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ToolsDavey, Robert, Savva, George, Dicks, Jo and Roberts, Ian N. (2007) MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets. Bioinformatics, 23 (8). pp. 1023-1025. ISSN 1460-2059
Full text not available from this repository. (Request a copy)Abstract
MPP is a Java application, encompassing both new and established algorithms, for the analysis of gene and marker content datasets arising from high-throughput microarray techniques. MPP analyses flat file output from microarray experiments to determine the probability of the presence or absence of genes or markers within a genome. MPP can construct gene or marker content datasets for a number of genomes and can use the data to estimate an evolutionary tree or network. Results from gene content analyses may be validated by comparing them to known gene contents. MPP was initially developed to analyse data derived from comparative genome hybridization (CGH) microarray experiments in fungi and bacteria. It has recently been adapted to analyse retrotransposon-based insertion polymorphism (RBIP) marker scores derived from tagged microarray marker (TAM) experiments in pea. New analytical procedures may be added easily to MPP as plugins in order to increase the scope of the software.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | algorithms,chromosome mapping,databases, genetic,gene dosage,genetic markers,information storage and retrieval,oligonucleotide array sequence analysis,phylogeny,programming languages,sequence alignment,sequence analysis, dna,software |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Groups > Health in Later Life (former - to 2017) Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
| Depositing User: | Pure Connector |
| Date Deposited: | 06 Jan 2014 14:32 |
| Last Modified: | 01 Dec 2023 02:01 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/47063 |
| DOI: | 10.1093/bioinformatics/btm038 |
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