How to organise a scientific competition to benchmark methods and algorithms in computational biology?

Scientific competitions have driven methodological innovation in artificial intelligence and machine learning, yet remain underutilized in computational biology. This paper provides a comprehensive guide for organizing scientific competitions in bioinformatics, based on our experience with HADACA3, a data challenge focused on deconvolution algorithms for predicting cellular composition in cancer, from multi-omics data. We detail the complete organizational workflow from preparation to execution to postanalysis, offering practical strategies and lessons learned. Beyond advancing multiomics deconvolution methods, HADACA3 demonstrated how expert-guided competitions foster methodological development, scientific exploration, and collaborative networking. By sharing our organizational framework, we aim to democratize scientific competitions as a fundamental methodology for developing and benchmarking computational methods in life sciences.