scholarly journals CoralP: Flexible visualization of the human phosphatome

2019 ◽  
Author(s):  
Amit Min ◽  
Erika Deoudes ◽  
Marielle L. Bond ◽  
Eric S. Davis ◽  
Douglas H. Phanstiel
Keyword(s):  
Web Application ◽  
Protein Phosphatases ◽  
Source Code ◽  
Protein Family ◽  
Biological Processes ◽  
Important Class ◽  
Pharmaceutical Development ◽  
Link Type ◽  
Phosphoryl Groups ◽  
Publication Quality

Protein phosphatases and kinases play critical roles in a host of biological processes and diseases via the removal and addition of phosphoryl groups. While kinases have been extensively studied for decades, recent findings regarding the specificity and activities of phosphatases have generated an increased interest in targeting phosphatases for pharmaceutical development. This increased focus has created a need for methods to visualize this important class of proteins within the context of the entire phosphatase protein family. Here, we present CoralP, an interactive web application for the generation of customizable, publication-quality representations of human phosphatome data. Phosphatase attributes can be encoded through edge colors, node colors, and node sizes. CoralP is the first and currently the only tool designed for phosphatome visualization and should be of great use to the signaling community. The source code and web application are available at https://github.com/PhanstielLab/coralp and http://phanstiel-lab.med.unc.edu/coralp respectively.

scholarly journals Knowledge.Bio: A Web Application for Exploring, Building and Sharing Webs of Biomedical Relationships Mined from PubMed

2016 ◽  
Author(s):  
Richard Bruskiewich ◽  
Kenneth Huellas-Bruskiewicz ◽  
Farzin Ahmed ◽  
Rajaram Kaliyaperumal ◽  
Mark Thompson ◽  
...  
Keyword(s):  
User Interface ◽  
Text Mining ◽  
Graphical User Interface ◽  
Biomedical Research ◽  
Web Application ◽  
Source Code ◽  
Research Literature ◽  
Knowledge Networks ◽  
Link Type ◽  
Web Platform

AbstractKnowledge.Bio is a web platform that enhances access and interpretation of knowledge networks extracted from biomedical research literature. The interaction is mediated through a collaborative graphical user interface for building and evaluating maps of concepts and their relationships, alongside associated evidence. In the first release of this platform, conceptual relations are drawn from the Semantic Medline Database and the Implicitome, two compleme ntary resources derived from text mining of PubMed abstracts.Availability— Knowledge.Bio is hosted at http://knowledge.bio/ and the open source code is available at http://bitbucket.org/sulab/kb1/.Contact— [email protected]; [email protected]

scholarly journals CLINE: a web-tool for the comparison of biological dendrogram structures

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Rodolfo S. Allendes Osorio ◽  
Lokesh P. Tripathi ◽  
Kenji Mizuguchi
Keyword(s):  
User Interface ◽  
Open Access ◽  
Special Interest ◽  
Web Application ◽  
Source Code ◽  
Visualization Tool ◽  
Web Tool ◽  
Link Type ◽  
Multiple Structures ◽  
Biological Interpretation

Abstract Background When visually comparing the results of hierarchical clustering, the differences in the arrangements of components are of special interest. However, in a biological setting, identifying such differences becomes less straightforward, as the changes in the dendrogram structure caused by permuting biological replicates, do not necessarily imply a different biological interpretation. Here, we introduce a visualization tool to help identify biologically similar topologies across different clustering results, even in the presence of replicates. Results Here we introduce CLINE, an open-access web application that allows users to visualize and compare multiple dendrogram structures, by visually displaying the links between areas of similarity across multiple structures. Through the use of a single page and a simple user interface, the user is able to load and remove structures form the visualization, change some aspects of their display and set the parameters used to match cluster topology across consecutive pairs of dendrograms. Conclusions We have implemented a web-tool that allows the users to visualize different dendrogram structures, showing not only the structures themselves, but also linking areas of similarity across multiple structures. The software is freely available at http://mizuguchilab.org/tools/cline/. Also, the source code, documentation and installation instructions are available on GitHub at https://github.com/RodolfoAllendes/cline/.

scholarly journals Logomaker: Beautiful sequence logos in python

2019 ◽  
Author(s):  
Ammar Tareen ◽  
Justin B. Kinney
Keyword(s):  
Source Code ◽  
Biological Properties ◽  
Programming Environment ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Multiple Sequence Alignments ◽  
Link Type ◽  
Sequence Logos ◽  
Python Programming ◽  
Publication Quality

AbstractSequence logos are visually compelling ways of illustrating the biological properties of DNA, RNA, and protein sequences, yet it is currently difficult to generate such logos within the Python programming environment. Here we introduce Logomaker, a Python API for creating publication-quality sequence logos. Logomaker can produce both standard and highly customized logos from any matrix-like array of numbers. Logos are rendered as vector graphics that are easy to stylize using standard matplotlib functions. Methods for creating logos from multiple-sequence alignments are also included.Availability and ImplementationLogomaker can be installed using the pip package manager and is compatible with both Python 2.7 and Python 3.6. Source code is available athttp://github.com/jbkinney/logomaker.Supplemental InformationDocumentation is provided athttp://[email protected].

scholarly journals Intervene: a tool for intersection and visualization of multiple gene or genomic region sets

2017 ◽  
Author(s):  
Aziz Khan ◽  
Anthony Mathelier
Keyword(s):  
Web Application ◽  
High Throughput Sequencing ◽  
Genomic Region ◽  
Web Interface ◽  
Multiple Gene ◽  
Link Type ◽  
Common Task ◽  
Computer Scientists ◽  
Genomic Regions ◽  
Publication Quality

AbstractBackgroundA common task for scientists relies on comparing lists of genes or genomic regions derived from high-throughput sequencing experiments. While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited.ResultsTo 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. Intervene, and its interactive web ShinyApp companion, generate publication-quality figures for the interpretation of genomic region and list sets.ConclusionsIntervene and its web application companion provide an easy command line, and an interactive web interface to compute intersections of multiple genomic and list sets. They also have the capacity to plot intersections using easy-to-interpret visual approaches. Intervene is developed and designed to meet the needs of both computer scientists and biologists. The source code is freely available at https://bitbucket.org/CBGR/intervene, with the web application available at https://asntech.shinyapps.io/intervene.

scholarly journals Varapp: A reactive web-application for variants filtering

2016 ◽  
Author(s):  
Julien Delafontaine ◽  
Alexandre Masselot ◽  
Robin Liechti ◽  
Dmitry Kuznetsov ◽  
Ioannis Xenarios ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Web Application ◽  
De Novo ◽  
Source Code ◽  
Regions Of Interest ◽  
Mendelian Diseases ◽  
Link Type ◽  
Large Sets ◽  
Front End

AbstractSummary: Varapp is an open-source web application to filter variants from large sets of exome data stored in a relational database. Varapp offers a reactive graphical user interface, very fast data pro-cessing, security and facility to save, reproduce and shareresults. Typically, a few seconds suffice to apply non-trivial filters to a set of half a million variants and extract a handful of potential clinically relevant targets. Varapp implements different scenarios for Mendelian diseases (dominant, recessive, de novo, X-linked, andcompound heterozygous), and allows searching for variants in genes or chro-mosomal regions of interest.Availability: The application is made of a Javascript front-end and a Python back-end. Its source code is hosted at https://github.com/varapp. A demo version isavailable at https://varapp-demo.vital-it.ch. The full documentation can be found at https://varapp-demo.vital-it.ch/docs.Contact:[email protected]

scholarly journals fsbrain: an R package for the visualization of structural neuroimaging data

2020 ◽  
Author(s):  
Tim Schäfer ◽  
Christine Ecker
Keyword(s):  
Source Code ◽  
R Package ◽  
Three Dimensions ◽  
Structural Neuroimaging ◽  
Link Type ◽  
Neuroimaging Data ◽  
Voxel Data ◽  
Statistical Results ◽  
Publication Quality

AbstractSummaryWe introduce fsbrain, an R package for the visualization of neuroimaging data. The package can be used to visualize vertex-wise and region-wise morphometry data, parcellations, labels and statistical results on brain surfaces in three dimensions (3D). Voxel data can be displayed in lightbox mode. The fsbrain package offers various customization options and produces publication quality plots which can be displayed interactively, saved as bitmap images, or integrated into R notebooks.Availability and ImplementationThe software, source code and documentation are available under the MIT license at https://github.com/dfsp-spirit/fsbrain. Releases can be installed directly from the Comprehensive R Archive Network (CRAN)[email protected]

scholarly journals Gilda: biomedical entity text normalization with machine-learned disambiguation as a service

2021 ◽  
Author(s):  
Benjamin M. Gyori ◽  
Charles Tapley Hoyt ◽  
Albert Steppi
Keyword(s):  
Small Molecules ◽  
Web Service ◽  
Source Code ◽  
String Matching ◽  
Software Tool ◽  
Biological Processes ◽  
Biomedical Ontologies ◽  
Matching Algorithm ◽  
Link Type ◽  
Text Normalization

AbstractSummaryGilda is a software tool and web service which implements a scored string matching algorithm for names and synonyms across entries in biomedical ontologies covering genes, proteins (and their families and complexes), small molecules, biological processes and diseases. Gilda integrates machine-learned disambiguation models to choose between ambiguous strings given relevant surrounding text as context, and supports species-prioritization in case of ambiguity.AvailabilityThe Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials are available via https://github.com/indralab/[email protected]

scholarly journals clinker & clustermap.js: Automatic generation of gene cluster comparison figures

2020 ◽  
Author(s):  
Cameron L.M. Gilchrist ◽  
Yit-Heng Chooi
Keyword(s):  
Gene Cluster ◽  
Evolutionary History ◽  
Source Code ◽  
Gene Clusters ◽  
Automatic Generation ◽  
Biological Pathways ◽  
Link Type ◽  
E Mail ◽  
Python Package ◽  
Publication Quality

AbstractSummaryGenes involved in biological pathways are often collocalised in gene clusters, the comparison of which can give valuable insights into their function and evolutionary history. However, comparison and visualisation of gene cluster homology is a tedious process, particularly when many clusters are being compared. Here, we present clinker, a Python based tool, and clustermap.js, a companion JavaScript visualisation library, which used together can automatically generate accurate, interactive, publication-quality gene cluster comparison figures directly from sequence files.Availability and ImplementationSource code and documentation for clinker and clustermap.js is available on GitHub (github.com/gamcil/clinker and github.com/gamcil/clustermap.js, respectively) under the MIT license. clinker can be installed directly from the Python Package Index via pip.ContactE-mail: [email protected], [email protected]

scholarly journals myCircos: Facilitating the Creation and Use of Circos Plots Online

2016 ◽  
Author(s):  
Caroline Labelle ◽  
Geneviève Boucher ◽  
Sébastien Lemieux
Keyword(s):  
User Interface ◽  
Web Application ◽  
Graphical Representation ◽  
Source Code ◽  
Command Line ◽  
Genomic Information ◽  
Link Type ◽  
Intuitive User Interface ◽  
The Creation

AbstractCircos plots were designed to display large amounts of processed genomic information on a single graphical representation. The creation of such plots remains challenging for less technical users as the leading tool requires command-line proficiency. Here, we introduce myCircos, a web application that facilitates the generation of Circos plots by providing an intuitive user interface, adding interactive functionalities to the representation and providing persistence of previous requests. myCircos is available at: http://mycircos.iric.ca. Non registered users can explore the application through the Guest user. Source code (for local server installation) is available upon request.

scholarly journals GenFam: A web application and database for gene family-based classification and functional enrichment analysis

2018 ◽  
Author(s):  
Renesh Bedre ◽  
Kranthi Mandadi
Keyword(s):  
Gene Family ◽  
Web Application ◽  
High Throughput Sequencing ◽  
Source Code ◽  
Enrichment Analysis ◽  
Gene Families ◽  
Functional Enrichment ◽  
Multiple Testing Correction ◽  
Web Based ◽  
Link Type

ABSTRACTGenome-scale studies using high-throughput sequencing (HTS) technologies generate substantial lists of differentially expressed genes under different experimental conditions. These gene lists need to be further mined to narrow down biologically relevant genes and associated functions in order to guide downstream functional genetic analyses. A popular approach is to determine statistically overrepresented genes in a user-defined list through enrichment analysis tools, which rely on functional annotations of genes based on Gene Ontology (GO) terms. Here, we propose a new approach, GenFam, which allows classification and enrichment of genes based on their gene family, thus simplifying identification of candidate gene families and associated genes that may be relevant to the query. GenFam and its integrated database comprises of three-hundred and eighty-four unique gene families and supports gene family classification and enrichment analyses for sixty plant genomes. Four comparative case studies with plant species belonging to different clades and families were performed using GenFam which demonstrated its robustness and comprehensiveness over preexisting functional enrichment tools. To make it readily accessible for plant biologists, GenFam is available as a web-based application where users can input gene IDs and export enrichment results in both tabular and graphical formats. Users can also customize analysis parameters by choosing from the various statistical enrichment tests and multiple testing correction methods. Additionally, the web-based application, source code and database are freely available to use and download. Website: http://mandadilab.webfactional.com/home/. Source code and database: http://mandadilab.webfactional.com/home/dload/.

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