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Updated: Jul 18, 2026
10:56
Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Published on: May 17, 2014
GeneSpeed: protein domain organization of the transcriptome
Alecksandr Kutchma1, Nayeem Quayum, Jan Jensen
1Barbara Davis Center for Childhood Diabetes, University of Colorado at Denver and Health Sciences Center, 1775 North Ursula Street, Mail Stop B140, PO Box 6511, Denver, CO, 80045, USA.
Nucleic Acids Research
|November 30, 2006
Summary
The GeneSpeed database offers protein domain homology analysis across four species' transcriptomes. It integrates gene expression data for comprehensive gene family studies.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Protein domain homology is crucial for understanding gene function and evolution.
- Analyzing transcriptomes requires robust tools for domain annotation and expression profiling.
Purpose of the Study:
- To develop and present the GeneSpeed database, a resource for studying protein domain homology in transcriptomes.
- To integrate diverse datasets for comprehensive gene family analysis and expression profiling.
Main Methods:
- Utilized HOWARD parallel cluster technology for exhaustive tBLASTn searches against PFAM domain classes.
- Annotated Unigene clusters with protein domain presence and performed custom transcription factor-family curation.
- Integrated Gene Ontology classifications and Novartis SymAtlas2 expression data for human and mouse.
Main Results:
- The GeneSpeed database provides complete protein domain annotation for Unigene clusters in four model organisms.
- Users can search and browse data by domain content, gene identifiers, or expression patterns.
- Facilitates supervised, hierarchical analysis of gene families linked to tissue-based expression datasets.
Conclusions:
- GeneSpeed serves as a valuable online resource for detailed protein domain homology studies.
- The integration of domain annotation, functional classification, and expression data enhances biological research.
- Enables efficient exploration of gene families and their expression profiles across multiple species.
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