Inferring biological networks by sparse identification of nonlinear dynamics

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Niall M Mangan

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Hi Niall, thank you for the explanation, this is super great!

By the way, could you please share the source code (just like Brunton did), it will be really helpful for us viewers to understand the process. Thanks!

fxchristsandya

You show a model starting around 5:20. Could one possibly determine possibly dynamical structures for the unknown parts of the system? I would imagine with enough data and for "logical" systems that the dynamics of an unknown but logical system connected to a known system could possibly be determined up to "some constant". Given something like "least action" if we assume "nature does it best" then, in some sense, this limits the possible dynamics. There is also then some likely "continuity" between systems such as "x1" and "x2".

In terms of linear algebra this is essentially "upsampling"(in the sense of lifting). E.g., one is going to have a matrix system that is defined for fewer systems enlarged and the missing components have to be estimated from the structure determined by SINDY.

E.g., Suppose you had a system with a rather large number of subsystems such as the human body. One does not know all the systems but many are well understood more or less. Each system is a dynamical system. So the dynamics of the overall is the dynamics of the individuals(more or less).

kodfkdleepd

Nice how the screen is projected before you ..can you please say it

mohanachuthvarma

658 views and two of them are :).we smart and also are everywhere :D:D

akshaytiwari

Inferring biological networks by sparse identification of nonlinear dynamics

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