Title |
An extended gene protein/products boolean network model including post-transcriptional regulation
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Published in |
Theoretical Biology and Medical Modelling, May 2014
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DOI | 10.1186/1742-4682-11-s1-s5 |
Pubmed ID | |
Authors |
Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, Alessandro Vasciaveo |
Abstract |
Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex regulatory mechanisms of a cell. Unfortunately, given their intrinsic complexity and non discrete nature, the computational study of realistic-sized complex GRNs requires some abstractions. Boolean Networks (BNs), for example, are a reliable model that can be used to represent networks where the possible state of a node is a boolean value (0 or 1). Despite this strong simplification, BNs have been used to study both structural and dynamic properties of real as well as randomly generated GRNs. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Italy | 1 | 5% |
Luxembourg | 1 | 5% |
Unknown | 19 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 7 | 33% |
Student > Bachelor | 3 | 14% |
Student > Ph. D. Student | 3 | 14% |
Other | 1 | 5% |
Student > Doctoral Student | 1 | 5% |
Other | 2 | 10% |
Unknown | 4 | 19% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 4 | 19% |
Computer Science | 4 | 19% |
Biochemistry, Genetics and Molecular Biology | 3 | 14% |
Medicine and Dentistry | 2 | 10% |
Chemistry | 2 | 10% |
Other | 1 | 5% |
Unknown | 5 | 24% |