The use of quantitative approaches in cell biology, including modeling and theory, has been increasing steadily in the past decade. A number of seminal works that combine experiments and modeling have made a significant impact on the field (see Hill and Kirschner, 1982; Peskin et al., 1993; Barkai and Leibler, 1997, to name but a few). Mathematical modeling can help when our intuition fails or misleads us. It can provide a precise language for understanding complex cell biological phenomena. Modeling represents a new addition to our repertoire of strategies to understand biological systems
In this paper we take the view that computational models of biological systems should satisfy two co...
Modelling can provide intellectual frameworks that are necessary to translate data into knowledge. M...
This special issue of Mathematical Modelling of Natural Phenomena on biomathematics education shares...
Understanding modeling in biology requires understanding how biology is organized as a discipline an...
Mathematical biology has been an area of wide interest during the recent decades, as the modeling of...
Most of the published quantitative models in biology are lost for the community because they are eit...
In the context of the launching of this new journal, we propose a forum to the community of research...
International audienceMathematical modeling is a very powerful tool to understand natural phenomena....
Computational biology aims at disentangling the complexity of biological phenomena by providing tool...
Biological systems are staggeringly complex. To untangle this complexity and make predictions about ...
Science is an iterative process of experiments and hypotheses. Experiments produce surprising result...
Recently, there has been a surge in the number of pioneering studies combining experiments with quan...
© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attributi...
Most of the published quantitative models in biology are lost for the community because they are eit...
Computational models of cell signalling are perceived by many biologists to be prohibitively complic...
In this paper we take the view that computational models of biological systems should satisfy two co...
Modelling can provide intellectual frameworks that are necessary to translate data into knowledge. M...
This special issue of Mathematical Modelling of Natural Phenomena on biomathematics education shares...
Understanding modeling in biology requires understanding how biology is organized as a discipline an...
Mathematical biology has been an area of wide interest during the recent decades, as the modeling of...
Most of the published quantitative models in biology are lost for the community because they are eit...
In the context of the launching of this new journal, we propose a forum to the community of research...
International audienceMathematical modeling is a very powerful tool to understand natural phenomena....
Computational biology aims at disentangling the complexity of biological phenomena by providing tool...
Biological systems are staggeringly complex. To untangle this complexity and make predictions about ...
Science is an iterative process of experiments and hypotheses. Experiments produce surprising result...
Recently, there has been a surge in the number of pioneering studies combining experiments with quan...
© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attributi...
Most of the published quantitative models in biology are lost for the community because they are eit...
Computational models of cell signalling are perceived by many biologists to be prohibitively complic...
In this paper we take the view that computational models of biological systems should satisfy two co...
Modelling can provide intellectual frameworks that are necessary to translate data into knowledge. M...
This special issue of Mathematical Modelling of Natural Phenomena on biomathematics education shares...