Max Karlsson

Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab)

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Genome-Wide Annotation of the Human Protein-Coding Genes Using Co-Expression Clustering

Number of pages: 30 Posted: 01 Dec 2023
María Bueno Álvez, Max Karlsson, Mengnan Shi, Richard Tjörnhammar, Loren Méar, Andreas Digre, Rutger Schutten, Evelina Sjöstedt, Fredrik Edfors, Per Oksvold, Kalle von Feilitzen, Martin Zwahlen, Mattias Forsberg, Fredric Johansson, Lynn Butler, Adil Mardinoglu, Fredrik Ponten, Cheng Zhang, Åsa Sivertsson, Mathias Uhlen, Linn Fagerberg and Cecilia Lindskog
Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Uppsala University, Uppsala University, Uppsala University, Harvard University, Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Uppsala University - Department of Immunology, Genetics and Pathology, Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab), Royal Institute of Technology (KTH) - Science for Life Laboratory (SciLife Lab) and Uppsala University
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Abstract:

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single cell, transcriptomics, genome-wide annotation, co-expression clustering, immunohistochemistry, data integration, spatial proteomics