TY - GEN
T1 - Discovering local patterns of co-evolution
AU - Felder, Yifat
AU - Tuller, Tamir
PY - 2008
Y1 - 2008
N2 - Co-evolution is the process in which a set of orthologs exhibits a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions, about their complementary and backup relations, and more generally, for answering fundamental questions about the evolution of biological systems. Orthologs that exhibit strong signal of co-evolution in part of the evolutionary tree may show mild signal of co-evolution in other parts of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive evolution. Previous works in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local. In this work, we describe a new set of biological problems that are related to finding patterns of local co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above. We use our approach to trace the co-evolution of fungal and Eukaryotic genes at a high resolution across the different parts of the corresponding phylogenetic trees. Our analysis shows that local co-evolution is a wide-scale phenomenon.
AB - Co-evolution is the process in which a set of orthologs exhibits a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions, about their complementary and backup relations, and more generally, for answering fundamental questions about the evolution of biological systems. Orthologs that exhibit strong signal of co-evolution in part of the evolutionary tree may show mild signal of co-evolution in other parts of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive evolution. Previous works in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local. In this work, we describe a new set of biological problems that are related to finding patterns of local co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above. We use our approach to trace the co-evolution of fungal and Eukaryotic genes at a high resolution across the different parts of the corresponding phylogenetic trees. Our analysis shows that local co-evolution is a wide-scale phenomenon.
KW - Bi-clustering
KW - Co-evolution
KW - Evolution rates
KW - Functional ontology
KW - Gene copy number
KW - Gene deletion and duplication
KW - Systems biology
UR - http://www.scopus.com/inward/record.url?scp=70449589309&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-87989-3_5
DO - 10.1007/978-3-540-87989-3_5
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AN - SCOPUS:70449589309
SN - 3540879889
SN - 9783540879886
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 55
EP - 71
BT - Comparative Genomics, International Workshop, RECOMB-CG 2008, Proceedings
T2 - RECOMB Workshop on Comparative Genomics, RECOMB-CG 2008
Y2 - 13 October 2008 through 15 October 2008
ER -