Special Issue "Expression Analyses for Biological Pathway Modeling in Drug Discovery"


A special issue of Microarrays (ISSN 2076-3905).

Deadline for manuscript submissions: closed (31 August 2014)

Special Issue Editor

Guest Editor
Prof. Dr. Jacqueline Franke

HTW Berlin, Life Science Engineering, Wilhelminenhofstr. 75A, 12459 Berlin, Germany
Phone: +49 30 5019 43 75
Interests: aging; intracellular transport; telomere function; compound screening; natural products; yeast genetics

Special Issue Information

Dear Colleagues,

Developing new drugs and the identification of their targets is hard and expensive. High-throughput technologies provide for the first time the chance to comprehensively monitor the mode-of-action of small molecules on cellular level. The genomic era has caused a basic change in research, enabling scientists to look more systematically at biological systems. The complete sequencing of the human genome coupled with advances in automation and high-throughput technologies have afforded an important transformation in drug target discovery, towards systematic whole genome and proteome analyses. Novel proteomic techniques enable genome-wide annotation of function in several model organisms. Data derived from whole genome sequence, expression and functional analyses will help to identify causal genes in disease and significantly improve the process of target identification. Moreover, technological progresses in small molecule screening have resulted in the development of efficient and powerful platforms for elucidating the function of modulators of proteins. In addition, microarray based technologies are currently being used to identify targets of orphan small molecules. In this issue we are focusing on new results in microarray based drug discovery research. You are cordially invited to present new material that shows how microarray technologies can contribute to improve the understanding of the function of small molecules in biological networks.

Prof. Dr. Jacqueline Franke
Guest Editor


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.


  • drug discovery
  • target identification
  • chemical biology
  • systems biology
  • pathway analysis

Published Papers (1 paper)

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Open AccessArticle The Robustness of Pathway Analysis in Identifying Potential Drug Targets in Non-Small Cell Lung Carcinoma
Microarrays 2014, 3(4), 212-225; doi:10.3390/microarrays3040212
Received: 21 July 2014 / Revised: 4 October 2014 / Accepted: 13 October 2014 / Published: 27 October 2014
PDF Full-text (513 KB) | HTML Full-text | XML Full-text | Supplementary Files
The identification of genes responsible for causing cancers from gene expression data has had varied success. Often the genes identified depend on the methods used for detecting expression patterns, or on the ways that the data had been normalized and filtered. The [...] Read more.
The identification of genes responsible for causing cancers from gene expression data has had varied success. Often the genes identified depend on the methods used for detecting expression patterns, or on the ways that the data had been normalized and filtered. The use of gene set enrichment analysis is one way to introduce biological information in order to improve the detection of differentially expressed genes and pathways. In this paper we show that the use of network models while still subject to the problems of normalization is a more robust method for detecting pathways that are differentially overrepresented in lung cancer data. Such differences may provide opportunities for novel therapeutics. In addition, we present evidence that non-small cell lung carcinoma is not a series of homogeneous diseases; rather that there is a heterogeny within the genotype which defies phenotype classification. This diversity helps to explain the lack of progress in developing therapies against non-small cell carcinoma and suggests that drug development may consider multiple pathways as treatment targets. Full article
(This article belongs to the Special Issue Expression Analyses for Biological Pathway Modeling in Drug Discovery)

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