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Chase A. Miller

dblp:26/9260 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 4 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 79% Computational science and engineering · 21%
Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genome visualization
0.212013
Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web · Bioinform. 2013
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.212013
Scotty: a web tool for designing RNA-Seq experiments to measure differential gene expression · Bioinform. 2013
Bioinformatics and computational biology › genomics › genome visualization
web-based genome browser
0.212013
Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web · Bioinform. 2013
Computational science and engineering
research software infrastructure
0.112012
Biogem: an effective tool-based approach for scaling up open source software development in bioinformatics · Bioinform. 2012
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
0.012013
Scotty: a web tool for designing RNA-Seq experiments to measure differential gene expression · Bioinform. 2013
Visualization and visual analytics
interactive visualization
0.012013
Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web · Bioinform. 2013

Methods — techniques the papers use, named apart from their topics

HTML5 Canvas · 0.3
YearPublicationVenuePosition
2013 Scotty: a web tool for designing RNA-Seq experiments to measure differential gene expression
abstract
Abstract Motivation: A common question arises at the beginning of every experiment where RNA-Seq is used to detect differential gene expression between two conditions: How many reads should we sequence? Results: Scotty is an interactive web-based application that assists biologists to design an experiment with an appropriate sample size and read depth to satisfy the user-defined experimental objectives. This design can be based on data available from either pilot samples or publicly available datasets. Availability: Scotty can be freely accessed on the web at http://euler.bc.edu/marthlab/scotty/scotty.php Contact: [email protected] Supplementary information: Supplementary data are is available at Bioinformatics online.
Michele A. Busby, Chip Stewart, Chase A. Miller, Krzysztof R. Grzeda, Gabor T. Marth
Bioinform.3
2013 Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web
abstract
MOTIVATION: High-throughput biological research requires simultaneous visualization as well as analysis of genomic data, e.g. read alignments, variant calls and genomic annotations. Traditionally, such integrative analysis required desktop applications operating on locally stored data. Many current terabyte-size datasets generated by large public consortia projects, however, are already only feasibly stored at specialist genome analysis centers. As even small laboratories can afford very large datasets, local storage and analysis are becoming increasingly limiting, and it is likely that most such datasets will soon be stored remotely, e.g. in the cloud. These developments will require web-based tools that enable users to access, analyze and view vast remotely stored data with a level of sophistication and interactivity that approximates desktop applications. As rapidly dropping cost enables researchers to collect data intended to answer questions in very specialized contexts, developers must also provide software libraries that empower users to implement customized data analyses and data views for their particular application. Such specialized, yet lightweight, applications would empower scientists to better answer specific biological questions than possible with general-purpose genome browsers currently available. RESULTS: Using recent advances in core web technologies (HTML5), we developed Scribl, a flexible genomic visualization library specifically targeting coordinate-based data such as genomic features, DNA sequence and genetic variants. Scribl simplifies the development of sophisticated web-based graphical tools that approach the dynamism and interactivity of desktop applications. AVAILABILITY AND IMPLEMENTATION: Software is freely available online at http://chmille4.github.com/Scribl/ and is implemented in JavaScript with all modern browsers supported.
Chase A. Miller, Jon S. Anthony, Michelle M. Meyer, Gabor T. Marth
Bioinform.1
2012 Biogem: an effective tool-based approach for scaling up open source software development in bioinformatics
abstract
SUMMARY: Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics. AVAILABILITY: Biogem and modules are free and are OSS. Biogem runs on all systems that support recent versions of Ruby, including Linux, Mac OS X and Windows. Further information at http://www.biogems.info. A tutorial is available at http://www.biogems.info/howto.html CONTACT: [email protected].
Raoul Jean Pierre Bonnal, Jan Aerts, George Githinji, Naohisa Goto, Daniel MacLean, Chase A. Miller, Hiroyuki Mishima, Massimiliano Pagani, Ricardo Ramirez-Gonzalez, Geert Smant, Francesco Strozzi, Rob Syme, Rutger A. Vos, Trevor J. Wennblom, Ben J. Woodcroft, Toshiaki Katayama, Pjotr Prins
Bioinform.6
2011 Bio: : Phylo - phyloinformatic analysis using Perl
abstract
BACKGROUND: Phyloinformatic analyses involve large amounts of data and metadata of complex structure. Collecting, processing, analyzing, visualizing and summarizing these data and metadata should be done in steps that can be automated and reproduced. This requires flexible, modular toolkits that can represent, manipulate and persist phylogenetic data and metadata as objects with programmable interfaces. RESULTS: This paper presents Bio::Phylo, a Perl5 toolkit for phyloinformatic analysis. It implements classes and methods that are compatible with the well-known BioPerl toolkit, but is independent from it (making it easy to install) and features a richer API and a data model that is better able to manage the complex relationships between different fundamental data and metadata objects in phylogenetics. It supports commonly used file formats for phylogenetic data including the novel NeXML standard, which allows rich annotations of phylogenetic data to be stored and shared. Bio::Phylo can interact with BioPerl, thereby giving access to the file formats that BioPerl supports. Many methods for data simulation, transformation and manipulation, the analysis of tree shape, and tree visualization are provided. CONCLUSIONS: Bio::Phylo is composed of 59 richly documented Perl5 modules. It has been deployed successfully on a variety of computer architectures (including various Linux distributions, Mac OS X versions, Windows, Cygwin and UNIX-like systems). It is available as open source (GPL) software from http://search.cpan.org/dist/Bio-Phylo.
Rutger A. Vos, Jason Caravas, Klaas Hartmann, Mark A. Jensen, Chase A. Miller
BMC Bioinform.5