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SEMINAR:Computational Approaches to Integrate.....02-11-2020

Speaker:  Tunca Doğan

Title: Computational Approaches to Integrate, Analyse and Make Sense out of Large-Scale and Complex Biological Data

Date/Time: 4 November 2020/ 1:40 - 2:30 pm

Zoom: Meeting ID: 948 0435 6644

Passcode: grad20su

Abstract:Data driven approaches became popular and employed to infer meaning from large-scale and noisy biological/biomedical data, following development of cheap technologies that led to a surge of data production and accumulation in public servers. A key concept in this endeavour is the prediction of unknown attributes and properties of biomolecules (e.g., molecular functions, interactions and etc.), and their relation to high level biomedical concepts such as systems and diseases. Lately, deep learning techniques applied on biological data to aid the development of novel and effective in silico solutions to the issues in biomedicine. In this seminar, I’ll talk about our efforts for integrating large-scale data from different biological data resources (i.e., the CROssBAR project) together with the development and application of deep learning based computational methods for enriching the integrated data by predicting: (i) functions (i.e., DEEPred tool), (ii) drug discovery centric ligand interactions (i.e., DEEPScreen and MDeePred tools), and (iii) disease related phenotypic implications (i.e., HPO2GO method) of genes and proteins. We hope that our tools and services, together with the ones currently in development process, will aid researchers from diverse fields of the life-sciences domain to build and pre-evaluate their hypothesis at the systems-level, before planning and executing costly experimental work.

Bio: Dr Tunca Dogan worked as a post-doctoral researcher at the University of Cambridge and the UniProt database (Protein Function Development) team at the European Bioinformatics Institute (EMBL-EBI) between the years 2013 and 2016. Upon his return to Turkey, Dr Dogan worked as a research group leader and adjunct faculty member at the Department of Health Informatics of the Informatics Institute in Middle East Technical University, between 2016 and 2019. During this period, he also served as a research associate at the European Bioinformatics Institute (EMBL-EBI). Currently, Dr Dogan is a faculty member at the Department of Computer and AI Engineering and the Institute of Informatics in Hacettepe University. His research focus can be summarized as developing computational methods for biomolecular sequence analysis, protein function prediction, computational drug discovery and biological data integration, using statistical approaches and machine/deep learning techniques.