Abstract
During disease progression or organism development, alternative splicing (AS) may lead to isoform switches (IS) that demonstrate similar temporal patterns and reflect the AS co-regulation of such genes. Tools for dynamic process analysis usually neglect AS. Here we propose Spycone (https://github.com/yollct/spycone), a splicing-aware framework for time course data analysis. Spycone exploits a novel IS detection algorithm and offers downstream analysis such as network and gene set enrichment. We demonstrate the performance of Spycone using simulated and real-world data of SARS-CoV-2 infection.

Group Leader
I’m a group leader of Computational Genomics and Transcriptomics group. I focus on the BMBF funded Sys_CARE project about alternative splicing in cardiac and renal diseases. I graduated from Lomonosov Moscow State University and did PhD in Kharkevich Institute in Moscow at professor Gelfand lab. There I studied the evolution of transcriptional regulatory networks in bacteria. During my PhD I shortly stayed at Stowers Institute for Medical Research, Kansas-City, where I went on working on regulation of bacterial metabolic pathways. As a research scientist, I worked in Skolkovo Institute of Science and Technology, Moscow on 3D chromatin structure analysis.