We start with presenting inverse problems from iron and steel making, from
systems biology and from finance and show, by numerical evidence, their
instability. then we present basic mathematical facts about inverse and
ill-posed problems, focussing on regularization methods for their stable
solution. emphasis is on nonlinear problems and new types of regularization
methods enforcing sparse solutions. we show the effectiveness of this approach
for a qualitative inverse problems from systems biology.