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BACKGROUND Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. RESULTS We give a set of algorithms to compute the conditional probability of all labellings "near" a reference labelling lambda for a sequence y for a variety of definitions of "near". In addition, we give optimization(More)
Rollating walkers are popular mobility aids used by older adults to improve balance control. There is a need to automatically recognize the activities performed by walker users to better understand activity patterns, mobility issues and the context in which falls are more likely to happen. We design and compare several techniques to recognize walker related(More)
BACKGROUND Identifying recombinations in HIV is important for studying the epidemiology of the virus and aids in the design of potential vaccines and treatments. The previous widely-used tool for this task uses the Viterbi algorithm in a hidden Markov model to model recombinant sequences. RESULTS We apply a new decoding algorithm for this HMM that(More)
We consider the problem of phylogenetic placement, in which large numbers of sequences (often next-generation sequencing reads) are placed onto an existing phylogenetic tree. We adapt our recent work on phylogenetic tree inference, which uses ancestral sequence reconstruction and locality-sensitive hashing, to this domain. With these ideas, new sequences(More)
We prove that maximum likelihood phylogenetic inference is consistent on gapped multiple sequence alignments (MSAs) as long as substitution rates across each edge are greater than zero, under mild assumptions on the structure of the alignment. Under these assumptions, maximum likelihood will asymptotically recover the tree with edge lengths corresponding to(More)
We present the first sub-quadratic time algorithm that with high probability correctly reconstructs phylogenetic trees for short sequences generated by a Markov model of evolution. Due to rapid expansion in sequence databases, such very fast algorithms are becoming necessary. Other fast heuristics have been developed for building trees from very large(More)
Recently, we have identified a randomized quartet phylogeny algorithm that has O(n logn) runtime with high probability, which is asymptotically optimal. Our algorithm has high probability of returning the correct phylogeny when quartet errors are independent and occur with known probability, and when the algorithm uses a guide tree on O(loglogn) taxa that(More)
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