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Computational Modeling of Signaling Networks

Overview of attention for book
Cover of 'Computational Modeling of Signaling Networks'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Predictive Models for Cellular Signaling Networks
  3. Altmetric Badge
    Chapter 2 Analyzing and Constraining Signaling Networks: Parameter Estimation for the User
  4. Altmetric Badge
    Chapter 3 A Tutorial on Mathematical Modeling of Biological Signaling Pathways
  5. Altmetric Badge
    Chapter 4 Bistability in One Equation or Fewer
  6. Altmetric Badge
    Chapter 5 Mathematical Investigation of How Oncogenic Ras Mutants Promote Ras Signaling
  7. Altmetric Badge
    Chapter 6 Modeling miRNA Regulation in Cancer Signaling Systems: miR-34a Regulation of the p53/Sirt1 Signaling Module
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    Chapter 7 Design of Experiments to Investigate Dynamic Cell Signaling Models
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    Chapter 8 Mathematical Modeling of Biochemical Systems with PottersWheel
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    Chapter 9 Rule-Based Modeling of Signal Transduction: A Primer
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    Chapter 10 Computational Modeling of Signal Transduction Networks: A Pedagogical Exposition
  12. Altmetric Badge
    Chapter 11 Modeling spatiotemporal dynamics of bacterial populations.
  13. Altmetric Badge
    Chapter 12 Discrete Dynamic Modeling of Signal Transduction Networks
  14. Altmetric Badge
    Chapter 13 Analytic Methods for Modeling Stochastic Regulatory Networks
Attention for Chapter 8: Mathematical Modeling of Biochemical Systems with PottersWheel
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Chapter title
Mathematical Modeling of Biochemical Systems with PottersWheel
Chapter number 8
Book title
Computational Modeling of Signaling Networks
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-833-7_8
Pubmed ID
23361985
Book ISBNs
978-1-61779-832-0, 978-1-61779-833-7
Authors

Thomas Maiwald, Oliver Eberhardt, Julie Blumberg

Abstract

The program PottersWheel has been developed to provide an intuitive and yet powerful framework for data-based modeling of dynamical systems like biochemical reaction networks. Its key functionality is multi-experiment fitting, where several experimental data sets from different laboratory conditions are fitted simultaneously in order to improve the estimation of unknown model parameters, to check the validity of a given model, and to discriminate competing model hypotheses. New experiments can be designed interactively. Models are either created text-based or using a visual model designer. Dynamically generated and compiled C files provide fast simulation and fitting procedures. Each function can either be accessed using a graphical user interface or via command line, allowing for batch processing within custom Matlab scripts. PottersWheel is designed as a Matlab toolbox, comprises 250,000 lines of Matlab and C code, and is freely available for academic usage at www.potterswheel.de .

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 18%
Lecturer > Senior Lecturer 1 9%
Lecturer 1 9%
Student > Doctoral Student 1 9%
Student > Bachelor 1 9%
Other 5 45%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 27%
Biochemistry, Genetics and Molecular Biology 2 18%
Medicine and Dentistry 2 18%
Engineering 2 18%
Neuroscience 1 9%
Other 0 0%
Unknown 1 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 February 2013.
All research outputs
#18,331,227
of 22,699,621 outputs
Outputs from Methods in molecular biology
#7,835
of 13,073 outputs
Outputs of similar age
#196,010
of 244,144 outputs
Outputs of similar age from Methods in molecular biology
#326
of 474 outputs
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So far Altmetric has tracked 13,073 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 474 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.

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