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X-WR-CALDESC:Events for SciLifeLab
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DTSTART;TZID=Europe/Stockholm:20210423T131000
DTEND;TZID=Europe/Stockholm:20210423T140000
DTSTAMP:20260407T132828
CREATED:20210414T084939Z
LAST-MODIFIED:20210414T084942Z
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SUMMARY:The open source ecosystem for genome-scale metabolic models
DESCRIPTION:Mihail Anton\, National Bioinformatics Infrastructure Sweden \n\n\n\nWhen: April 23\, 13:10  \n\n\n\nZoom link to the seminar: https://stockholmuniversity.zoom.us/j/68215564760 \n\n\n\nHost: Rui Benfeitas\, Stockholm University \n\n\n\nAbstract\n\n\n\nAs science is advancing towards full reproducibility\, the ecosystem of tools and resources for genome-scale metabolic modelling is increasingly open-source. The talk will showcase how Metabolic Atlas is contributing to this ecosystem by integrating several open-source GEMs\, and providing visualisations for these\, with the aim of aiding discovery of disease-related alterations of metabolism.
URL:https://www.scilifelab.se/event/the-open-source-ecosystem-for-genome-scale-metabolic-models/
CATEGORIES:Event
ORGANIZER;CN="Rui Benfeitas%2C SciLifeLab/Stockholm University":MAILTO:rui.benfeitas@scilifelab.se
LOCATION:https://stockholmuniversity.zoom.us/j/68215564760
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210423T110000
DTEND;TZID=Europe/Stockholm:20210423T120000
DTSTAMP:20260407T132828
CREATED:20210414T085113Z
LAST-MODIFIED:20210414T085116Z
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SUMMARY:Systems biology approaches for translational cancer research
DESCRIPTION:Francesco Gatto\, CSO Elypta\, Sweden \n\n\n\nWhen: April 23\, 11:00  \n\n\n\nZoom: https://stockholmuniversity.zoom.us/j/68215564760 \n\n\n\nHost: Rui Benfeitas\, Stockholm University \n\n\n\nAbstract\n\n\n\nIn this seminar\, I will illustrate how we investigated regulation of cancer metabolism using systems biology approaches and leading to the discovery of potential disease biomarkers. The talk will further focus on the challenge to translate fundamental discoveries in clinical practice and the foundation of Elypta – a start-up university spin-off that is executing this transition.
URL:https://www.scilifelab.se/event/systems-biology-approaches-for-translational-cancer-research/
CATEGORIES:Event
ORGANIZER;CN="Rui Benfeitas%2C SciLifeLab/Stockholm University":MAILTO:rui.benfeitas@scilifelab.se
LOCATION:https://stockholmuniversity.zoom.us/j/68215564760
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210422T150000
DTEND;TZID=Europe/Stockholm:20210422T160000
DTSTAMP:20260407T132828
CREATED:20210414T084404Z
LAST-MODIFIED:20210414T084407Z
UID:10000358-1619103600-1619107200@www.scilifelab.se
SUMMARY:The evolution of human Genome Scale Metabolic models
DESCRIPTION:Jonathan Robinson\, Scientific Data Developer Bioinnovation Institute\, Denmark \n\n\n\nWhen: April 22\, 15:00 \n\n\n\nZoom: https://stockholmuniversity.zoom.us/j/68215564760 \n\n\n\nHost: Rui Benfeitas\, Stockholm University \n\n\n\nAbstract\n\n\n\nMetabolism provides the energy and building blocks necessary to support life\, but the complexity of the metabolic network presents a challenge when trying to determine how changes to one component affects the system as a whole. Genome-scale metabolic models (GEMs) were developed to address this challenge by providing computational reconstructions of metabolic networks. GEMs have been developed for hundreds of species including humans\, supporting new approaches to study human health and disease.In my talk\, I will present our work in developing the most recent human GEM\, Human1\, and the different ways in which the model can be used to interpret omics data in a metabolic context. I will also share the challenges that we faced while developing Human1\, and the challenges that we still face over a year after its initial release in 2020. Finally\, I will discuss how we envision the future of GEMs\, and our efforts to make them more accessible and useful for bioinformaticians.
URL:https://www.scilifelab.se/event/the-evolution-of-human-genome-scale-metabolic-models/
CATEGORIES:Event
ORGANIZER;CN="Rui Benfeitas%2C SciLifeLab/Stockholm University":MAILTO:rui.benfeitas@scilifelab.se
LOCATION:https://stockholmuniversity.zoom.us/j/68215564760
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210421T131500
DTEND;TZID=Europe/Stockholm:20210421T140000
DTSTAMP:20260407T132828
CREATED:20210414T084108Z
LAST-MODIFIED:20210414T084111Z
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SUMMARY:Data-driven approaches towards studying context-specific cell signalling
DESCRIPTION:Evangelia Petsalaki\, Group Leader EMBL/EBI\, United Kingdom \n\n\n\nWhen: April 21\, 13:15 \n\n\n\nZoom: https://stockholmuniversity.zoom.us/j/68215564760 \n\n\n\nHost: Rui Benfeitas\, Stockholm University \n\n\n\nAbstract\n\n\n\nOur 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.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 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. For the second one I will present a method that combines paired transcriptomics and imaging data to extract context-specific signalling networks\, with the context in this case cell shape in breast cancer. The method is generalisable to any paired transcriptomics/phenotype data.
URL:https://www.scilifelab.se/event/data-driven-approaches-towards-studying-context-specific-cell-signalling/
CATEGORIES:Event
ORGANIZER;CN="Rui Benfeitas%2C SciLifeLab/Stockholm University":MAILTO:rui.benfeitas@scilifelab.se
LOCATION:https://stockholmuniversity.zoom.us/j/68215564760
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