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Computational Modeling and Analysis of Microarray Data: New Horizons
High-throughput microarray technologies have long been a source of data for a wide range of biomedical investigations. Over the decades, variants have been developed and sophistication of measurements has improved, with generated data providing both valuable insight and considerable analytical chall...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5197945/ https://www.ncbi.nlm.nih.gov/pubmed/27775644 http://dx.doi.org/10.3390/microarrays5040026 |
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author | Ruskin, Heather J. |
author_facet | Ruskin, Heather J. |
author_sort | Ruskin, Heather J. |
collection | PubMed |
description | High-throughput microarray technologies have long been a source of data for a wide range of biomedical investigations. Over the decades, variants have been developed and sophistication of measurements has improved, with generated data providing both valuable insight and considerable analytical challenge. The cost-effectiveness of microarrays, as well as their fundamental applicability, made them a first choice for much early genomic research and efforts to improve accessibility, quality and interpretation have continued unabated. In recent years, however, the emergence of new generations of sequencing methods and, importantly, reduction of costs, has seen a preferred shift in much genomic research to the use of sequence data, both less ‘noisy’ and, arguably, with species information more directly targeted and easily interpreted. Nevertheless, new microarray data are still being generated and, together with their considerable legacy, can offer a complementary perspective on biological systems and disease pathogenesis. The challenge now is to exploit novel methods for enhancing and combining these data with those generated by alternative high-throughput techniques, such as sequencing, to provide added value. Augmentation and integration of microarray data and the new horizons this opens up, provide the theme for the papers in this Special Issue. |
format | Online Article Text |
id | pubmed-5197945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-51979452017-01-04 Computational Modeling and Analysis of Microarray Data: New Horizons Ruskin, Heather J. Microarrays (Basel) Editorial High-throughput microarray technologies have long been a source of data for a wide range of biomedical investigations. Over the decades, variants have been developed and sophistication of measurements has improved, with generated data providing both valuable insight and considerable analytical challenge. The cost-effectiveness of microarrays, as well as their fundamental applicability, made them a first choice for much early genomic research and efforts to improve accessibility, quality and interpretation have continued unabated. In recent years, however, the emergence of new generations of sequencing methods and, importantly, reduction of costs, has seen a preferred shift in much genomic research to the use of sequence data, both less ‘noisy’ and, arguably, with species information more directly targeted and easily interpreted. Nevertheless, new microarray data are still being generated and, together with their considerable legacy, can offer a complementary perspective on biological systems and disease pathogenesis. The challenge now is to exploit novel methods for enhancing and combining these data with those generated by alternative high-throughput techniques, such as sequencing, to provide added value. Augmentation and integration of microarray data and the new horizons this opens up, provide the theme for the papers in this Special Issue. MDPI 2016-10-21 /pmc/articles/PMC5197945/ /pubmed/27775644 http://dx.doi.org/10.3390/microarrays5040026 Text en © 2016 by the author; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Editorial Ruskin, Heather J. Computational Modeling and Analysis of Microarray Data: New Horizons |
title | Computational Modeling and Analysis of Microarray Data: New Horizons |
title_full | Computational Modeling and Analysis of Microarray Data: New Horizons |
title_fullStr | Computational Modeling and Analysis of Microarray Data: New Horizons |
title_full_unstemmed | Computational Modeling and Analysis of Microarray Data: New Horizons |
title_short | Computational Modeling and Analysis of Microarray Data: New Horizons |
title_sort | computational modeling and analysis of microarray data: new horizons |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5197945/ https://www.ncbi.nlm.nih.gov/pubmed/27775644 http://dx.doi.org/10.3390/microarrays5040026 |
work_keys_str_mv | AT ruskinheatherj computationalmodelingandanalysisofmicroarraydatanewhorizons |