Subramaniam: Không nhất thiết. Bạn có thể có các thuộc tính xuất hiện như một hệ quả của hội nhập. Noble: Và thậm chí bạn có thể bối rối là tại sao. Đây không phải là một lời giải thích. Boissel: Thời hạn tiếp theo là "mạnh mẽ". Hôm qua, một lần nữa, tôi nghe thấy hai di ¡erent nitions ¢ de. Đầu tiên, sự thiếu hiểu biết giá trị tham số thứ hai, vô cảm đến không chắc chắn. | GENERAL DISCUSSION II 127 Subramaniam Not necessarily. You can have emergent properties as a consequence of integration. Noble And you may even be puzzled as to why. This is not yet an explanation. Boissel The next term is robustness . Yesterday again I heard two different definitions. First insensitivity to parameter values second insensitivity to uncertainty. I like the second but not the first. Noble In some cases you would want sensitivity. No Hodgkin-Huxley analysis of a nerve impulse would be correct without it being the case that at a certain critical point the whole thing takes off. We will need to have sensitivity to some parameter values. Boissel For me insensitivity to parameter values means that the parameters are useless in the model. Cassman In those cases at least the fairly limited number where this seems to be true it is the architecture of the system that determines the output and not the specific parameter values. It seems likely this is only true for certain characteristic phenotypic outcomes. In some cases it exists in others it doesn t. Hinch Perhaps a better way of saying this is insensitivity to ill-defined parameter values. In some models there are parameters that are not well defined which is the case in a lot of signalling networks. In contrast in a lot of electrophysiology they are well defined and then the model doesn t have to be robust to a well defined parameter. Loew Rather than uncertainty a better concept for our discussion might be variability. That is because of differences in the environment and natural variability. We are often dealing with a small number of molecules. There is therefore a certain amount of uncertainty or variability that is built into biology. If a biological system is going to work reliably it has to be insensitive to this variability. Boissel That is different from uncertainty so we should add variability here. Paterson It is the difference between robustness of a prediction versus robustness of a system .
