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Latest Bioinformatic Research

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The Latest Bioinformatic Research blog has been archived.  Although we will no longer be posting to this section, all previous entries will remain viewable. 

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Although there are many visualization tools available, that allow researchers to explore and analyze their cancer datasets, not many of them provide simplified diagrams. To answer the need for simplification, researchers from Bilkent University, Cornell University, and Oregon Health and Science University have a developed a new online tool. Named PathwayMapper, the web editor allows researchers to create more clear pathways and diagrams, similar to those found in The Cancer Genome Atlas.

The online tool can be accessed via the PathwayMapper website (www.pathwaymapper.org) or can be downloaded from the PathwayMapper's Github Page. 

Our Interaction with PathwayMapper

Our brief interaction with the online web version of PathwayMapper showed us just how easy it was to develop sophisticated pathways while keeping things easy to follow and understand. Users can quickly select different node palettes such as the particular gene, complex, family, etc. Another category allows you to create the various interactions that are occurring between the complexes. Additionally, the software allows you to create customizations to the layout, that gives you the most control over the entire design of the pathway. 



Although finding orthologous genes is a major step in phylogenetics, the fact that many of these orthology tools and software utilize extensive amounts of computational resources makes it a challenging issue for researchers. Recently, scientists at the University of California, and UC Davis' Department of Plant Sciences revealed an orthology prediction tool, which can help alleviate this computational matter. The tool is called OrthoReD and was recently published in BMC Bioinformatics by Kai Battenberg, Ernest Lee Dr. Joanna Chiu, Dr. Alison Berry, and Dr. Daniel Potter. 

When OrthoReD was benchmarked against other currently published orthology prediction tools, OrthoReD was able to demonstrate similar biological results, while minimizing the number of computational powers that were needed. An image that describes the overview of how OrthoReD functions can be seen below: 

OrthoReD: Bioinformatic Orthology Prediction Tool With Low Computational Demand


More information on OrthoReD can be viewed in the BMC Bioinformatics journal article: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1726-5



Intervene: Software Package for Genomic Visualization 

A brand new Bioinformatic software has been released that aims at helping researchers with visualizations of multiple gene or genomic regions. The software is called Intervene and it was just published in the journal BMC Bioinformatics. The creators, Dr. Aziz Khan and Dr. Anthony Mathelier from the University of Oslo, state the aim of creating this software was to address the gap that is present within current visualization and intersection software. 



While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited. To address this gap, we have developed the Intervene tool, which provides an easy and automated interface for the effective intersection and visualization of genomic region or list sets, thus facilitating their analysis and interpretation. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps. 

Full information on how to use and install the software can be found at Intervene's documentation website.

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