This is a friendly reminder about today's virtual Sven Furberg Seminar in Bioinformatics and Statistical Genomics. 
Dr. Evangelia Petsalaki, Group Leader at EMBL-EBI, will present the lecture entitled "Integrative studies of context-specific signalling" (see Zoom info below and https://www.mn.uio.no/sbi/english/furberg-seminars/dr.-evangelia-petsalaki.html).

Abstract
Our group aims to understand and describe the organisation principles of cell signalling that allow the diverse and context-specific cell responses and phenotypes.
It is well established that signalling responses happen through complex networks. However, most signalling research still uses linear pathways as the ground truth. Moreover, signalling responses are highly dependent on context, such as tissue type, genetic background etc and therefore these static pathways are not always suitable. There is also a high bias in the literature towards kinases and pathways for which reagents and prior knowledge is readily available. This leaves a huge dark space in our understanding of cell signalling and significantly hinders studies of its general principles. Data-driven methods to study cell signalling using phosphoproteomics have typically been developed on transcriptomics data. Due to fundamental differences of these data types, including the sparsity of phosphoproteomics, these methods perform poorly on signalling network inference. Finally, large-scale essentiality datasets that can shed light on the context in which different signalling-related genes and pathways are crucial have thus far been severely underused in largescale omics data integrative efforts, likely due to their inaccessibility to non-expert users.
In this talk I will present two projects where we try to mitigate some of the above issues. For the first one I will present a method for data-driven machine-learning-based approach that takes advantage of global phosphoproteomics datasets to predict kinase regulatory networks, including their direction and sign of regulation. Our predicted kinase regulatory network is able to recapitulate known signalling pathways and agrees with orthogonal validation datasets. We were able to provide predictions for a large fraction of the understudied kinase space and found that kinase regulatory networks are denser than previously suspected.
For the second one I will present CEN-tools, an integrative webserver and python package, that allows users to navigate the contexts of different gene essentialities. I will demonstrate examples of its use in discovering new gene-gene relationships and important putative signalling targets for different cancers.

Looking forward to seeing you all this afternoon.
Best
Manuela & Anthony

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Anthony Mathelier is inviting you to a scheduled Zoom meeting.
 
Topic: Evangelia Petsalaki - Sven Furberg Seminar in Bioinformatics and Statistical Genomics
Time: May 28, 2020 02:30 PM Oslo
 
Join Zoom Meeting
https://uio.zoom.us/j/69498791162?pwd=aTZoRGFObmxpQmJQZ2k5ZmsrUEE5dz09
 
Meeting ID: 694 9879 1162
Password: furberg

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