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David R. Damerell

dblp:247/2180 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author

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
3 papers
Bioinformatics and computational biology · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural bioinformatics
molecular structure visualization
0.412020
MichelaNglo: sculpting protein views on web pages without coding · Bioinform. 2020
Bioinformatics and computational biology › protein analysis
protein bioinformatics
0.412019
UbiHub: a data hub for the explorers of ubiquitination pathways · Bioinform. 2019
Bioinformatics and computational biology › bioinformatics infrastructure
web-based bioinformatics tools
0.412019
SATurn: a modular bioinformatics framework for the design of robust maintainable web-based and standalone applications · Bioinform. 2019
Bioinformatics and computational biology › structural bioinformatics
protein structure
0.112020
MichelaNglo: sculpting protein views on web pages without coding · Bioinform. 2020
Bioinformatics and computational biology
drug discovery
0.112019
UbiHub: a data hub for the explorers of ubiquitination pathways · Bioinform. 2019
Bioinformatics and computational biology › drug discovery
target prioritization
0.112019
UbiHub: a data hub for the explorers of ubiquitination pathways · Bioinform. 2019

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

web-based visualization · 0.4phylogenetic tree visualization · 0.4modular software design · 0.4data integration · 0.4
YearPublicationVenuePosition
2020 MichelaNglo: sculpting protein views on web pages without coding
abstract
MOTIVATION: The sharing of macromolecular structural information online by scientists is predominantly performed via 2D static images, since the embedding of interactive 3D structures in webpages is non-trivial. Whilst the technologies to do so exist, they are often only implementable with significant web coding experience. RESULTS: Michelaɴɢʟo is an accessible and open-source web-based application that supports the generation, customization and sharing of interactive 3D macromolecular visualizations for digital media without requiring programming skills. A PyMOL file, PDB file, PDB identifier code or protein/gene name can be provided to form the basis of visualizations using the NGL JavaScript library. Hyperlinks that control the view can be added to text within the page. Protein-coding variants can be highlighted to support interpretation of their potential functional consequences. The resulting visualizations and text can be customized and shared, as well as embedded within existing websites by following instructions and using a self-contained download. Michelaɴɢʟo allows researchers to move away from static images and instead engage, describe and explain their protein to a wider audience in a more interactive fashion. AVAILABILITY AND IMPLEMENTATION: Michelaɴɢʟo is hosted at michelanglo.sgc.ox.ac.uk. The Python code is freely available at https://github.com/thesgc/MichelaNGLo, along with documentations about its implementation.
Matteo P. Ferla, Alistair T. Pagnamenta, David R. Damerell, Jenny C. Taylor, Brian D. Marsden
Bioinform.3
2019 SATurn: a modular bioinformatics framework for the design of robust maintainable web-based and standalone applications
David R. Damerell, Claire Strain-Damerell, Sefa Garsot, Stephen P. Joyce, Paul Barrett, Brian D. Marsden
Bioinform.1
2019 UbiHub: a data hub for the explorers of ubiquitination pathways
abstract
MOTIVATION: Protein ubiquitination plays a central role in important cellular machineries such as protein degradation or chromatin-mediated signaling. With the recent discovery of the first potent ubiquitin-specific protease inhibitors, and the maturation of proteolysis targeting chimeras as promising chemical tools to exploit the ubiquitin-proteasome system, protein target classes associated with ubiquitination pathways are becoming the focus of intense drug-discovery efforts. RESULTS: We have developed UbiHub, an online resource that can be used to visualize a diverse array of biological, structural and chemical data on phylogenetic trees of human protein families involved in ubiquitination signaling, including E3 ligases and deubiquitinases. This interface can inform target prioritization and drug design, and serves as a navigation tool for medicinal chemists, structural and cell biologists exploring ubiquitination pathways. AVAILABILITY AND IMPLEMENTATION: https://ubihub.thesgc.org.
David R. Damerell, Leonidas Koukouflis, Yufeng Tong 0001, Brian D. Marsden, Matthieu Schapira
Bioinform.2