Title of the topic:
Application and development of bioinformatics and network theoretical methods in cardiovascular disease research and pharmacovigilance
Name of supervisor:
Dr. Bence Károly Ágg, associate professor
E-mail of supervisor:
agg.bence@semmelweis.hu
Department which announces the topic of research:
Department of Pharmacology and Pharmacotherapy
Students are expected from this/these faculty/faculties:
Faculty of Medicine, Faculty of Pharmaceutical Sciences
Students are expected from this/these year(s):
Year 2, Year 3, Year 4
Description of the topic of research, important knowledge regarding the topic:
„Our research group is exploring the application of bioinformatics, machine learning and network theoretical methods developed in recent years in the field of drug discovery. Rapidly expanding pharmaceutical databases made it possible to complement lengthy and costly experiments with in silico methods to aid drug development, interaction or side effect detection.
In parallel, datasets from high-throughput molecular biology studies are being analysed with the aim of uncovering mediators central to the pathomechanism of cardiovascular disease.
Our research group is advertising several TDK positions in different topics, which will be presented in detail if you are interested.
We usually offer the possibility to carry out research tasks at home via VPN connection, online or in person.”
Tasks and requirements for students:
„Tasks of the TDK student:
The main objective of our research is to improve the current standard methods already established, for which the following steps are essential:
– Scientific literature search, following breakthroughs in artificial intelligence and network theory, translating their applicability to drug discovery
– Exploring and understanding databases from pharmaceutical and clinical trials
– Bioinformatics analysis of data from high-throughput molecular biology studies (RNA-seq, miRNA-seq)
– Manual curation of interactome datasets.
– Development of software modules for processing and analysis of datasets (C++, R)
– Implementation (Python, Tensorflow), testing and optimisation of machine learning methods
Necessary knowledge:
– At least a basic knowledge of a programming language (C , C++, Java, or a scripting language such as PHP, Perl, Python, etc.)
– Prior experience of using the UNIX (especially GNU/Linux) command line is an advantage
– Knowledge of English”
Students can apply until:
2025-07-01
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Post expires at 12:00am on 2025 July 1st