Title |
Targeting molecular networks for drug research
|
---|---|
Published in |
Frontiers in Genetics, June 2014
|
DOI | 10.3389/fgene.2014.00160 |
Pubmed ID | |
Authors |
José P. Pinto, Rui S. R. Machado, Joana M. Xavier, Matthias E. Futschik |
Abstract |
The study of molecular networks has recently moved into the limelight of biomedical research. While it has certainly provided us with plenty of new insights into cellular mechanisms, the challenge now is how to modify or even restructure these networks. This is especially true for human diseases, which can be regarded as manifestations of distorted states of molecular networks. Of the possible interventions for altering networks, the use of drugs is presently the most feasible. In this mini-review, we present and discuss some exemplary approaches of how analysis of molecular interaction networks can contribute to pharmacology (e.g., by identifying new drug targets or prediction of drug side effects), as well as list pointers to relevant resources and software to guide future research. We also outline recent progress in the use of drugs for in vitro reprogramming of cells, which constitutes an example par excellence for altering molecular interaction networks with drugs. |
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Geographical breakdown
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United States | 4 | 44% |
United Kingdom | 1 | 11% |
India | 1 | 11% |
Unknown | 3 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 67% |
Scientists | 3 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 3% |
United Kingdom | 1 | 1% |
Mexico | 1 | 1% |
Poland | 1 | 1% |
Unknown | 66 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 22 | 31% |
Researcher | 11 | 15% |
Student > Master | 8 | 11% |
Student > Doctoral Student | 5 | 7% |
Professor > Associate Professor | 4 | 6% |
Other | 7 | 10% |
Unknown | 14 | 20% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 15 | 21% |
Biochemistry, Genetics and Molecular Biology | 13 | 18% |
Computer Science | 10 | 14% |
Chemistry | 5 | 7% |
Medicine and Dentistry | 4 | 6% |
Other | 8 | 11% |
Unknown | 16 | 23% |