A5079991493- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Advanced Control Systems Optimization
- Cell Image Analysis Techniques
- Data Visualization and Analytics
- Machine Learning in Bioinformatics
- Microbial Community Ecology and Physiology
- Medical Image Segmentation Techniques
- SARS-CoV-2 and COVID-19 Research
- Gaussian Processes and Bayesian Inference
- Bacteriophages and microbial interactions
- DNA and Biological Computing
- Gut microbiota and health
- Bacterial Genetics and Biotechnology
- Advanced biosensing and bioanalysis techniques
- Computational Drug Discovery Methods
- Artificial Intelligence in Healthcare and Education
- Tissue Engineering and Regenerative Medicine
- Single-cell and spatial transcriptomics
- Data Analysis with R
- Explainable Artificial Intelligence (XAI)
- Distributed Control Multi-Agent Systems
- Species Distribution and Climate Change
- Image Processing Techniques and Applications
- Kidney Stones and Urolithiasis Treatments
Robert Koch Institute
2022-2025
Freie Universität Berlin
2023-2025
Philipps University of Marburg
2020-2023
Loewe Center for Synthetic Microbiology
2023
Allen Institute for Artificial Intelligence
2023
University of North Carolina at Charlotte
2022
Linköping University
2022
National Center for Tumor Diseases
2019-2021
Helmholtz-Zentrum Dresden-Rossendorf
2020
Technische Universität Dresden
2020
Abstract Recent technological advances have made Virtual Reality (VR) attractive in both research and real world applications such as training, rehabilitation, gaming. Although these other fields benefited from VR technology, it remains unclear whether contributes to better spatial understanding training the context of surgical planning. In this study, we evaluated use by comparing recall information two learning conditions: a head-mounted display (HMD) desktop screen (DT). Specifically,...
Abstract The structural biology of membrane proteins (MP) is hampered by the difficulty in producing and purifying them. A comprehensive analysis protein databases revealed that 213 unique structures have been obtained after production target E. coli . primary expression system used was one based on T7 RNA polymerase, followed arabinose T5 promoter systems. C41λ(DE3) C43λ(DE3) bacterial mutant hosts contributed to 28% non structures. large scale protocols demonstrated a preference for...
Since the outbreak in 2019, researchers are trying to find effective drugs against SARS-CoV-2 virus based on de novo drug design and repurposing. The former approach is very time consuming needs extensive testing humans, whereas repurposing more promising, as have already been tested for side effects, etc. At present, there no treatment COVID-19 that clinically effective, but a huge amount of data from studies analyze potential drugs. We developed CORDITE efficiently combine state-of-the-art...
The use of complex biological molecules to solve computational problems is an emerging field at the interface between biology and computer science. There are two main categories in which molecules, especially DNA, investigated as alternatives silicon-based technologies. One DNA a storage medium, other for computing. Both strategies come with certain constraints. In current study, we present novel approach derived from chaos game representation generate code words that fulfill user-defined...
In an ever-growing need for data storage capacity, the Deoxyribonucleic Acid (DNA) molecule gains traction as a new medium with larger higher density, and longer lifespan over conventional media. To effectively use DNA storage, it is important to understand different methods of encoding information in compare their effectiveness. This requires evaluating which decoded sequences carry most encoded based on various attributes. However, navigating field coding theory years experience domain...
The growing AI field faces trust, transparency, fairness, and discrimination challenges. Despite the need for new regulations, there is a mismatch between regulatory science AI, preventing consistent framework. A five-layer nested model design validation aims to address these issues streamline application validation, improving adoption. This aligns with addresses practitioners' daily challenges, offers prescriptive guidance determining appropriate evaluation approaches by identifying unique...
The field of health informatics has been profoundly influenced by the development random forest models, which have led to significant advances in interpretability feature interactions. These models are characterized their robustness overfitting and parallelization, making them particularly useful this domain. However, increasing number features estimators forests can prevent domain experts from accurately interpreting global interactions, thereby compromising trust regulatory compliance. A...
Abstract Owing to the great variety of distinct peptide encodings, working on a biomedical classification task at hand is challenging. Researchers have determine encodings capable represent underlying patterns as numerical input for subsequent machine learning. A general guideline lacking in literature, thus, we present here first large-scale comprehensive study investigate performance wide range multiple datasets from different domains. For sake completeness, added additional sequence- and...
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The causes infectious disease COVID-19. biology coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly have only recently developed as rapid reaction to need fast detection, understanding, and treatment To control ongoing COVID-19 pandemic, it utmost importance get insight into evolution pathogenesis virus. In this review, we cover workflows...
Abstract It is known that microorganisms are essential for the functioning of ecosystems, but extent to which respond different environmental variables in their natural habitats not clear. In current study, we present a methodological framework quantify covariation microbial community habitat and this habitat. built on theoretical considerations systems ecology, makes use state‐of‐the‐art machine learning techniques can be used identify bioindicators. We apply data set containing operational...
Abstract Predicting if a set of mushrooms is edible or not corresponds to the task classifying them into two groups—edible poisonous—on basis classification rule. To support this binary task, we have collected largest and most comprehensive attribute based data available. In work, detail creation, curation simulation for classification. Thanks natural language processing, primary are on text book mushroom identification contain 173 species from 23 families. While secondary comprise simulated...
Evaluating the performance of multiple complex models, such as those found in biology, medicine, climatology, and machine learning, using conventional approaches is often challenging when various evaluation metrics simultaneously. The traditional approach, which relies on presenting multi-model scores table, presents an obstacle determining similarities between models order performance.By combining statistics, information theory, data visualization, juxtaposed Taylor Mutual Information...
The generation of high-quality assemblies, even for large eukaryotic genomes, has become a routine task many biologists thanks to recent advances in sequencing technologies. However, the annotation these assemblies - crucial step towards unlocking biology organism interest remained complex challenge that often requires advanced bioinformatics expertise. Here we present MOSGA, genome framework genomes with user-friendly web-interface generates and integrates annotations from various tools....
The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase the requirements power supply components, including permanent magnet synchronous motors (PMSMs). To infer part of system, machine learning techniques are widely employed, especially Gaussian process regression (GPR) due to its flexibility continuous system modeling guaranteed performance. For practical implementation, distributed GPR is adopted alleviate high computational...
This paper introduces an innovative approach to enhance distributed cooperative learning using Gaussian process (GP) regression in multi-agent systems (MASs). The key contribution of this work is the development elective algorithm, namely prior-aware GP (Pri-GP), which empowers agents with capability selectively request predictions from neighboring based on their trustworthiness. proposed Pri-GP effectively improves individual prediction accuracy, especially cases where prior knowledge agent...