Claire Jean-Quartier

• MMsc. PhD
• Graz University of Technology

Objective Data sharing promotes the scientific progress. However, not all data can be shared freely due to privacy issues. This work is intended to foster FAIR sharing of sensitive data exemplary in the biomedical domain, via an integrated computational approach for utilizing and enriching individual datasets by scientists without coding experience...

While source code of software and algorithms depicts an essential component in all fields of modern research involving data analysis and processing steps, it is uncommonly shared upon publication of results throughout disciplines. Simple guidelines to generate reproducible source code have been published. Still, code optimization supporting its rep...

Open data provide the scientific community and other stakeholders with unrestricted access to data. Open data serve as a foundation for reproducing research findings, while also facilitating collaboration and enabling novel discoveries. However, open data practices are still not commonly applied. To contribute to the implementation of open data str...

This contribution explores the underuse of artificial intelligence (AI) in the health sector, what this means for practice, and how much the underuse can cost. Attention is drawn to the relevance of an issue that the European Parliament has outlined as a "major threat" in 2020. At its heart is the risk that research and development on trusted AI sy...

Within the FAIR Data Austria project, supported by the Federal Ministry for Education, Science, and Research (BMBWF), a national strategy has been established to advance the creation of tailored Data Stewardship solutions for the Austrian context. The strategy, formalized as a toolbox, delineates various Data Steward models, corresponding competenc...

The black-box nature of most artificial intelligence (AI) models encourages the development of explainability methods to engender trust into the AI decision-making process. Such methods can be broadly categorized into two main types: post hoc explanations and inherently interpretable algorithms. We aimed at analyzing the possible associations betwe...

In response to socioeconomic development, the number of machine learning applications has increased, along with the calls for algorithmic transparency and further sustainability in terms of energy efficient technologies. Modern computer algorithms that process large amounts of information, particularly artificial intelligence methods and their work...

Recent developments in research on artificial intelligence (AI) in medicine deal with the analysis of image data such as Magnetic Resonance Imaging (MRI) scans to support the of decision-making of medical personnel. For this purpose, machine learning (ML) algorithms are often used, which do not explain the internal decision-making process at all. T...

Research and development are facilitated by sharing knowledge bases, and the innovation process benefits from collaborative efforts that involve the collective utilization of data. Until now, most companies and organizations have produced and collected various types of data, and stored them in data silos that still have to be integrated with one an...

This study aims to reflect on a list of libraries providing decision support to AI models. The goal is to assist in finding suitable libraries that support visual explainability and interpretability of the output of their AI model. Especially in sensitive application areas, such as medicine, this is crucial for understanding the decision-making pro...

Supporting data sharing is paramount to making progress in cancer research. This includes the search for more precise targeted therapies and the search for novel biomarkers, through cluster and classification analysis, and extends to learning details in signal transduction pathways or intra- and intercellular interactions in cancer, through network...

Mitochondrial Ca²⁺ uptake regulates mitochondrial function and contributes to cell signaling. Accordingly, quantifying mitochondrial Ca²⁺ signals and elaborating the mechanisms that accomplish mitochondrial Ca²⁺ uptake are essential to gain our understanding of cell biology. Here, we describe the benefits and drawbacks of various established old an...

Background Malignant brain tumor diseases exhibit differences within molecular features depending on the patient’s age. Methods In this work, we use gene mutation data from public resources to explore age specifics about glioma. We use both an explainable clustering as well as classification approach to find and interpret age-based differences in...

This paper reviews guidelines on how medical imaging analysis can be enhanced by Artificial Intelligence (AI) and Machine Learning (ML). In addition to outlining current and potential future developments, we also provide background information on chemical imaging and discuss the advantages of Explainable AI. We hypothesize that it is a matter of AI...

The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, c...

State of the art genomic methods produce an abundance of data which ultimately increases the quantity within and of data repositories. Thereby, open data is of much importance to boost scientific studies for combating disease. More and more often, there are several data sources available, offering diverse sample data. Particularly, interpretation o...

Abstract Enhanced resolution of 7 T magnetic resonance imaging (MRI) scanners has considerably advanced our knowledge of structure and function in human and animal brains. Post-industrialized countries are particularly prone to an ever-increasing number of ageing individuals and ageing-associated neurodegenerative diseases. Neurodegenerative diseas...

Background A plethora of Web resources are available offering information on clinical, pre-clinical, genomic and theoretical aspects of cancer, including not only the comprehensive cancer projects as ICGC and TCGA, but also less-known and more specialized projects on pediatric diseases such as PCGP. However, in case of data on childhood cancer ther...

Background: Improving our understanding of cancer and other complex diseases requires integrating diverse data sets and algorithms. Intertwining in vivo and in vitro data and in silico models are paramount to overcome intrinsic difficulties given by data complexity. Importantly, this approach also helps to uncover underlying molecular mechanisms....

The various interplaying variables of tumor growth remain key questions in cancer research, in particular what makes such a growth malignant and what are possible therapies to stop the growth and prevent re-growth. Given the complexity and heterogeneity of the disease, as well as the steadily growing set of publicly available big data sets, there i...

Background Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biolog...

Cancer constitutes a condition and is referred to a group of numerous different diseases, that are characterized by uncontrolled cell growth. Tumors, in the broader sense, are described by abnormal cell growth and are not exclusively cancerous. The molecular basis involves a process of multiple steps and underlying signaling pathways, building up a...

The general disease group of malignant neoplasms depicts one of the leading and increasing causes for death. The underlying complexity of cancer demands for abstractions to disclose an exclusive subset of information related to the disease. Our idea is to create a user interface for linking a simulation on cancer modeling to relevant additional pub...

Understanding living systems is crucial for curing diseases. To achieve this task we have to understand biological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of databases and tools that support analysts in exploring protein-protein interactions on an integrated level for knowledge discovery. They...

Mitochondrial Ca(2+) uptake regulates mitochondrial function and contributes to cell signaling. Accordingly, quantifying mitochondrial Ca(2+) signals and elaborating the mechanisms that accomplish mitochondrial Ca(2+) uptake are essential to gain our understanding of cell biology. Here, we describe the benefits and drawbacks of various established...

A protein referred to as CCDC109A and then renamed to mitochondrial calcium uniporter (MCU) has recently been shown to accomplish mitochondrial Ca(2+) uptake in different cell types. In this study, we investigated whole-mitoplast inward cation currents and single Ca(2+) channel activities in mitoplasts prepared from stable MCU knockdown HeLa cells...

The transfer of Ca2+ across the inner mitochondrial membrane is an important physiological process linked to the regulation of metabolism, signal transduction, and cell death. While the definite molecular composition of mitochondrial Ca2+ uptake sites remains unknown, several proteins of the inner mitochondrial membrane, that are likely to accompli...

Previous studies have demonstrated several molecularly distinct players involved in mitochondrial Ca(2+) uptake. In the present study, electrophysiological recordings on mitoplasts that were isolated from HeLa cells were performed in order to biophysically and pharmacologically characterize Ca(2+) currents across the inner mitochondrial membrane. I...

Mitochondrial Ca(2+) sequestration is a well-known process that is involved in various physiological and pathological mechanisms. Using isolated suspended mitochondria one unique mitochondrial Ca(2+) uniporter was considered to account ubiquitously for the transfer of Ca(2+) into these organelles. However, by applying alternative techniques for mea...

Cytosolic Ca2+ signals are transferred into mitochondria over a huge concentration range. In our recent work we described uncoupling proteins 2 and 3 (UCP2/3) to be fundamental for mitochondrial uptake of high Ca2+ domains in mitochondria-ER junctions. On the other hand, the leucine zipper EF hand-containing transmembrane protein 1 (Letm1) was iden...

A versatile two-step method has been developed that allows linking of biomolecules covalently to hydrogen-terminated group-IV semiconductors by means of epoxy-alkenes. First, the terminal C==C double bond of the alkene forms a covalent bond with the silicon, germanium, or diamond surface by UV-mediated hydrosilylation. The terminal oxirane moiety t...

Online-Messungen zur Partikelbildung und zur gesteuerten Agglomeration me-tallischer und halbleitender Nanoparti-kel durchgeführt. Es zeigte sich eine sehr hohe Sensitivität der HRS-Spek-troskopie bezüglich des Agglomera-tionsprozesses, der mit alternativen Messmethoden wie UV-Vis-Spektrosko-pie und dynamischer Lichtstreuung nur unzureichend bzw. g...