Systematic analysis of alternative splicing in time course data using spycone

HIGHLIGHTS

• who: Bioinformatics and colleagues from the Institute for Computational Systems Biology, University of Hamburg, Notkestrasse, Hamburg, Germany, Chair of Experimental have published the Article: Systematic analysis of alternative splicing in time course data using Spycone, in the Journal: (JOURNAL)
• what: The authors propose Spycone a splicing-aware framework for time course data analysis. The authors demonstrate the performance of Spycone using simulated and real-world data of SARS-CoV-2 infection. On the latter, the authors demonstrate how Spycone identifies network modules that are potentially affected by alternatively spliced genes during SARS-CoV-2 infection . . .
  

   

  

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