Computational Analysis and Integration of Large-Scale Biological Data with Deep Learning Approaches

  • Title: Computational Analysis and Integration of Large-Scale Biological Data with Deep Learning Approaches
  • Presenter: Dr. Tunca Doğan from EMBI – EBI & METU
  • Date: August 2, 2018
  • Language: English
  • Abstract: Machine learning and data mining techniques are frequently employed to make sense of large-scale and noisy biological/biomedical data accumulated in public servers. A key subject in this endeavour is the prediction of the properties of proteins such as their functions and interactions. Recently, deep learning (DL) based methods have outperformed the conventional machine learning algorithms in the fields of computer vision, natural language processing and artificial intelligence; which brought attention to their application to the biological data. In this talk, I’m going to explain the DL-based probabilistic computational methods we have recently developed in our research center (KanSiL, Graduate School of Informatics, ODTU); first, to predict the functions of the uncharacterised proteins (i.e., DEEPred); and second, to identify novel interacting drug candidate molecules for all potential targets in the human proteome (i.e., DEEPscreen) to serve the purposes of drug discovery and repositioning, together with the aim of biomedical data integration. Apart from the benefits of employing novel DL approaches, I’ll also mention the limitations of DL-based techniques when applied on the biological data, to explain why deep learning alone cannot solve every problem related to bioinformatics.
  • Bigmarker: https://www.bigmarker.com/bioinfonet/TuncaDogan
  • Youtube: https://www.youtube.com/watch?v=ijr0B5oTnuY

Short Tandem Repeats in Tumours and Immunotherapy

Our July webinar was given by Tugce Bilgin Sonay, from the Department of Computational Biology in the University of Lausanne. In this session, apart from her work, Tugce also explained other studies in this area.

At the beginning of the talk, she gave a general introduction on the detection of short tandem repeats and their impact on phenotype, gene expression and epigenetics. The primary focus of the talk was (1) Microsatellite Instability (MSI) in tumours, which mostly occurs due to the increase in the number of short tandem repeats as a result of a faulty DNA damage repair system, (2) Identification of the effect of the short tandem repeats in these tumours and (3) how these effects can be utilized for immunotherapy.

If you are interested in how short tandem repeats influence cancer and how they can be used for immunotherapy purposes, we strongly suggest you watch this webinar: https://youtu.be/GmjwyTZinjU (unfortunately, this webinar is only available in Turkish)

As ISCB RSG Turkey, we want to thank Tugce again for accepting our invitation and giving this very informative talk!

RSG-Turkey is a member of The International Society for Computational Biology (ISCB) Student Council (SC) Regional Student Groups (RSG). We are a non-profit community composed of early career researchers interested in computational biology and bioinformatics.

Contact: turkey.rsg@gmail.com

Follow us on social media!