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Displaying 1-12 out of 12 total
A Transcript Perspective on Evolution
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Yann Christinat,Bernard M.E. Moret
Issue Date:November 2013
pp. 1403-1411
Alternative splicing is now recognized as a major mechanism for transcriptome and proteome diversity in higher eukaryotes, yet its evolution is poorly understood. Most studies focus on the evolution of exons and introns at the gene level, while only few co...
 
Inferring Transcript Phylogenies
Found in: Bioinformatics and Biomedicine, IEEE International Conference on
By Yann Christinat,Bernard M.E. Moret
Issue Date:November 2011
pp. 208-215
Alternative splicing, an unknown mechanism 20 years ago, is now recognized as a major mechanism for proteome and transcriptome diversity, particularly in mammals -- some researchers conjecture that up to 90% of human genes are alternatively spliced. Despit...
 
Uncovering Hidden Phylogenetic Consensus in Large Data Sets
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Nicholas D. Pattengale, Andre J. Aberer, Krister M. Swenson, Alexandros Stamatakis, Bernard M.E. Moret
Issue Date:July 2011
pp. 902-911
Many of the steps in phylogenetic reconstruction can be confounded by
 
Using Phylogenetic Relationships to Improve the Inference of Transcriptional Regulatory Networks
Found in: BioMedical Engineering and Informatics, International Conference on
By Xiuwei Zhang, Maryam Zaheri, Bernard M.E. Moret
Issue Date:May 2008
pp. 186-193
Inferring transcriptional regulatory networks from gene-expression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong network models. Time-series expression data have shown promise and recent work by ...
 
Identifying Orthologs: Cycle Splitting on the Breakpoint Graph
Found in: 2005 IEEE Computational Systems Bioinformatics Conference - Workshops
By Krister M. Swenson, Nicholas D. Pattengale, Bernard M.E. Moret
Issue Date:August 2005
pp. 65-68
<p>Gene rearrangements have successfully been used in phylogenetic reconstruction and comparative genomics (see the survey of [4] and the monograph of [6]), but usually under the assumption that all genomes have the same gene content and that no gene...
 
Phylogenetic Postprocessing
Found in: 2005 IEEE Computational Systems Bioinformatics Conference - Workshops
By Nicholas D. Pattengale, Bernard M.E. Moret
Issue Date:August 2005
pp. 57-58
<p>Phylogenetic reconstruction techniques often produce multiple, competing evolutionary hypotheses. The umbrella term phylogenetic postprocessing encompassesmethods that attempt to reconcile the ambiguity. Three classes of phylogenetic postprocessin...
 
Consensus Methods Using Phylogenetic Databases
Found in: 2005 IEEE Computational Systems Bioinformatics Conference - Workshops
By Mahesh M. Kulkarni, Bernard M.E. Moret
Issue Date:August 2005
pp. 61-62
<p>With the increasing use and size of phylogenies, the output of reconstruction programs must be stored for future reference, in which case post-tree analyses such as consensus must be run from a database. We set out to determine whether such analys...
 
Phylogenetic Networks: Modeling, Reconstructibility, and Accuracy
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Bernard M.E. Moret, Luay Nakhleh, Tandy Warnow, C. Randal Linder, Anna Tholse, Anneke Padolina, Jerry Sun, Ruth Timme
Issue Date:January 2004
pp. 13-23
Phylogenetic networks model the evolutionary history of sets of organisms when events such as hybrid speciation and horizontal gene transfer occur. In spite of their widely acknowledged importance in evolutionary biology, phylogenetic networks have so far ...
 
An Investigation of Phylogenetic Likelihood Methods
Found in: Bioinformatic and Bioengineering, IEEE International Symposium on
By Tiffani L. Williams, Bernard M.E. Moret
Issue Date:March 2003
pp. 79
We analyze the performance of likelihood-based approaches used to reconstruct phylogenetic trees. Unlike other techniques such as Neighbor-Joining (NJ) and Maximum Parsimony (MP), relatively little is known regarding the behavior of algorithms founded on t...
 
Toward New Software for Computational Phylogenetics
Found in: Computer
By Bernard M.E. Moret, Li-San Wang, Tandy Warnow
Issue Date:July 2002
pp. 55-64
<p>Systematists study how a group of genes or organisms evolved. These biologists now have set their sights on the Tree of Life challenge: to reconstruct the evolutionary history of all knownliving organisms.</p><p>A typical phylogenetic ...
 
Uncovering Hidden Phylogenetic Consensus in Large Data Sets
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Alexandros Stamatakis, Andre Aberer, Bernard Moret, Krister Swenson, Nicholas Pattengale
Issue Date:July 2011
pp. 902-911
Many of the steps in phylogenetic reconstruction can be confounded by "rogue” taxa—taxa that cannot be placed with assurance anywhere within the tree, indeed, whose location within the tree varies with almost any choice of algorithm or paramete...
     
The computational metaphor and quantum physics
Found in: Communications of the ACM
By Bernard M.E. Moret, Michael J. Manthey
Issue Date:February 1983
pp. 137-145
Concurrent computational systems, viewed as sets of cooperating processes, are shown to have close analogies in the world of quantum physics. In particular, analogies exist between processes and particles, between a process' state and a particle's mass, be...
     
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