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Michael Mahr

dblp:08/5105 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2015
—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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular informatics
cheminformatics
0.212015
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map · Bioinform. 2015
Bioinformatics and computational biology › protein structure analysis
structural similarity search
0.212015
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map · Bioinform. 2015
Bioinformatics and computational biology › drug discovery
compound prioritization
0.112015
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map · Bioinform. 2015
Bioinformatics and computational biology
drug discovery
0.112015
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map · Bioinform. 2015

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

pre-filtering · 0.2molecule kernels · 0.2
YearPublicationVenuePosition
2015 Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map
abstract
UNLABELLED: We have developed Rchempp, a web service that identifies structurally similar compounds (structural analogs) in large-scale molecule databases. The service allows compounds to be queried in the widely used ChEMBL, DrugBank and the Connectivity Map databases. Rchemcpp utilizes the best performing similarity functions, i.e. molecule kernels, as measures for structural similarity. Molecule kernels have proven superior performance over other similarity measures and are currently excelling at machine learning challenges. To considerably reduce computational time, and thereby make it feasible as a web service, a novel efficient prefiltering strategy has been developed, which maintains the sensitivity of the method. By exploiting information contained in public databases, the web service facilitates many applications crucial for the drug development process, such as prioritizing compounds after screening or reducing adverse side effects during late phases. Rchemcpp was used in the DeepTox pipeline that has won the Tox21 Data Challenge and is frequently used by researchers in pharmaceutical companies. AVAILABILITY AND IMPLEMENTATION: The web service and the R package are freely available via http://shiny.bioinf.jku.at/Analoging/ and via Bioconductor. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Günter Klambauer, Martin Wischenbart, Michael Mahr, Thomas Unterthiner, Sepp Hochreiter
Bioinform.3
2006 Accessible User Interface Framework for Severely Physically Disabled People
Michael Mahr, Alexander K. Nischelwitzer
ICCHP1
2006 MediaWheelie - A Best Practice Example for Research in Multimodal User Interfaces (MUIs)
Alexander K. Nischelwitzer, Bernd Sproger, Michael Mahr, Andreas Holzinger
ICCHP3