Jeremiah J Faith
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Jeremiah J Faith has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Andrew Olson
Cold Spring Harbor Laboratory , 1 Bungtown Road, Cold Spring Harbor, NY 11724
1 shared publication - David D. Pollock
Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, United States
1 shared publication - Laila A Nahum
Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA
1 shared publication - Matthew T Reynolds
Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803 USA
1 shared publication - Rahul Jonna
Division of Developmental Disabilities, Arizona State Department, Phoenix, AZ 85012 USA
1 shared publication - Ravi Sachidanandam
New York Medical College
1 shared publication
Latest Publications
- Open Access
- 18 September 2007
- Published by Springer Nature in BMC Bioinformatics
- Vol. 8 (1) , 344
Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context
Background: Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. Results: lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. Conclusion: lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.
- 18 September 2007
- Published by Springer Nature in BMC Bioinformatics
- Vol. 8 (1) , 344
Open AccessLightweight genome viewer: portable software for browsing genomics data in its chromosomal context
Background: Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. Results: lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. Conclusion: lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.
- Open Access
- 26 September 2006
- Published by Springer Nature in BMC Bioinformatics
- Vol. 7 (S2) , S7
EGenBio: A Data Management System for Evolutionary Genomics and Biodiversity
Background: Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed E volutionary Gen omics and Bio diversity (EGenBio; http://egenbio.lsu.edu) to begin to address this. Description: EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs. Conclusion: EGenBio was designed to serve as a platform for tools and resources to ease combined analysis in evolution, genomics, and biodiversity.
- 26 September 2006
- Published by Springer Nature in BMC Bioinformatics
- Vol. 7 (S2) , S7
Open AccessEGenBio: A Data Management System for Evolutionary Genomics and Biodiversity
Background: Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed E volutionary Gen omics and Bio diversity (EGenBio; http://egenbio.lsu.edu) to begin to address this. Description: EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs. Conclusion: EGenBio was designed to serve as a platform for tools and resources to ease combined analysis in evolution, genomics, and biodiversity.