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@ARTICLE{Porras:137882,
author = {Porras, Pablo and Duesbury, Margaret and Fabregat, Antonio
and Ueffing, Marius and Orchard, Sandra and Gloeckner,
Christian Johannes and Hermjakob, Henning},
title = {{A} visual review of the interactome of {LRRK}2: {U}sing
deep-curated molecular interaction data to represent
biology.},
journal = {Practical proteomics},
volume = {15},
number = {8},
issn = {1615-9853},
address = {Weinheim},
publisher = {Wiley VCH69157},
reportid = {DZNE-2020-04204},
pages = {1390-1404},
year = {2015},
abstract = {Molecular interaction databases are essential resources
that enable access to a wealth of information on
associations between proteins and other biomolecules.
Network graphs generated from these data provide an
understanding of the relationships between different
proteins in the cell, and network analysis has become a
widespread tool supporting -omics analysis. Meaningfully
representing this information remains far from trivial and
different databases strive to provide users with detailed
records capturing the experimental details behind each piece
of interaction evidence. A targeted curation approach is
necessary to transfer published data generated by primarily
low-throughput techniques into interaction databases. In
this review we present an example highlighting the value of
both targeted curation and the subsequent effective
visualization of detailed features of manually curated
interaction information. We have curated interactions
involving LRRK2, a protein of largely unknown function
linked to familial forms of Parkinson's disease, and hosted
the data in the IntAct database. This LRRK2-specific dataset
was then used to produce different visualization examples
highlighting different aspects of the data: the level of
confidence in the interaction based on orthogonal evidence,
those interactions found under close-to-native conditions,
and the enzyme-substrate relationships in different in vitro
enzymatic assays. Finally, pathway annotation taken from the
Reactome database was overlaid on top of interaction
networks to bring biological functional context to
interaction maps.},
subtyp = {Review Article},
keywords = {Animals / Computer Graphics / Databases, Protein / Humans /
Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 /
Molecular Sequence Annotation / Parkinson Disease:
metabolism / Protein Interaction Maps /
Protein-Serine-Threonine Kinases: physiology / Proteomics:
methods / Software / LRRK2 protein, human (NLM Chemicals) /
Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 (NLM
Chemicals) / Protein-Serine-Threonine Kinases (NLM
Chemicals)},
cin = {AG Gloeckner},
ddc = {540},
cid = {I:(DE-2719)1210007},
pnm = {345 - Population Studies and Genetics (POF3-345)},
pid = {G:(DE-HGF)POF3-345},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:25648416},
pmc = {pmc:PMC4415485},
doi = {10.1002/pmic.201400390},
url = {https://pub.dzne.de/record/137882},
}