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Author (up) Allende, C.; Sohn, E.; Little, C. pdf  doi
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  Title Treelink: data integration, clustering and visualization of phylogenetic trees Type
  Year 2015 Publication Bmc Bioinformatics Abbreviated Journal BMC Bioinformatics  
  Volume 16 Issue Pages 6 pp  
  Keywords Phylogenetic tree; Data integration; Clustering; Visualization  
  Abstract Background: Phylogenetic trees are central to a wide range of biological studies. In many of these studies, tree nodes need to be associated with a variety of attributes. For example, in studies concerned with viral relationships, tree nodes are associated with epidemiological information, such as location, age and subtype. Gene trees used in comparative genomics are usually linked with taxonomic information, such as functional annotations and events. A wide variety of tree visualization and annotation tools have been developed in the past, however none of them are intended for an integrative and comparative analysis. Results: Treelink is a platform-independent software for linking datasets and sequence files to phylogenetic trees. The application allows an automated integration of datasets to trees for operations such as classifying a tree based on a field or showing the distribution of selected data attributes in branches and leafs. Genomic and proteonomic sequences can also be linked to the tree and extracted from internal and external nodes. A novel clustering algorithm to simplify trees and display the most divergent clades was also developed, where validation can be achieved using the data integration and classification function. Integrated geographical information allows ancestral character reconstruction for phylogeographic plotting based on parsimony and likelihood algorithms. Conclusion: Our software can successfully integrate phylogenetic trees with different data sources, and perform operations to differentiate and visualize those differences within a tree. File support includes the most popular formats such as newick and csv. Exporting visualizations as images, cluster outputs and genomic sequences is supported. Treelink is available as a web and desktop application at http://www. treelinkapp. com.  
  Address [Allende, Christian; Sohn, Erik; Little, Cedric] Univ Adolfo Ibanez, Fac Sci & Engn, Santiago 7941169, Chile, Email: christian.allende.cid@gmail.com  
  Corporate Author Thesis  
  Publisher Biomed Central Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1471-2105 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000367229200001 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 559  
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Author (up) Gatica, M.; Navarro, C.F.; Lavado, A.; Reig, G.; Pulgar, E.; Llanos, P.; Haertel, S.; Ravasio, A.; Bertocchi, C.; Concha, M.L.; Cerda, M. doi  openurl
  Title VolumePeeler: a novel FIJI plugin for geometric tissue peeling to improve visualization and quantification of 3D image stacks Type
  Year 2023 Publication BMC Bioinformatics Abbreviated Journal BMC Bioinformatics  
  Volume 24 Issue 1 Pages 283  
  Keywords Microscopy; Image processing; 3D projections; Virtual 3D peeling  
  Abstract Motivation Quantitative descriptions of multi-cellular structures from optical microscopy imaging are prime to understand the variety of three-dimensional (3D) shapes in living organisms. Experimental models of vertebrates, invertebrates and plants, such as zebrafish, killifish, Drosophila or Marchantia, mainly comprise multilayer tissues, and even if microscopes can reach the needed depth, their geometry hinders the selection and subsequent analysis of the optical volumes of interest. Computational tools to “peel” tissues by removing specific layers and reducing 3D volume into planar images, can critically improve visualization and analysis.Results We developed VolumePeeler, a versatile FIJI plugin for virtual 3D “peeling” of image stacks. The plugin implements spherical and spline surface projections. We applied VolumePeeler to perform peeling in 3D images of spherical embryos, as well as non-spherical tissue layers. The produced images improve the 3D volume visualization and enable analysis and quantification of geometrically challenging microscopy datasets.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1471-2105 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001029240200002 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1853  
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Author (up) Timmermann, T.; Gonzalez, B.; Ruz, G.A. doi  openurl
  Title Reconstruction of a gene regulatory network of the induced systemic resistance defense response in Arabidopsis using boolean networks Type
  Year 2020 Publication Bmc Bioinformatics Abbreviated Journal BMC Bioinformatics  
  Volume 21 Issue 1 Pages 16 pp  
  Keywords Boolean networks; Differential evolution; Gene regulatory networks; Induced systemic resistance; Paraburkholderia phytofirmans; Pseudomonas syringae  
  Abstract Background An important process for plant survival is the immune system. The induced systemic resistance (ISR) triggered by beneficial microbes is an important cost-effective defense mechanism by which plants are primed to an eventual pathogen attack. Defense mechanisms such as ISR depend on an accurate and context-specific regulation of gene expression. Interactions between genes and their products give rise to complex circuits known as gene regulatory networks (GRNs). Here, we explore the regulatory mechanism of the ISR defense response triggered by the beneficial bacterium Paraburkholderia phytofirmans PsJN in Arabidopsis thaliana plants infected with Pseudomonas syringae DC3000. To achieve this, a GRN underlying the ISR response was inferred using gene expression time-series data of certain defense-related genes, differential evolution, and threshold Boolean networks. Results One thousand threshold Boolean networks were inferred that met the restriction of the desired dynamics. From these networks, a consensus network was obtained that helped to find plausible interactions between the genes. A representative network was selected from the consensus network and biological restrictions were applied to it. The dynamics of the selected network showed that the largest attractor, a limit cycle of length 3, represents the final stage of the defense response (12, 18, and 24 h). Also, the structural robustness of the GRN was studied through the networks' attractors. Conclusions A computational intelligence approach was designed to reconstruct a GRN underlying the ISR defense response in plants using gene expression time-series data of A. thaliana colonized by P. phytofirmans PsJN and subsequently infected with P. syringae DC3000. Using differential evolution, 1000 GRNs from time-series data were successfully inferred. Through the study of the network dynamics of the selected GRN, it can be concluded that it is structurally robust since three mutations were necessary to completely disarm the Boolean trajectory that represents the biological data. The proposed method to reconstruct GRNs is general and can be used to infer other biologically relevant networks to formulate new biological hypotheses.  
  Address [Timmermann, Tania; Gonzalez, Bernardo; Ruz, Gonzalo A.] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Lab Bioingn, Santiago, Chile, Email: gonzalo.ruz@uai.cl  
  Corporate Author Thesis  
  Publisher Bmc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1471-2105 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000529043500003 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 1143  
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