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# Concerning the NJ algorithm and its unweighted version, UNJ

@inproceedings{Gascuel1996ConcerningTN, title={Concerning the NJ algorithm and its unweighted version, UNJ}, author={Olivier Gascuel}, booktitle={Mathematical Hierarchies and Biology}, year={1996} }

- Published 1996 in Mathematical Hierarchies and Biology

In this paper we will present UNJ, an unweighted version of the NJ algorithm (Saitou and Nei 1987; Studier and Keppler 1988). We will demonstrate that UNJ is well suited when the data are of the ( ) ( ) δ ε ij ij ij d = + type, where ( ) dij is a tree distance, and when the εij are independent and identically distributed noise variables. Simulations confirm this theory. On a more general level, we will study the three main components of the agglomerative approach, applied to the reconstruction… CONTINUE READING