Analysing Microarray Data using the Multi-functional Immune Ontologiser
Gene expression microarrays are a prominent experimental tool in functional genomics allowing researchers to gain a deeper understanding of biological processes. To date, no such tool has been developed to allow researchers with a specialised biological research interest to distinctively identify th...
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doaj-f6ac0fa592404b3eaecc2a42b3b3c8d82021-09-06T19:40:30ZengDe GruyterJournal of Integrative Bioinformatics1613-45162006-12-0132143610.1515/jib-2006-25biecoll-jib-2006-25Analysing Microarray Data using the Multi-functional Immune OntologiserKhalid Sabah0Khan Mohsin1Wang Ping2Liu Xiaohui3Li Suling4Molecular Immunology Group, Microarray Facility, Division of BioSciences, Brunel University, Uxbridge, UB8 3PH, UK United Kingdom of Great Britain and Northern IrelandMolecular Immunology Group, Microarray Facility, Division of BioSciences, Brunel University, Uxbridge, UB8 3PH, United Kingdom of Great Britain and Northern IrelandImmunology Group, Institute of Cell and Molecular Sciences, Barts and London School of Medicine, London, United Kingdom of Great Britain and Northern IrelandIntelligent Data Analysis Group, Department of Information Systems and Computing, Brunel University, Uxbridge, UB8 3PH, United Kingdom of Great Britain and Northern IrelandMolecular Immunology Group, Microarray Facility, Division of BioSciences, Brunel University, Uxbridge, UB8 3PH, United Kingdom of Great Britain and Northern IrelandGene expression microarrays are a prominent experimental tool in functional genomics allowing researchers to gain a deeper understanding of biological processes. To date, no such tool has been developed to allow researchers with a specialised biological research interest to distinctively identify those genes and gene functionalities associated more strongly with the research area. Based on this functional analysis capability we present a specialised multi-functional Immune Ontologiser – a software, specialised for immunologists to annotate multiple genes from microarray datasets within two new ontologies: a newly structured Immune Ontology focussed at immunology and haematology and a uniquely curated ImmunoArray-PubOntology. The Immune Ontology functionally annotates genes identifying immunology related functions enriched with upregulated or downregulated genes of interest. The ImmunoArray-PubOntology compares and contrasts gene functionality of microarray datasets, comparing genes of interest with the differential gene expression matrices published amongst immunologyrelated microarray literature. This aspect facilitates literature mining by extracting publications containing gene sets of interest in a well-structured immunological context where the literature has been categorised according to disease types. The software consists of a query-optimised database of two parts – the ImmunoGene-database and a unique Database of Immunological Microarray Publications (DIMP) to provide the user with a more detailed insight into other studies involving their genes and research groups investigating similar research areas. Using our Immune Ontologiser software to analyse tolerance array data we identify 70 interesting up-regulated genes in terms of their functionality within tolerance. Furthermore, from these 70 genes we identify 15 genes to have immunology-related functions. More interestingly, the remaining 55 genes were not previously known to be directly involved within the immunology related condition and hence we have identified target genes for future investigation. Among the 70 genes, 21 have been identified by our software to be studied within various immunology-related diseases via microarray experiments performed by other laboratories.https://doi.org/10.1515/jib-2006-25ontologyimmunologyliterature miningmicroarraysimmune tolerance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Khalid Sabah Khan Mohsin Wang Ping Liu Xiaohui Li Suling |
spellingShingle |
Khalid Sabah Khan Mohsin Wang Ping Liu Xiaohui Li Suling Analysing Microarray Data using the Multi-functional Immune Ontologiser Journal of Integrative Bioinformatics ontology immunology literature mining microarrays immune tolerance |
author_facet |
Khalid Sabah Khan Mohsin Wang Ping Liu Xiaohui Li Suling |
author_sort |
Khalid Sabah |
title |
Analysing Microarray Data using the Multi-functional Immune Ontologiser |
title_short |
Analysing Microarray Data using the Multi-functional Immune Ontologiser |
title_full |
Analysing Microarray Data using the Multi-functional Immune Ontologiser |
title_fullStr |
Analysing Microarray Data using the Multi-functional Immune Ontologiser |
title_full_unstemmed |
Analysing Microarray Data using the Multi-functional Immune Ontologiser |
title_sort |
analysing microarray data using the multi-functional immune ontologiser |
publisher |
De Gruyter |
series |
Journal of Integrative Bioinformatics |
issn |
1613-4516 |
publishDate |
2006-12-01 |
description |
Gene expression microarrays are a prominent experimental tool in functional genomics allowing researchers to gain a deeper understanding of biological processes. To date, no such tool has been developed to allow researchers with a specialised biological research interest to distinctively identify those genes and gene functionalities associated more strongly with the research area. Based on this functional analysis capability we present a specialised multi-functional Immune Ontologiser – a software, specialised for immunologists to annotate multiple genes from microarray datasets within two new ontologies: a newly structured Immune Ontology focussed at immunology and haematology and a uniquely curated ImmunoArray-PubOntology. The Immune Ontology functionally annotates genes identifying immunology related functions enriched with upregulated or downregulated genes of interest. The ImmunoArray-PubOntology compares and contrasts gene functionality of microarray datasets, comparing genes of interest with the differential gene expression matrices published amongst immunologyrelated microarray literature. This aspect facilitates literature mining by extracting publications containing gene sets of interest in a well-structured immunological context where the literature has been categorised according to disease types. The software consists of a query-optimised database of two parts – the ImmunoGene-database and a unique Database of Immunological Microarray Publications (DIMP) to provide the user with a more detailed insight into other studies involving their genes and research groups investigating similar research areas. Using our Immune Ontologiser software to analyse tolerance array data we identify 70 interesting up-regulated genes in terms of their functionality within tolerance. Furthermore, from these 70 genes we identify 15 genes to have immunology-related functions. More interestingly, the remaining 55 genes were not previously known to be directly involved within the immunology related condition and hence we have identified target genes for future investigation. Among the 70 genes, 21 have been identified by our software to be studied within various immunology-related diseases via microarray experiments performed by other laboratories. |
topic |
ontology immunology literature mining microarrays immune tolerance |
url |
https://doi.org/10.1515/jib-2006-25 |
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