GraphML files for protein sequence networks of expansin homologues
C. Lohoff. Dataset, (2020)Related to: Lohoff C., Buchholz P. C. F., Le Roes-Hill M. & Pleiss J. (2020). The Expansin Engineering Database: a navigation and classification tool for expansins and homologues. Proteins: Structure, Function, and Bioinformatics 89:2. doi: 10.1002/prot.26001.
DOI: 10.18419/darus-624
Abstract
GraphML files for undirected weighted graphs with nodes that represent protein sequences of expansin homologues. Protein sequences were clustered by a threshold of sequence identity to derive representative sequences.Pairwise sequence identity between two sequences was derived from global Needleman-Wunsch alignment. Protein sequence networks were generated with edge weights of pairwise sequence identity, filtered by a predefined threshold. Metadata of the nodes (e.g. annotations) and of the edges (the edge weights) were summarized in GraphML files.
Related to: Lohoff C., Buchholz P. C. F., Le Roes-Hill M. & Pleiss J. (2020). The Expansin Engineering Database: a navigation and classification tool for expansins and homologues. Proteins: Structure, Function, and Bioinformatics 89:2. doi: 10.1002/prot.26001
%0 Generic
%1 lohoff2020graphml
%A Lohoff, Caroline
%D 2020
%K darus ubs_10003 ubs_20003 ubs_30187 unibibliografie
%R 10.18419/darus-624
%T GraphML files for protein sequence networks of expansin homologues
%X GraphML files for undirected weighted graphs with nodes that represent protein sequences of expansin homologues. Protein sequences were clustered by a threshold of sequence identity to derive representative sequences.Pairwise sequence identity between two sequences was derived from global Needleman-Wunsch alignment. Protein sequence networks were generated with edge weights of pairwise sequence identity, filtered by a predefined threshold. Metadata of the nodes (e.g. annotations) and of the edges (the edge weights) were summarized in GraphML files.
@misc{lohoff2020graphml,
abstract = {GraphML files for undirected weighted graphs with nodes that represent protein sequences of expansin homologues. Protein sequences were clustered by a threshold of sequence identity to derive representative sequences.Pairwise sequence identity between two sequences was derived from global Needleman-Wunsch alignment. Protein sequence networks were generated with edge weights of pairwise sequence identity, filtered by a predefined threshold. Metadata of the nodes (e.g. annotations) and of the edges (the edge weights) were summarized in GraphML files.},
added-at = {2022-03-08T18:37:34.000+0100},
affiliation = {Lohoff, Caroline/Universität Stuttgart},
author = {Lohoff, Caroline},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e4d7fe0f3b7025cea79dbdae4d14ba8d/unibiblio},
doi = {10.18419/darus-624},
howpublished = {Dataset},
interhash = {7bc6c66e5a7da5fb4260abc62cd037d5},
intrahash = {e4d7fe0f3b7025cea79dbdae4d14ba8d},
keywords = {darus ubs_10003 ubs_20003 ubs_30187 unibibliografie},
note = {Related to: Lohoff C., Buchholz P. C. F., Le Roes-Hill M. & Pleiss J. (2020). The Expansin Engineering Database: a navigation and classification tool for expansins and homologues. Proteins: Structure, Function, and Bioinformatics 89:2. doi: 10.1002/prot.26001},
timestamp = {2022-03-08T17:37:34.000+0100},
title = {GraphML files for protein sequence networks of expansin homologues},
year = 2020
}
