape.”
BackgroundMethodVaxelaire, E., Gamand, L., Aebischer-Gumy, C., Moretti, P., & Bertschinger, M. (2015) · BMC Proceedings · doi:10.1186/1753-6561-9-s9-p4 · Cited by 4 · see citing works
Loh, W. P., Yang, Y., Tan, A. H., & Lam, K. (2015) · BMC Proceedings · doi:10.1186/1753-6561-9-s9-p6 · Cited by 3 · see citing works
Multidimensional Projections for Visual Analysis of Social Networks
Rafael, Messias, Martins, Gabriel, G., Faria, Andery, Henry, Heberle, Fernando, F., Vieira, et al. (2012) · Acta Scientiarum Naturalium Universitatis Sunyatseni · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [17]Schuhmacher A. Software Visualization via Hierarchic Graphs: PhD thesis, Karlsruhe Institute of Technology; 2015. http://i11www.iti.kit.edu/_media/teaching/theses/ma-schuhmacher-15.pdf. Accessed 17 Apr 2017.
Cited by
Sorted by citations
Mapping the multiscale structure of biological systems
Schaffer, L. V., & Ideker, T. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.012 · Cited by 75 · see citing works
“At a larger scale, studies have integrated protein-protein interaction networks with subcellular organization by partitioning a network into subnetworks according to subcellular location (Barsky et al., 2007; Heberle et al., 2017; Nagasaki et al.,2011; Ofranet al., 2006; Zhang etal.,2012a).”
BackgroundGong, Z., Chen, J., Jiao, X., Gong, H., Pan, D., Liu, L., Zhang, Y., & Tan, T. (2024) · Biotechnology Advances · doi:10.1016/j.biotechadv.2024.108319 · Cited by 63 · see citing works
Mapping the technology evolution path: a novel model for dynamic topic detection and tracking
Liu, H., Chen, Z., Tang, J., Zhou, Y. J., & Liu, S. (2020) · Scientometrics · doi:10.1007/s11192-020-03700-5 · Cited by 53 · see citing works
Bioinformatics applied to biotechnology: A review towards bioenergy research
de Carvalho, L. M., Borelli, G., Camargo, A. P., de Assis, M. A., de Ferraz, S. M. F., Fiamenghi, M. B., José, J., Mofatto, L. S., Nagamatsu, S. T., Persinoti, G. F., et al. (2019) · Biomass and Bioenergy · doi:10.1016/j.biombioe.2019.02.016 · Cited by 37 · see citing works
Exploratory Gene Ontology Analysis with Interactive Visualization
Zhu, J., Zhao, Q., Katsevich, E., & Sabatti, C. (2019) · Scientific Reports · doi:10.1038/s41598-019-42178-x · Cited by 30 · see citing works
Baldwin, M. J., Mimpen, J. Y., Cribbs, A. P., Stace, E. T., Philpott, M., Dakin, S. G., Carr, A. J., & Snelling, S. J. B. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2021.795748 · Cited by 22 · see citing works
“, 2020), visualised using the CellNetVis web interface (Heberle et al., 2017) and functionally annotated with the mygene package.”
MethodLCN2-interacting proteins and their expression patterns in brain tumors
Du, Z., Wu, B., Xia, Q., Zhao, Y. D., Lin, L., Cai, Z., Wang, S., Li, E., Xu, L., Li, Y., et al. (2019) · Brain Research · doi:10.1016/j.brainres.2019.146304 · Cited by 19 · see citing works
Tracing the footsteps of autophagy in computational biology
Sarmah, D. T., Bairagi, N., & Chatterjee, S. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa286 · Cited by 17 · see citing works
“Web tools like CellNetVis [116], Biographer [117] are also used for network visualization purposes.”
MethodRobin, V., Bodein, A., Scott‐Boyer, M., Leclercq, M., Périn, O., & Droit, A. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.962799 · Cited by 18 · see citing works
“The main differences between simple and complex algorithms for visualization depend on the size of the network, the topology of the network, and the dimensionality of the information (Heberle et al., 2017; Becker et al., 2020; Raja et al., 2020).”
BackgroundNORMA: The Network Makeup Artist — A Web Tool for Network Annotation Visualization
Koutrouli, M., Karatzas, E., Papanikolopoulou, K., & Pavlopoulos, G. A. (2021) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.02.005 · Cited by 13 · see citing works
“CellNetVis [28] is a web tool for the visualization of biological networks placing nodes in the cellular components they belong to.”
MethodVisualization and Analysis of Epiproteome Dynamics
Kaur, S., Baldi, B. F., Vuong, J., & O’Donoghue, S. I. (2019) · Journal of Molecular Biology · doi:10.1016/j.jmb.2019.01.044 · Cited by 11 · see citing works
SPV: a JavaScript Signaling Pathway Visualizer
Calderone, A., & Cesareni, G. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty188 · Cited by 10 · see citing works
VizTract: Visualization of Complex Social Networks for Easy User Perception
Akula, R., & Garibay, I. I. (2019) · Big Data and Cognitive Computing · doi:10.3390/bdcc3010017 · Cited by 9 · see citing works
“The method of compound graphs is also employed in [24] for the bio-molecular interaction networks along with force-directed layout, where the networks are placed into cellular components to quickly identify the location of the network elements, especially for the densely populated locations.”
MethodCellMap visualizes protein-protein interactions and subcellular localization
Dallago, C., Goldberg, T., Andrade-Navarro, M. A., Alanis‐Lobato, G., & Rost, B. (2017) · F1000Research · doi:10.12688/f1000research.12707.1 · Cited by 9 · see citing works
Dallago, C., Goldberg, T., Andrade-Navarro, M. A., Alanis‐Lobato, G., & Rost, B. (2020) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.97 · Cited by 5 · see citing works
Memberships Networks for High-Dimensional Fuzzy Clustering Visualization
Ariza-Jiménez, L., Villa, L. F., & Montoya, O. L. Q. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-31019-6_23 · Cited by 3 · see citing works
An investigation into various visualization tools for complex biological networks
Alzahrani, H., & Fernstad, S. J. (2023) · Information Visualization · doi:10.1177/14738716231181545 · Cited by 3 · see citing works
“Based on the findings, essential factors were categorized as either generic and heuristic, where the former concern different analytical and interactive functionalities, such as an efficient layout, advanced search capabilities, plugin availability, graph analysis and user-friendliness, while the latter concern usabil…”
BackgroundGene Ontology and Pathway Enrichment Analysis
Gupta, M. K., Gouda, G., Sabarinathan, S., Donde, R., Dash, G. K., Vadde, R., & Behera, L. (2021) · Springer eBooks · doi:10.1007/978-981-16-3993-7_12 · Cited by 3 · see citing works
Applications of disease pathways in biology and medicine
Nesterova, A. P., Климов, Е. А., Zharkova, M. S., Sozin, S., Sobolev, V. A., Ivanikova, N. V., Shkrob, M., & Yuryev, A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-817086-1.00014-2 · Cited by 2 · see citing works
Ji, L., Wang, Z., Qiu, S., Yang, G., & Zhang, S. (2025) · Visual Informatics · doi:10.1016/j.visinf.2025.100237
- Authors
- Heberle, H., Carazzolle, M. F., Telles, G. P., Meirelles, G. V., & Minghim, R.
- Affiliations
- Universidade de São Paulo (BR)
- Universidade Estadual de Campinas (UNICAMP) (BR)
- Brazilian Biosciences National Laboratory (BR)
- Corresponding author
- Minghim, Rosane
- ORCID
- Venue
- BMC Bioinformatics
- Published
- 2017-09
- Volume
- 18
- Issue
- S10
- Pages
- 395-395
- ISSN
- 1471-2105 (ISSN-L)
- PMC
- PMC5606216
- OpenAlex
- W2734881787
- Cited by
- 21
- References
- 45
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 3 · 2019: 8 · 2018: 1 · 2017: 1
- FWCI
- 1.45
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Bioinformatics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- biological network visualization, force-directed layout, cell compartments, protein-protein interaction network, web visualization tool
- MeSH terms
- Algorithms, Cells, Humans, Software, User-Computer Interface, Databases, Factual, Internet, MAP Kinase Signaling System, Metabolic Networks and Pathways, Gene Ontology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
