After a brief introduction to the use of machine learning in computational biology, we focus on the problem of biological networks inference. We define the problem as a problem of kernel learning using prediction in kernelized output spaces. Methods based on Output kernel Tree are presented to solve the problem. Results on two benchmarks are shown.