Literature DB >> 22144153

Using phylogenetic profiles to predict functional relationships.

Matteo Pellegrini1.   

Abstract

Phylogenetic profiling involves the comparison of phylogenetic data across gene families. It is possible to construct phylogenetic trees, or related data structures, for specific gene families using a wide variety of tools and approaches. Phylogenetic profiling involves the comparison of this data to determine which families have correlated or coupled evolution. The underlying assumption is that in certain cases these couplings may allow us to infer that the two families are functionally related: that is their function in the cell is coupled. Although this technique can be applied to noncoding genes, it is more commonly used to assess the function of protein coding genes. Examples of proteins that are functionally related include subunits of protein complexes, or enzymes that perform consecutive steps along biochemical pathways. We hypothesize the deletion of one of the families from a genome would then indirectly affect the function of the other. Dozens of different implementations of the phylogenetic profiling technique have been developed over the past decade. These range from the first simple approaches that describe phylogenetic profiles as binary vectors to the most complex ones that attempt to model to the coevolution of protein families on a phylogenetic tree. We discuss a set of these implementations and present the software and databases that are available to perform phylogenetic profiling.

Mesh:

Substances:

Year:  2012        PMID: 22144153     DOI: 10.1007/978-1-61779-361-5_9

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  13 in total

Review 1.  Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments.

Authors:  Irina M Armean; Kathryn S Lilley; Matthew W B Trotter
Journal:  Mol Cell Proteomics       Date:  2012-10-15       Impact factor: 5.911

Review 2.  Inter-residue, inter-protein and inter-family coevolution: bridging the scales.

Authors:  Hendrik Szurmant; Martin Weigt
Journal:  Curr Opin Struct Biol       Date:  2017-11-05       Impact factor: 6.809

3.  CoPAP: Coevolution of presence-absence patterns.

Authors:  Ofir Cohen; Haim Ashkenazy; Eli Levy Karin; David Burstein; Tal Pupko
Journal:  Nucleic Acids Res       Date:  2013-06-08       Impact factor: 16.971

4.  Generation of divergent uroplakin tetraspanins and their partners during vertebrate evolution: identification of novel uroplakins.

Authors:  Rob Desalle; Javier U Chicote; Tung-Tien Sun; Antonio Garcia-España
Journal:  BMC Evol Biol       Date:  2014-01-23       Impact factor: 3.260

5.  A computational interactome and functional annotation for the human proteome.

Authors:  José Ignacio Garzón; Lei Deng; Diana Murray; Sagi Shapira; Donald Petrey; Barry Honig
Journal:  Elife       Date:  2016-10-22       Impact factor: 8.140

6.  Phylo_dCor: distance correlation as a novel metric for phylogenetic profiling.

Authors:  Gabriella Sferra; Federica Fratini; Marta Ponzi; Elisabetta Pizzi
Journal:  BMC Bioinformatics       Date:  2017-09-05       Impact factor: 3.169

7.  Predicting human protein function with multi-task deep neural networks.

Authors:  Rui Fa; Domenico Cozzetto; Cen Wan; David T Jones
Journal:  PLoS One       Date:  2018-06-11       Impact factor: 3.240

8.  Phylogenetic Clustering of Genes Reveals Shared Evolutionary Trajectories and Putative Gene Functions.

Authors:  Chaoyue Liu; Benjamin Wright; Emma Allen-Vercoe; Hong Gu; Robert Beiko
Journal:  Genome Biol Evol       Date:  2018-09-01       Impact factor: 3.416

9.  Developing of the Computer Method for Annotation of Bacterial Genes.

Authors:  Mikhail A Golyshev; Eugene V Korotkov
Journal:  Adv Bioinformatics       Date:  2015-12-06

10.  Human disease locus discovery and mapping to molecular pathways through phylogenetic profiling.

Authors:  Yuval Tabach; Tamar Golan; Abrahan Hernández-Hernández; Arielle R Messer; Tomoyuki Fukuda; Anna Kouznetsova; Jian-Guo Liu; Ingrid Lilienthal; Carmit Levy; Gary Ruvkun
Journal:  Mol Syst Biol       Date:  2013-10-01       Impact factor: 11.429

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