Μονάδα Υποστήριξης Φοιτητών (Μ.Υ.Φ.)

Πρόσκληση σε Διαδικτυακό Σεμινάριο "Resolving atherosclerosis mechanisms with multi-omics, network and machine learning methods" - IEEE EMB Greece Webinar Series

Πρόσκληση σε Διαδικτυακό Σεμινάριο του Ελληνικού Παραρτήματος του Engineering in Medicine and Biology του Institute of Electrical and Electronic Engineering (IEEE EMB Greece chapter)

Με ιδιαίτερη χαρά σας προσκαλούμε στο δεύτερο διαδικτυακό σεμινάριο (webinar) της σειράς διαδικτυακών σεμιναρίων που διοργανώνει το Ελληνικό Παράρτημα του Engineering in Medicine and Biology του Institute of Electrical and Electronic Engineering (IEEE EMB Greece chapter).

Το δεύτερο διαδικτυακό σεμινάριο με θέμα:

"Resolving atherosclerosis mechanisms with multi-omics, network and machine learning methods"

θα φιλοξενήσει τον Δρ. Κωνσταντίνο Θεοφιλάτο, Lecturer in Bioinformatics at King's College London και θα πραγματοποιηθεί την

Τετάρτη, 13 Νοεμβρίου 2024, ώρα 18.00 (GMT+2).

 

Την εκδήλωση θα χαιρετήσει η Αν. Καθηγήτρια Ιωάννα Χουβαρδά, πρόεδρος του Ελληνικού Παραρτήματος του IEEE ΕΜΒ (IEEE ΕΜΒ Greece section)

Η εκδήλωση είναι ανοιχτή προς όλους κατόπιν δωρεάν εγγραφής στον σύνδεσμο: https://authgr.zoom.us/meeting/register/tJMqdemurDsuH9ZMP2Aq9RVD9e0sF-i7nWru

 

Σας περιμένουμε με χαρά στην εκδήλωση!

 

Εκ μερους του ΙΕΕΕ EMB Greece Chapter Board

Σεφερίνα Μαυρουδή, Επικ. Καθηγήτρια, Τμήμα Νοσηλευτικής

 

Περίληψη Ομιλίας: Despite major advances in our understanding and treatment of cardiovascular disease (CVD), there are likely molecular targets beyond traditional lipid measurements that can better inform the diagnosis and prognosis of CVD, while atherosclerosis is one of the major contributing factors to elevated CVD risk. At the Cardiovascular Bioinformatics lab of King’s College London, we possess the technical expertise and infrastructure to perform multi-omics comparisons of proteins, lipid species and non-coding RNAs and we have leveraged the power of machine learning to compare biomarkers from different molecular entities and develop diagnostic and prognostic tests for Coronary Heart Disease1, Myocardial Infarction2, 3 and atherosclerosis4. In the context of the present webinar, we will introduce the principles of applying network and machine learning methods for diagnostic and prognostic model development in cardiovascular research showcasing examples of analyzing multiple omics modalities. Specific focus will be given to how multi-omics data has been used for identifying novel atherosclerosis phenotypes, prognostic scores and the related molecular mechanisms associated with them.

  1. Clarke R, et al. Apolipoprotein proteomics for residual lipid-related risk in coronary heart disease. Circulation Research. 2023 Feb 17;132(4):452-64.
  2. Schulte C, et al. Serial measurements of protein and microRNA biomarkers to specify myocardial infarction subtypes. Journal of molecular and cellular cardiology plus. 2022 Sep 1;1:100014.
  3. Schulte C, et al. Comparative analysis of circulating noncoding RNAs versus protein biomarkers in the detection of myocardial injury. Circulation research. 2019 Jul 19;125(3):328-40.
  4. Theofilatos K, Stojkovic S, Hasman M, van der Laan SW, Baig F, Barallobre-Barreiro J, Schmidt LE, Yin S, Yin X, Burnap S, Singh B. Proteomic atlas of atherosclerosis: the contribution of proteoglycans to sex differences, plaque phenotypes, and outcomes. Circulation research. 2023 Sep 15;133(7):542-58.

 

Σχετικά με τον Ομιλητή: Dr. Konstantinos Theofilatos is a Lecturer in Bioinformatics. The research of Dr Theofilatos focuses on machine learning, bioinformatics, proteomics and multi-omics data analysis with applications in cardiovascular research. In particular, he has more than 10 years of experience in bioinformatics, biological networks and machine learning data analysis (Düzgün MB, et al. OMCL. 2019; Theofilatos K, et al. BMCMG. 2019; Corthésy J, et al. JPR. 2018; Korfiati A, et al. EMBnet J, 2017; Theofilatos K, et al. AIM, 2015; Kleftogiannis D, et al. IEEE/ACM TCBB. 2015; Rapakoulia T, et al. Bioinformatics,  2014.) while for the last seven years, he has emphasized applying these techniques for the identification of therapeutic, prognostic and predictive biomarkers for cardiovascular diseases (Theofilatos et al, Circulation Research 2023, Moreira LM, et al. Nature, 2020; Schulte C, et al. Cir Res. 2019.). Dr. Theofilatos has co-authored more than 45 publications with 2209 citations so far. He has co-edited 2 books and he is the primary inventor of two bioinformatics processes related to patent applications to the US patent office. Since 2013, he has co-founded InSyBio, a multi-awarded biotechnology company and since 2017 he has been a lecturer of bioinformatics at British Heart Foundation Centre of Research Excellence at King’s College London, UK.

IEEE EMB Greece chapter

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Είδος εκδήλωσης