Before revision:  Traditional clustering methods assign each component to one group. Noisy measurements are common in high-throughput biological datasets. These two limitations reduce our ability to accurately define clusters in biological datasets and to interpret their biological functions.
After revision:  However, traditional clustering methods detect non-overlapping communities. These detected communities may also be unstable and difficult to replicate, because traditional methods are sensitive to noise and parameter settings. These aspects of traditional clustering methods limit our ability to accurately define clusters in biological datasets and to interpret their biological functions.