{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T07:57:56Z","timestamp":1761292676597},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2010,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Biochemical networks play an essential role in systems biology. Rapidly growing network data and versatile research activities call for convenient visualization tools to aid intuitively perceiving abstract structures of networks and gaining insights into the functional implications of networks. There are various kinds of network visualization software, but they are usually not adequate for visual analysis of complex biological networks mainly because of the two reasons: 1) most existing drawing methods suitable for biochemical networks have high computation loads and can hardly achieve near real-time visualization; 2) available network visualization tools are designed for working in certain network modeling platforms, so they are not convenient for general analyses due to lack of broader range of readily accessible numerical utilities.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We present LucidDraw as a visual analysis tool, which features (a) speed: typical biological networks with several hundreds of nodes can be drawn in a few seconds through a new layout algorithm; (b) ease of use: working within MATLAB makes it convenient to manipulate and analyze the network data using a broad spectrum of sophisticated numerical functions; (c) flexibility: layout styles and incorporation of other available information about functional modules can be controlled by users with little effort, and the output drawings are interactively modifiable.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Equipped with a new grid layout algorithm proposed here, LucidDraw serves as an auxiliary network analysis tool capable of visualizing complex biological networks in near real-time with controllable layout styles and drawing details. The framework of the algorithm enables easy incorporation of extra biological information, if available, to influence the output layouts with predefined node grouping features.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-11-31","type":"journal-article","created":{"date-parts":[[2010,1,15]],"date-time":"2010-01-15T19:14:54Z","timestamp":1263582894000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["LucidDraw: Efficiently visualizing complex biochemical networks within MATLAB"],"prefix":"10.1186","volume":"11","author":[{"given":"Sheng","family":"He","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Mei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guiyang","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengxiang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weijiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2010,1,15]]},"reference":[{"key":"3488_CR1","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1186\/1471-2105-10-19","volume":"10","author":"T Hashimoto","year":"2009","unstructured":"Hashimoto T, Nagasaki M, Kojima K, Miyano S: BFL: a node and edge betweenness based fast layout algorithm for large scale networks. BMC Bioinformatics 2009, 10: 19. 10.1186\/1471-2105-10-19","journal-title":"BMC Bioinformatics"},{"issue":"7","key":"3488_CR2","doi-asserted-by":"publisher","first-page":"e2541","DOI":"10.1371\/journal.pone.0002541","volume":"3","author":"W Li","year":"2008","unstructured":"Li W, Kurata H: Visualizing Global Properties of Large Complex Networks. PLoS ONE 2008, 3(7):e2541. 10.1371\/journal.pone.0002541","journal-title":"PLoS ONE"},{"issue":"8","key":"3488_CR3","doi-asserted-by":"publisher","first-page":"1040","DOI":"10.1093\/bioinformatics\/btm057","volume":"23","author":"A Barsky","year":"2007","unstructured":"Barsky A, Gardy JL, Hancock REW, Munzner T: Cerebral: a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation. Bioinformatics 2007, 23(8):1040\u20131042. 10.1093\/bioinformatics\/btm057","journal-title":"Bioinformatics"},{"issue":"2","key":"3488_CR4","first-page":"22","volume":"16","author":"M Kato","year":"2005","unstructured":"Kato M, Nagasaki M, Doi A, Miyano S: Automatic drawing of biological networks using cross cost and subcomponent data. Genome Inform 2005, 16(2):22\u201331.","journal-title":"Genome Inform"},{"key":"3488_CR5","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1186\/1471-2105-8-76","volume":"8","author":"K Kojima","year":"2007","unstructured":"Kojima K, Nagasaki M, Jeong E, Kato M, Miyano S: An efficient grid layout algorithm for biological networks utilizing various biological attributes. BMC Bioinformatics 2007, 8: 76. 10.1186\/1471-2105-8-76","journal-title":"BMC Bioinformatics"},{"issue":"12","key":"3488_CR6","doi-asserted-by":"publisher","first-page":"1433","DOI":"10.1093\/bioinformatics\/btn196","volume":"24","author":"K Kojima","year":"2008","unstructured":"Kojima K, Nagasaki M, Miyano S: Fast grid layout algorithm for biological networks with sweep calculation. Bioinformatics 2008, 24(12):1433\u20131441. 10.1093\/bioinformatics\/btn196","journal-title":"Bioinformatics"},{"issue":"9","key":"3488_CR7","doi-asserted-by":"publisher","first-page":"2036","DOI":"10.1093\/bioinformatics\/bti290","volume":"21","author":"W Li","year":"2005","unstructured":"Li W, Kurata H: A grid layout algorithm for automatic drawing of biochemical networks. Bioinformatics 2005, 21(9):2036\u20132042. 10.1093\/bioinformatics\/bti290","journal-title":"Bioinformatics"},{"issue":"20","key":"3488_CR8","doi-asserted-by":"publisher","first-page":"2651","DOI":"10.1093\/bioinformatics\/btm401","volume":"23","author":"M Suderman","year":"2007","unstructured":"Suderman M, Hallett M: Tools for visually exploring biological networks. Bioinformatics 2007, 23(20):2651\u20132659. 10.1093\/bioinformatics\/btm401","journal-title":"Bioinformatics"},{"issue":"6","key":"3488_CR9","doi-asserted-by":"publisher","first-page":"1253","DOI":"10.1109\/TVCG.2008.117","volume":"14","author":"A Barsky","year":"2008","unstructured":"Barsky A, Munzner T, Gardy J, Kincaid R: Cerebral: Visualizing Multiple Experimental Conditions on a Graph with Biological Context. IEEE transactions on visualization and computer graphics 2008, 14(6):1253\u20131260. 10.1109\/TVCG.2008.117","journal-title":"IEEE transactions on visualization and computer graphics"},{"issue":"11","key":"3488_CR10","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1101\/gr.1239303","volume":"13","author":"P Shannon","year":"2003","unstructured":"Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Research 2003, 13(11):2498\u20132504. 10.1101\/gr.1239303","journal-title":"Genome Research"},{"issue":"7","key":"3488_CR11","doi-asserted-by":"publisher","first-page":"996","DOI":"10.1093\/bioinformatics\/18.7.996","volume":"18","author":"E Demir","year":"2002","unstructured":"Demir E, Babur O, Dogrusoz U, Gursoy A, Nisanci G, Cetin-Atalay R, Ozturk M: PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways. Bioinformatics 2002, 18(7):996\u20131003. 10.1093\/bioinformatics\/18.7.996","journal-title":"Bioinformatics"},{"key":"3488_CR12","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1186\/1471-2105-5-17","volume":"5","author":"Z Hu","year":"2004","unstructured":"Hu Z, Mellor J, Wu J, DeLisi C: VisANT: an online visualization and analysis tool for biological interaction data. BMC Bioinformatics 2004, 5: 17. 10.1186\/1471-2105-5-17","journal-title":"BMC Bioinformatics"},{"issue":"3","key":"3488_CR13","first-page":"181","volume":"2","author":"M Nagasaki","year":"2003","unstructured":"Nagasaki M, Doi A, Matsuno H, Miyano S: Genomic Object Net: I. A platform for modelling and simulating biopathways. Applied Bioinformatics 2003, 2(3):181\u2013184.","journal-title":"Applied Bioinformatics"},{"issue":"3","key":"3488_CR14","first-page":"185","volume":"2","author":"A Doi","year":"2003","unstructured":"Doi A, Nagasaki M, Fujita S, Matsuno H, Miyano S: Genomic Object Net: II. Modelling biopathways by hybrid functional Petri net with extension. Applied Bioinformatics 2003, 2(3):185\u2013188.","journal-title":"Applied Bioinformatics"},{"issue":"4","key":"3488_CR15","doi-asserted-by":"publisher","first-page":"590","DOI":"10.1101\/gr.3463705","volume":"15","author":"H Kurata","year":"2005","unstructured":"Kurata H, Masaki K, Sumida Y, Iwasaki R: CADLIVE dynamic simulator: Direct link of biochemical networks to dynamic models. Genome Research 2005, 15(4):590\u2013600. 10.1101\/gr.3463705","journal-title":"Genome Research"},{"issue":"14","key":"3488_CR16","doi-asserted-by":"publisher","first-page":"4071","DOI":"10.1093\/nar\/gkg461","volume":"31","author":"H Kurata","year":"2003","unstructured":"Kurata H, Matoba N, Shimizu N: CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle. Nucleic Acids Research 2003, 31(14):4071\u20134084. 10.1093\/nar\/gkg461","journal-title":"Nucleic Acids Research"},{"issue":"8","key":"3488_CR17","doi-asserted-by":"publisher","first-page":"2790","DOI":"10.1128\/JB.01583-07","volume":"190","author":"MA Oberhardt","year":"2008","unstructured":"Oberhardt MA, Puchalka J, Fryer KE, Martins dos Santos VAP, Papin JA: Genome-Scale Metabolic Network Analysis of the Opportunistic Pathogen Pseudomonas aeruginosa PAO1. Journal of Bacteriology 2008, 190(8):2790\u20132803. 10.1128\/JB.01583-07","journal-title":"Journal of Bacteriology"},{"issue":"4","key":"3488_CR18","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1093\/bioinformatics\/btg033","volume":"19","author":"P Holme","year":"2003","unstructured":"Holme P, Huss M, Jeong H: Subnetwork hierarchies of biochemical pathways. Bioinformatics 2003, 19(4):532\u2013538. 10.1093\/bioinformatics\/btg033","journal-title":"Bioinformatics"},{"issue":"5","key":"3488_CR19","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/S0966-842X(01)02018-2","volume":"9","author":"CE Barry","year":"2001","unstructured":"Barry CE: Interpreting cell wall 'virulence factors' of Mycobacterium tuberculosis. Trends in Microbiology 2001, 9(5):237\u2013241. 10.1016\/S0966-842X(01)02018-2","journal-title":"Trends in Microbiology"},{"issue":"2","key":"3488_CR20","doi-asserted-by":"publisher","first-page":"140","DOI":"10.2174\/187152607781001772","volume":"7","author":"DP Bhave","year":"2007","unstructured":"Bhave DP, MuseIII WB, Carroll KS: Drug Targets in Mycobacterial Sulfur Metabolism. Infect Disord Drug Targets 2007, 7(2):140\u2013158. 10.2174\/187152607781001772","journal-title":"Infect Disord Drug Targets"},{"issue":"12","key":"3488_CR21","doi-asserted-by":"publisher","first-page":"5133","DOI":"10.1073\/pnas.0610634104","volume":"104","author":"M Jain","year":"2007","unstructured":"Jain M, Petzold CJ, Schelle MW, Leavell MD, Mougous JD, Bertozzi CR, Leary JA, Cox JS: Lipidomics reveals control of Mycobacterium tuberculosis virulence lipids via metabolic coupling. PNAS 2007, 104(12):5133\u20135138. 10.1073\/pnas.0610634104","journal-title":"PNAS"},{"key":"3488_CR22","first-page":"1","volume-title":"Proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization","author":"L Zhipeng","year":"2009","unstructured":"Zhipeng L, Jin-Kao H: A Critical Element-Guided Perturbation Strategy for Iterated Local Search. In Proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization. T\u00fcbingen, Germany: Springer-Verlag; 2009:1\u201312."},{"key":"3488_CR23","doi-asserted-by":"publisher","first-page":"043025","DOI":"10.1088\/1367-2630\/11\/4\/043025","volume":"11","author":"J Mei","year":"2009","unstructured":"Mei J, He S, Shi G, Wang Z, Li W: Revealing network communities through modularity maximization by a contraction-dilation method. New Journal of Physics 2009, 11: 043025. 10.1088\/1367-2630\/11\/4\/043025","journal-title":"New Journal of Physics"},{"key":"3488_CR24","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1186\/1471-2105-8-313","volume":"8","author":"R Schwarz","year":"2007","unstructured":"Schwarz R, Liang C, Kaleta C, Kuhnel M, Hoffmann E, Kuznetsov S, Hecker M, Griffiths G, Schuster S, Dandekar T: Integrated network reconstruction, visualization and analysis using YANAsquare. BMC Bioinformatics 2007, 8: 313. 10.1186\/1471-2105-8-313","journal-title":"BMC Bioinformatics"},{"key":"3488_CR25","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1186\/1471-2105-7-109","volume":"7","author":"B Junker","year":"2006","unstructured":"Junker B, Klukas C, Schreiber F: VANTED: A system for advanced data analysis and visualization in the context of biological networks. BMC Bioinformatics 2006, 7: 109. 10.1186\/1471-2105-7-109","journal-title":"BMC Bioinformatics"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-11-31.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T12:15:13Z","timestamp":1630498513000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-11-31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,1,15]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2010,12]]}},"alternative-id":["3488"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-11-31","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,1,15]]},"assertion":[{"value":"13 July 2009","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 2010","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 2010","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"31"}}