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Lars Juhl Jensen

Researcher at Swiss Institute of Bioinformatics

Publications -  5
Citations -  2508

Lars Juhl Jensen is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: Interaction network & BindingDB. The author has an hindex of 5, co-authored 5 publications receiving 1924 citations. Previous affiliations of Lars Juhl Jensen include University of Copenhagen & University of Zurich.

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STITCH 5: augmenting protein–chemical interaction networks with tissue and affinity data

TL;DR: In the new, fifth release of STITCH, functionality to filter out the proteins and chemicals not associated with a given tissue is implemented and a new network view is implemented that gives the user the ability to view binding affinities of chemicals in the interaction network.
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STITCH: interaction networks of chemicals and proteins

TL;DR: STITCH (‘search tool for interactions of chemicals’) integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug–target relationships, andferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals.
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STITCH 4: integration of protein–chemical interactions with user data

TL;DR: This version of STITCH added features for users to upload their own data to STITCH in the form of internal identifiers, chemical structures or quantitative data, and changed the scheme for transferring interactions between species to rely on orthology rather than protein similarity.
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STITCH 3: zooming in on protein–chemical interactions

TL;DR: STITCH, an aggregated database of interactions connecting over 300 000 chemicals and 2.6 million proteins from 1133 organisms, and offers the option to switch between two levels of detail, namely whether stereoisomers of a given compound are shown as a merged entity or as separate entities.
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STITCH 2: an interaction network database for small molecules and proteins

TL;DR: In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database, and InChIKeys that allow identification of chemicals with a short, checksum-like string are adopted.