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We present a local search based clustering algorithm free of such required input that can be used to improve the cluster quality of a set of given clusters taken from any existing algorithm or clusters produced via any arbitrary assignment. We implement this local search using a modern GPU based approach to allow for efficient runtime. The proposed algorithm shows promising results for improving the quality of clusters. With already high quality input clusters we can achieve cluster rating improvements upto to 33%. <\/jats:p>","DOI":"10.1142\/s0129626417500074","type":"journal-article","created":{"date-parts":[[2017,12,5]],"date-time":"2017-12-05T22:27:31Z","timestamp":1512512851000},"page":"1750007","source":"Crossref","is-referenced-by-count":0,"title":["A Parallel Local Search Algorithm for Clustering Large Biological Networks"],"prefix":"10.1142","volume":"27","author":[{"given":"Gaetano","family":"Coccimiglio","sequence":"first","affiliation":[{"name":"Algoma University Communications Research Laboratory, 1520 Queen St E, Sault Ste. 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