Special Issue "Advances in Data Analysis Methods and Tools"
A special issue of Microarrays (ISSN 2076-3905).
Deadline for manuscript submissions: 31 August 2014
Dr. Pawel Herzyk
Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
Phone: +44 141 3303180
Interests: next generation sequencing; microarrays; genomics; transcriptomics; data analysis; bioinformatics; data integration
Ever since the first reports of successful application of DNA microarrays appeared in the second half of the 1990s, the technology has matured immensely and gained popularity amongst army of researchers. The density of features has increased dramatically, allowing for manufacturing of whole genome expression arrays or high density SNPs arrays, and was accompanied by massively improved reproducibility of results. This process has been paralleled by dramatic improvements in data analysis methods, which in case of expression arrays, led to confident identification of statistically significant gene/transcript expression changes in complex experiments as well as to demystifying underlying biological processes by linking the resulting gene lists to functional classes, gene networks and biological pathways.
Although recent next generation sequencing technology becomes increasingly popular for applications previously “reserved” for microarrays, e.g., transcriptome profiling, the problems associated with modelling data distribution, data normalisation and subsequent identification of differential expression, make sequencing data analysis challenging and to some extent ambiguous, particularly given small number of replicated samples. Consequently, microarray data analysis seems more robust and better supported, which is particularly important for complex multifactorial experiments.
In this issue we are inviting material about computational methods and tools related to various aspects of microarray data analysis, such as normalisation, statistical analysis, data analysis workflows or functional downstream analysis as applied to wide range of arrays.
Dr. Pawel Herzyk
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microarrays is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
- data analysis
- differential expression
- statistical significance
- pathway analysis
- gene networks
- dimensionality reduction
- copy numbers
- SNP calling
Review: The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack
Microarrays 2013, 2(3), 186-207; doi:10.3390/microarrays2030186
Received: 27 May 2013; in revised form: 2 July 2013 / Accepted: 4 July 2013 / Published: 25 July 2013| Download PDF Full-text (278 KB) | View HTML Full-text | Download XML Full-text
Last update: 19 February 2014