Title Promoter Affiliations Abstract "Nieuwe applicaties in informatiebevraging, beeldverwerking en bio-informatica hebben geleid tot de ontwikkeling van nieuwe machine learning methoden om meerdere targets tegelijkertijd te voorspellen. Recent werden tal van nieuwe methoden ontwikkeld in ver" "Willem Waegeman" "Department of Data analysis and mathematical modelling, Department of Mathematical Modelling, Statistics and Bio-informatics" "Modern applications in areas such as information retrieval, image analysis and computational biology have triggered a need for specialized machine learning methods that deliver joint predictions for multiple targets. Recently, new algorithms for multi-target prediction problems have been proposed in different subfields of machine learning, and most of the recent methods intend to exploit, in one way or another, dependencies between targets. The goal of this project is to elaborate on the idea of exploiting target dependence, thereby contributing to a better understanding of existing multi-target prediction methods." "Identification of host or viral parameters that predict off-treatment outcomes in patients chronically infected with the hepatitis B virus by a combination of statistical modelling and bio-informatics approaches." "Thomas Vanwolleghem" "Social Epidemiology & Health Policy (SEHPO), Centre for Health Economics Research and Modelling of Infectious Diseases (CHERMID), Laboratory Experimental Medicine and Pediatrics (LEMP)" "Chronic Hepatitis B Virus infections affect 3.6% of the worldwide population and result in liver-related death in over 700000 people annually. Current standard of care, consisting of nucleos(t)ide analogues (NA), efficiently suppress viral replication, prevent liver disease, but do not cure the infection, defined as Hepatitis B surface antigen (HBsAg) loss. Lifelong NA treatment is therefore often required. However, in some patients with long term viral suppression, treatment withdrawal may lead to persistent off-treatment viral control and an upto 40% chance of HBsAg loss after 5 years. Obviously, identifying upfront which patients will benefit from a treatment cessation is of utmost importance. We are currently coordinating the COIN-B study, a multicentric national study in which 90 patients stop their antiviral treatment, and 50 continue. The design of this study allows for the evaluation of baseline host factors, such as ethnicity, on off-treatment outcomes, but not the effects of viral flares or retreatment. To this end, we will combine the data of the COIN-B study with several international prospective NA withdrawal studies with intensive monitoring schedules and retreatment criteria. We will apply and refine advanced statistical modelling to evaluate rare events, such as off-treatment HBsAg loss. This will enable a full picture of the different viral and host factors associated with viral control or functional cure (HBsAg loss) after NA withdrawal. This will further establish the optimal monitoring interval, retreatment indications and role of flares. Apart from statistical modelling, we will apply bio-informatics approaches to investigate gene signatures in blood of COIN-B patients. The goal of this substudy is to find a genetic biomarker able to select patients upfront for a NA treatment cessation. In addition, this will learn how the blood transcriptome is modulated during off-treatment responses and yield insight in the pathogenesis of flares and viral control. The combination of both approaches will ultimately lead to the optimal predictive model of clinical parameters and gene signatures that will guide future treatment decisions in the vast number of NA-treated patients." "Design and synthesis of TSLP complex antagonists based on chemo- and bio-informatics." "Hans De Winter" "Medicinal Chemistry (UAMC)" "Atopic diseases represent an important unmet need in modern day medicine. The pro-inflammatory cytokine TSLP is a key player in these pathologies. The aim of this project is the development of small molecules capable of disrupting TSLP signalling, using a chemo-and bio-informatics approach. These small molecules could help elucidate the role of TSLP in various pathologies and could be a starting point for further development of drugs targeting this pathway." "Bioinformatics: from nucleotids to networks (N2N)" "Kathleen Marchal" "Department of Plant Biotechnology and Bioinformatics" "The platform From Nucleotides to Networks (N2N) aims at setting up pipelines for the processing of the increasing flow of molecular data and the development of techniques for the integration of this data into further bio-informatics research." "Bioinformatics: from nucleotids to networks (N2N)" "Dieter Deforce" "Department of Pharmaceutics" "The platform From Nucleotides to Networks (N2N) aims at setting up pipelines for the processing of the increasing flow of molecular data and the development of techniques for the integration of this data into further bio-informatics research." "Bioinformatics: from nucleotids to networks (N2N)" "Gert De Cooman" "Department of Electronics and information systems, Department of Electromechanical, Systems and Metal Engineering" "The platform From Nucleotides to Networks (N2N) aims at setting up pipelines for the processing of the increasing flow of molecular data and the development of techniques for the integration of this data into further bio-informatics research." "Bioinformatics: from nucleotids to networks (N2N)" "Martine De Cock" "Department of Applied Mathematics, Computer Science and Statistics" "The platform From Nucleotides to Networks (N2N) aims at setting up pipelines for the processing of the increasing flow of molecular data and the development of techniques for the integration of this data into further bio-informatics research." "Bioinformatics: from nucleotids to networks (N2N)" "Peter Dawyndt" "Department of Applied Mathematics, Computer Science and Statistics" "The platform From Nucleotides to Networks (N2N) aims at setting up pipelines for the processing of the increasing flow of molecular data and the development of techniques for the integration of this data into further bio-informatics research." "Bioinformatics: from nucleotids to networks (N2N)" "Alexander Panfilov" "Department of Physics and astronomy" "The platform From Nucleotides to Networks (N2N) aims at setting up pipelines for the processing of the increasing flow of molecular data and the development of techniques for the integration of this data into further bio-informatics research." "Bioinformatics and machine learning for large-scale metabolomics data analysis." "Wout Bittremieux" "ADReM Data Lab (ADReM)" "Despite recent breakthroughs in artificial intelligence (AI) that have led to disruptive advances across many scientific domains, there are still challenges in adopting state-of-the-art AI techniques in the life sciences. Notably, analysis of small molecule untargeted mass spectrometry (MS) data is still based on expert knowledge and manually compiled rules, and each experiment is analyzed in isolation without taking into account prior knowledge. Instead, this project will develop more powerful approaches in which untargeted MS data is interpreted within the context of the vast background of previously generated, publicly available data. The research hypothesis driving the proposed project is that advanced AI techniques can uncover hidden knowledge from large amounts of open MS data in public repositories to gain a deeper understanding into the molecular composition of complex biological samples. We will develop machine learning solutions to explore the observed molecular universe and build a comprehensive small molecule knowledge base. These ambitious goals build on our unique expertise in both AI and MS to create next-generation, data-driven software solutions for molecular discovery from untargeted MS data."