KNetFold is a machine learning method, which takes a sequence alignment as an input and outputs a consensus structure allowing pseudoknots (Bindewald and Shapiro, 2006) . Simulfold takes an alignment as an input and simultaneously calculates a structure including pseudoknots, a multiple-sequence alignment and an evolutionary tree by sampling from the joint posterior distributions (Meyer and Miklos, 2007) . Tfold combines stem stability, covariation and conservation to search for compatible stems and subsequently for pseudoknots for a set of aligned homologous sequences (Engelen and Tahi, 2010) . Several comparative structure prediction methods including pseudoknots do not rely on an initial sequence alignment. The graph-theoretical approach comRNA computes stem similarity scores and uses a maximum clique finding algorithm to find pseudoknotted structures (Ji et al., 2004) . SCARNA performs pairwise structural alignment of stem fragments with fixed lengths derived from the probability dot plot (Tabei et al., 2008) .