Before revision:  To address these limitations , we designed an algorithm called SpeakEasy , which detects overlapping or non-overlapping communities in biological networks. Input to SpeakEasy can be physical networks, such as molecular interactions, or inferred networks, such as gene coexpression networks. The networks can be directed or undirected, and may contain negative links. SpeakEasy combines traditional bottom-up and top-down approaches to clustering, by creating competition between clusters.
After revision:  To address these limitations and detect robust overlapping biological communities, we propose an unorthodox clustering method called SpeakEasy which identifies communities using top-down approaches to clustering, by creating competition between clusters.