Summary :Data Science Seminar: Dr. Isana Veksler-Lublinsky
Location :Building 96, Room 001
Start Date : 07/12/2021 13:00
End Date : {0:07/12/2021 14:00}
Description :

Speaker: Dr.Isana Veksler-Lublinsky

Title: Examiningthe evolution of microRNA-target interactions: Machine-learning to the rescue!


Abstract: Gene expression is the process bywhich the genetic information encoded in the DNA, is used to synthesizeproteins that perform most of the functions in the cells of all livingorganisms. This process is highly regulated, and errors can cause a broad rangeof diseases. MicroRNAs (miRNAs) are small RNAs that play a major role in regulatinggene expression via hybridization to complementary sequences on target mRNAs.MicroRNAs are found both in body fluids and tissues, and their composition andlevels vary between normal and different pathological conditions, includingcancer. Thus, microRNAs have emerged as a class of promising non-invasivebiomarkers for rapid detection of human disease and targets for therapeuticintervention.

IdentifyingmiRNA target sites on mRNAs is a fundamental step in understanding miRNAfunction. Due to the technical challenges involved in the application ofexperimental methods, datasets of direct bona-fide miRNA targets exist only fora few model organisms. Machine learning (ML) based target prediction methodswere successfully trained and tested on some of these datasets. Nevertheless,there is a need to apply target prediction tools to other organisms as well,where experimental data is not available.

Weexamined miRNA-target interaction rules and features and used data science andML approaches to investigate whether these rules are transferable betweenspecies. For our analysis, we used available datasets of direct miRNA-targetinteractions. Our results indicate that the transferability of miRNA-targetingrules between organisms depends on several factors, including evolutionarydistance, the composition of seed families, and the diversity of interactionswithin the datasets. Our study lays the foundation for the future developmentsof target prediction tools that could be applied to "non-model"organisms for which minimal experimental data is available.


Bio: Dr. Isana Veksler-Lublinsky is a Senior Lecturer in the Department ofSoftware and Information Systems Engineering, at Ben-Gurion University of theNegev (BGU), Israel, since 2017. She received her B.Sc., M.Sc. and Ph.D.degrees in Computer Science and Bioinformatics from BGU, and did herpost-doctoral research at the University of Massachusetts Medical School.

Her research group develops computationaltechniques and applies them to study complex biological phenomena. The groupperforms multidisciplinary research in close collaboration with experimentalbiologists and clinicians from Israel and worldwide and specializes in severalresearch domains. Current research focuses on basic questions in small RNAbiology (e.g., functions, evolution, biogenesis) and the applicability ofmiRNAs in the diagnosis of human disease. In addition, they investigate thediversity of bacterial genomes to identify genetic factors responsible fordifferent traits e.g., bacterial pathogenicity and antibiotic resistance.Group’s website:


Summary :Data Science Seminar
Location :Building 96, Room 001
Start Date : 14/12/2021 13:00
End Date : {0:14/12/2021 14:00}
Description :





Summary :Data Science Seminar
Location :Building 96, Room 001
Start Date : 21/12/2021 13:00
End Date : {0:21/12/2021 14:00}
Description :
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