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.