Title |
Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks
|
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Published in |
Frontiers in Cell and Developmental Biology, August 2014
|
DOI | 10.3389/fcell.2014.00038 |
Pubmed ID | |
Authors |
Frank Emmert-Streib, Matthias Dehmer, Benjamin Haibe-Kains |
Abstract |
In recent years gene regulatory networks (GRNs) have attracted a lot of interest and many methods have been introduced for their statistical inference from gene expression data. However, despite their popularity, GRNs are widely misunderstood. For this reason, we provide in this paper a general discussion and perspective of gene regulatory networks. Specifically, we discuss their meaning, the consistency among different network inference methods, ensemble methods, the assessment of GRNs, the estimated number of existing GRNs and their usage in different application domains. Furthermore, we discuss open questions and necessary steps in order to utilize gene regulatory networks in a clinical context and for personalized medicine. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | <1% |
Korea, Republic of | 1 | <1% |
Czechia | 1 | <1% |
Brazil | 1 | <1% |
Taiwan | 1 | <1% |
United Kingdom | 1 | <1% |
Unknown | 437 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 99 | 22% |
Student > Bachelor | 58 | 13% |
Student > Master | 55 | 12% |
Researcher | 51 | 11% |
Student > Doctoral Student | 24 | 5% |
Other | 56 | 13% |
Unknown | 101 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 117 | 26% |
Agricultural and Biological Sciences | 73 | 16% |
Computer Science | 40 | 9% |
Engineering | 20 | 5% |
Medicine and Dentistry | 16 | 4% |
Other | 58 | 13% |
Unknown | 120 | 27% |