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software.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
<meta name="author" content="">
<title>Software</title>
<!-- Loads Bootstrap 4 -->
<script src="https://code.jquery.com/jquery-3.3.1.slim.min.js"
integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo"
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<link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/css/bootstrap.min.css"
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crossorigin="anonymous"></script>
<!-- Loads CSS -->
<link href="css/styles.css" rel="stylesheet">
<!-- Loads fonts -->
<link href="font-awesome/css/font-awesome.min.css" rel="stylesheet" type="text/css">
<link href="https://fonts.googleapis.com/css?family=Nunito&display=swap" rel="stylesheet">
<link href="https://fonts.googleapis.com/css?family=Rubik&display=swap" rel="stylesheet">
</head>
<body>
<!-- Navigation bar -->
<div id="nav"></div>
<script type="text/javascript" src="js/header.js"></script>
<!-- Page Content -->
<div class="container">
<!-- Page Heading/Breadcrumbs -->
<div class="top-row row">
<div class="col-12">
<h1 class="page-header">CSBIO Research</h1>
</div>
</div>
<hr class="large-break">
<!-- Project 1 -->
<div class="card mb-3 p-3">
<div class="row no-gutters">
<div class="col-md-4">
<a href="https://github.com/csbio/">
<img class="img-fluid img-hover d-block" src="images/Software/GitHub-Mark.png" alt="">
</a>
</div>
<div class="col-md-8">
<div class="card-body">
<h4 class="card-title">GitHub</h4>
<p class="card-text">Our lab GitHub page where we keep our code</p>
<a class="btn btn-primary" href="https://github.com/csbio/">View Project</a>
</div>
</div>
</div>
</div>
<hr class="small-break">
<!-- Project 2 -->
<div class="card mb-3 p-3 border-0">
<div class="row no-gutters">
<div class="col-md-4">
<a href="http://mosaic.cs.umn.edu">
<img class="img-fluid img-hover d-block" src="images/Software/mosaic.png" alt="">
</a>
</div>
<div class="col-md-8">
<h4 class="card-title">Mosaic</h4>
<h5 class="card-subtitle mb-2 text-muted">Mechanism Of Action In Compounds</h5>
<p class="card-text">The MOSAIC database is a queryable web interface for browsing chemical genetic
interaction data, molecular target predictions based on genetic interactions, Gene Ontology biological
process predictions, chemical genetic profile similarity and compound structural similarity. Compounds,
genes, and Gene Ontology terms are queryable using MOSAIC. The MOSAIC database is generated from publicly
released data from the yeast chemical genomics project</p>
<a class="btn btn-primary" href="http://mosaic.cs.umn.edu">View Project</a>
</div>
</div>
</div>
<hr class="small-break">
<!-- Project 3 -->
<div class="card mb-3 p-3 border-0">
<div class="row no-gutters">
<div class="col-md-4 h-100 d-flex ">
<a href="/software.html">
<img class="img-fluid img-hover mx-auto d-block" src="images/Network.jpg" alt="">
</a>
</div>
<div class="col-md-8">
<h4 class="card-title">neXus</h4>
<h5 class="card-subtitle mb-2 text-muted">Network - cross(X)-species - Search</h5>
<p class="card-text">neXus is an active subnetwork search algorithm that has been designed to discover conserved
subnetworks in the functional linkage networks that are enriched for active genes (such as high foldchange
genes in microarray). The algorithm associates statistical significance to each subnetwork that is
indicative of how possible such a clustering of genes is when the neXus is run on randomly set of active
genes. In the paper [1], the algorithm was used on human and mouse microarray expression data of stem cell
with respect to differentiating cells to discover conserved subnetworks representative of stem cell
functions in the two species. Variations of the algorithm have been used to discover species specific
subnetworks and on single species context. Python implementation of the algorithm is available at
http://csbio.cs.umn.edu/neXus/help.html.
</p>
<a class="btn btn-primary" href="http://csbio.cs.umn.edu/neXus/help.html">View Project</a>
<div class="card-footer text-muted mt-3 bg-transparent">
<p class="card-text">Associated publications: </p>
<p class="card-text">[1] Deshpande R, Sharma S, Verfaillie CM, Hu W, Myers CL: A
Scalable Approach for Discovering Conserved Active Subnetworks across Species. PLoS Comput Biol 2010
Dec;6(12):e1001028. http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001028</p>
</div>
</div>
</div>
</div>
<hr class="small-break">
<!-- Project 4 -->
<div class="card mb-3 p-3 border-0">
<div class="row no-gutters">
<div class="col-md-4">
<a href="http://function.princeton.edu/GRIFn/">
<img class="img-fluid img-hover mx-auto d-block" src="images/Software/GRIFn.jpg" alt="">
</a>
</div>
<div class="col-md-8">
<h4 class="card-title">GRIFn</h4>
<h5 class="card-subtitle mb-2 text-muted">Gene Relationship Identification in Functional data</h5>
<p class="card-text">GRIFn is a system for evaluation of datasets and methods using a functional genomics gold
standard based on
curation by expert biolgists. It allows users to assess the ability of their datasets or methods to
recapitulate known biology both in a global sense and in the context of specific biological processes. GRIFn
allows enables fair comparisons between various data types and methods.
</p>
<a class="btn btn-primary" href="http://function.princeton.edu/GRIFn/">View Project</a>
<div class="card-footer text-muted mt-3 bg-transparent">
<p class="card-text">Associated publications: </p>
<p class="card-text"> [1] Myers CL, Barrett D, Hibbs MA, Huttenhower C, Troyanskaya OG: Finding function:
evaluation methods for functional genomic data. BMC Genomics 2006, 7:187</p>
</div>
</div>
</div>
</div>
<hr class="small-break">
<!-- Project 5 -->
<div class="card mb-3 p-3 border-0">
<div class="row no-gutters">
<div class="col-md-4">
<a href="http://imp.princeton.edu/">
<img class="img-fluid img-hover mx-auto d-block" src="images/Software/bioPIXIE.jpg" alt="">
</a>
</div>
<div class="col-md-8">
<h4 class="card-title">bioPIXIE</h4>
<h5 class="card-subtitle mb-2 text-muted bg-transparent">Biological Pathway Inference from eXperimental
Interaction Evidence
</h5>
<p class="card-text">bioPIXIE is a novel system for biological data integration and visualization for S.
cerevisiae. It allows the user to discover interaction networks and pathways in which the user's gene(s) of
interest participate. The system is based on a Bayesian algorithm for identification of biological networks
based on integrated diverse genomic data. </p>
<a class="btn btn-primary" href="http://imp.princeton.edu/">View Project</a>
<div class="card-footer text-muted mt-3">
<p class="card-text">Associated publications: </p>
<p class="card-text"> [1] Myers CL, Robson D, Wible A, Hibbs M, Chiriac C, Theesfeld CL, Dolinski K,
Troyanskaya OG: Discovery of biological networks from diverse functional genomic data. Genome Biology
2005, 6(13):R114.</p>
</div>
</div>
</div>
</div>
<hr class="small-break">
<!-- Project 6 -->
<div class="card mb-3 p-3 border-0">
<div class="row no-gutters">
<div class="col-md-4">
<a href="http://function.princeton.edu/ChARMview/">
<img class="img-fluid img-hover mx-auto d-block" src="images/Software/ChARMview.jpg" alt="">
</a>
</div>
<div class="col-md-8">
<h4 class="card-title">ChARMview</h4>
<h5 class="card-subtitle mb-2 text-muted bg-transparent">Chromosomal Abberation Region Miner and Viewer</h5>
<p class="card-text">
ChARMView is a visualization and analysis system for guided discovery of chromosomal abnormalities from
microarray data. Our system facilitates manual or automated discovery of aneuploidies through dynamic
visualization and integrated statistical analysis. ChARMView can be used with array CGH and gene expression
microarray data, and multiple experiments can be viewed and analyzed simultaneously.
</p>
<a class="btn btn-primary" href="http://function.princeton.edu/ChARMview/">View Project</a>
<div class="card-footer text-muted mt-3">
<p class="card-text">Associated publications: </p>
<p class="card-text">[1] Myers CL, Chen X, Troyanskaya OG: Visualization-based discovery and analysis of
genomic abberations in microarray data. BMC Bioinformatics, 6:146, 2005.</p>
<p class="card-text">[2] Myers CL, Dunham M, Kung SY, Troyanskaya OG: Accurate detection of aneuploidies in
array CGH and gene expression microarray data. Bioinformatics, 20:3533-3543, 2004.</p>
</div>
</div>
</div>
</div>
<hr class="small-break">
<!-- Project 7 -->
<div class="card mb-3 p-3 border-0">
<div class="row no-gutters">
<div class="col-md-4">
<a href="#">
<img class="img-fluid img-hover mx-auto d-block" src="images/Software/GOLEM.jpg" alt="">
</a>
</div>
<div class="col-md-8">
<h4 class="card-title">GOLEM</h4>
<h5 class="card-subtitle mb-2 text-muted bg-transparent">Gene Ontology Local Exploration Map</h5>
<p class="card-text">GOLEM is a tool for viewing, navigating, and analyzing the hierarchical structure and
annotations to the gene ontology. The visualization component allows a user to see the local graph structure
around a GO term of interest and navigate to nearby nodes. GOLEM also provides the ability to look for
statistical enrichment of GO terms in lists of genes and then observe the relationships between those terms.
GOLEM is available both as an applet for use online and as a standalone download.</p>
<a class="btn btn-primary" href="#">View Project</a>
<div class="card-footer text-muted mt-3">
<p class="card-text">[1] Sealfon RSG, Hibbs MA, Huttenhower C, Myers CL, Troyanskaya OG: GOLEM: an
interactive graph-based gene ontology navigation and analysis tool. BMC Bioinformatics 2006, 7:443.</p>
</div>
</div>
</div>
</div>
<hr class="small-break">
<!-- Footer -->
<script type="text/javascript" src="js/footer.js"></script>
</div>
<!-- /.container -->
<!-- jQuery -->
<script src="js/jquery.js"></script>
</body>
</html>