Author

Olof Emanuelsson

KTH Royal Institute of TechnologyORCID 0000-0002-8879-9245Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:software / tool· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:multiple species· 1

Frequent Co-Authors

Arne ElofssoniD· 1 shared Gunnar von HEIJNEiD· 1 shared Henrik NielseniD· 1 shared José Juan Almagro ArmenterosiD· 1 shared Karl Johan WestriniD· 1 shared Marco SalvatoreiD· 1 shared Ole WintheriD· 1 shared Warren W. KretzschmariD· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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1 shared paperBioinformatics

Arne ElofssonORCID

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2 papers

Recent·Most cited

ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs

Karl Johan Westrin, Warren W. Kretzschmar, Olof Emanuelsson

ClusTrast improves de novo transcript isoform reconstruction by clustering contigs and merging assemblies, outperforming existing tools in recall and polymorphism detection.

bioRxiv · Jan 2, 2022 · PreprintBioinformatics

Detecting Novel Sequence Signals in Targeting Peptides Using Deep Learning

José Juan Almagro Armenteros, Marco Salvatore, Olof Emanuelsson, Ole Winther, Gunnar von HEIJNE, Arne Elofsson, Henrik Nielsen

The paper introduces TargetP 2.0, a deep learning method to identify N-terminal sorting signals in proteins, revealing insights into the importance of the second residue in targeting peptides.

Life Science Alliance · Sep 30, 2019Peer-reviewedBioinformatics