@article{Waldispuhl_ODonnell_Will-Simul_Align_and-JCB2014,
author = {Waldispuhl, Jerome and O'Donnell, Charles W. and Will, 
          Sebastian and Devadas, Srinivas and Backofen, Rolf and 
          Berger, Bonnie},
title = {Simultaneous {Alignment} and {Folding} of {Protein} 
         {Sequences}},
journal = {JCB},
year = {2014},
doi = {10.1089/cmb.2013.0163},
volume = {21},
user = {backofen},
pmid = {24766258},
pages = {477-491},
number = {7},
issn = {1066-5277},
abstract = {Abstract Accurate comparative analysis tools for 
            low-homology proteins remains a difficult challenge in 
            computational biology, especially sequence alignment and 
            consensus folding problems. We present partiFold-Align, the 
            first algorithm for simultaneous alignment and consensus 
            folding of unaligned protein sequences; the algorithm's 
            complexity is polynomial in time and space. Algorithmically, 
            partiFold-Align exploits sparsity in the set of 
            super-secondary structure pairings and alignment candidates 
            to achieve an effectively cubic running time for 
            simultaneous pairwise alignment and folding. We demonstrate 
            the efficacy of these techniques on transmembrane 
            beta-barrel proteins, an important yet difficult class of 
            proteins with few known three-dimensional structures. 
            Testing against structurally derived sequence alignments, 
            partiFold-Align significantly outperforms state-of-the-art 
            pairwise and multiple sequence alignment tools in the most 
            difficult low-sequence homology case. It also improves 
            secondary structure prediction where current approaches 
            fail. Importantly, partiFold-Align requires no prior 
            training. These general techniques are widely applicable to 
            many more protein families (partiFold-Align is available at 
            http://partifold.csail.mit.edu/ ).}
}