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Guijun Zhao

dblp:16/6882 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 91% Computational science and engineering · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
biological database
0.112007
MeTaDoR: a comprehensive resource for membrane targeting domains and their host proteins · Bioinform. 2007
Bioinformatics and computational biology › biological database
protein domain database
0.112007
MeTaDoR: a comprehensive resource for membrane targeting domains and their host proteins · Bioinform. 2007
Computational science and engineering › computational chemistry › molecular simulation
molecular dynamics
0.012007
MeTaDoR: a comprehensive resource for membrane targeting domains and their host proteins · Bioinform. 2007

Methods — techniques the papers use, named apart from their topics

molecular dynamics · 0.1
YearPublicationVenuePosition
2007 MeTaDoR: a comprehensive resource for membrane targeting domains and their host proteins
abstract
MOTIVATION: Protein-lipid interactions play a central role in cellular signaling and membrane trafficking and at the core of these interactions are domains specialized in lipid binding and membrane targeting. Considering the importance of these domains, we have created MeTaDoR, a comprehensive resource dedicated to membrane targeting domains (MTDs). RESULT: MeTaDoR begins with a brief introduction about all the important MTDs including their subcellular localization and structural features. Sequences of all known MTDs are then provided in two formats: standard Prosite format and a parsed tab-delimited format that provides a manually curated classification into binding or non-binding. Structures of all MTDs and host proteins known so far are provided with links to PDB and Pfam databases. Membrane-binding orientation of these proteins, whether experimentally determined or proposed, is also provided with links to the appropriate literature. To facilitate molecular dynamics studies of these proteins, the force-field parameters for many non-standard lipids that commonly interact with these proteins are also provided. Finally, an online server for predicting membrane-binding proteins and a search function with various search fields are included. The resource is publicly available and will be updated on a regular basis.
Nitin Bhardwaj, Robert V. Stahelin, Guijun Zhao, Wonhwa Cho, Hui Lu 0004
Bioinform.3