A5032147131- Genomics and Phylogenetic Studies
- Reproductive System and Pregnancy
- Natural Language Processing Techniques
- Endometrial and Cervical Cancer Treatments
- Autonomous Vehicle Technology and Safety
- Numerical methods in inverse problems
- Gynecological conditions and treatments
- Vehicle emissions and performance
- Sparse and Compressive Sensing Techniques
- Image and Signal Denoising Methods
- Plant Reproductive Biology
- Fungal and yeast genetics research
- Chromosomal and Genetic Variations
- Traffic control and management
- Microbial Community Ecology and Physiology
- Traffic and Road Safety
- VLSI and Analog Circuit Testing
- Yersinia bacterium, plague, ectoparasites research
- Simulation Techniques and Applications
- Cell Image Analysis Techniques
- Anatomy and Medical Technology
- Neural dynamics and brain function
- Low-power high-performance VLSI design
- Contact Mechanics and Variational Inequalities
- Nuts composition and effects
Fraunhofer Institute for Industrial Mathematics
2021-2024
University of Tübingen
2013-2022
University of Freiburg
2020-2022
Boston Children's Hospital
2013
Bernstein Center for Computational Neuroscience Tübingen
2011
Google (United States)
2011
Université de Perpignan
2000
Centre National de la Recherche Scientifique
2000
Microsynth (Switzerland)
1997-1999
A major challenge in the analysis of environmental sequences is data integration. The question how to analyze different types a unified approach, addressing both taxonomic and functional aspects. To facilitate such analyses, we have substantially extended MEGAN, widely used program. new program, MEGAN4, provides an integrated approach metagenomic, metatranscriptomic, metaproteomic, rRNA data. While performed based on NCBI taxonomy, using SEED classification subsystems roles or KEGG pathways...
The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part vagina in females with normal ovarian function.While genetic causes have been identified for a small subset patients epigenetic mechanisms presumably contribute to pathogenic unfolding, too, etiology has remained largely enigmatic. A comprehensive understanding gene activity context disease crucial identify etiological components their potential interplay.So far, this...
Google Body gives any user access to 3D anatomy information typically reserved for physicians and medical students. The can peel away add back layers of anatomy, rotate zoom, select entities such as muscles nerves, search. Direct links view the male or female model -- with an optional user-supplied annotation be forwarded friends, family, physicians. And it all works from a browser, smartphone, tablet.
To identify potential genetic causes for Mayer-Rokitansky-Küster-Hauser syndrome (MRKH), we analyzed blood and rudimentary uterine tissue of 5 MRKH discordant monozygotic twin pairs. Assuming that a variant solely identified in the affected or could cause phenotype, mosaic ACTR3B with high allele frequency tissue, low twin, almost absent unaffected twin. Focusing on candidate genes, detected pathogenic GREB1L one pair their mother showing reduced phenotypic penetrance. Furthermore, two...
Abstract Summary Segmentation of neural somata is a crucial and usually the most time-consuming step in analysis optical functional imaging neuronal microcircuits. In recent years, multiple auto-segmentation tools have been developed to improve speed consistency segmentation process, mostly, using deep learning approaches. Current tools, while advanced, still encounter challenges producing accurate results, especially datasets with low signal-to-noise ratio. This has led reliance on manual...
Deep Neural Networks (DNNs) are capable of solving complex problems in domains related to embedded systems, such as image and natural language processing. To efficiently implement DNNs on a specific FPGA platform for given cost criterion, e.g. energy efficiency, an enormous amount design parameters has be considered from the topology down final hardware implementation. Interdependencies between different layers have taken into account explored efficiently, making it hardly possible find...
While there was great progress regarding the technology and its implementation for vehicles equipped with automated driving systems (ADS), problem of how to proof their safety as a necessary precondition prior market launch remains unsolved. One promising solution are scenario-based test approaches; however, is no commonly accepted way systematically generate extract set relevant scenarios be tested sufficiently capture real-world traffic dynamics, especially urban operational design...
Abstract Objective Mayer-Rokitansky-Küster-Hauser syndrome (MRKH) is a rare congenital disease manifesting with aplasia or severe hypoplasia of uterine structures. Even though extensive studies have been performed, for the majority cases etiology remains unclear. In this study, we sought to identify genetic causes in discordant monozygotic (MZ) twins using genome sequencing blood both as well tissue affected twin. addition, profiled endometrial transcriptome compare perturbations those...
Scenario-based testing is a promising approach to solve the challenge of proving safe behavior vehicles equipped with automated driving systems.Since an infinite number concrete scenarios can theoretically occur in realworld road traffic, extraction relevant terms safety-related these systems key aspect for their successful verification and validation.Therefore, method extracting multimodal urban traffic from naturalistic data unsupervised manner, minimizing amount (potentially biased) prior...
Abstract The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part vagina in females with normal ovarian function. While genetic causes have been identified for a small subset patients epigenetic mechanisms presumably contribute to pathogenic unfolding, too, etiology has remained largely enigmatic. A comprehensive understanding gene activity context disease crucial identify etiological components their potential interplay. So...
Federated Learning as a decentralized artificial intelligence (AI) solution solves variety of problems in industrial applications. It enables continuously self-improving AI, which can be deployed everywhere at the edge. However, bringing AI to production for generating real business impact is challenging task. Especially case Learning, expertise and resources from multiple domains are required realize its full potential. Having this mind we have developed an innovative framework FACT based...
In this paper, we focus on learning optimal parameters for PDE-based image denoising and decomposition models. First, learn the regularization parameter differential operator gray-scale using fractional Laplacian in combination with a bilevel optimization problem. our setting allows use of Fourier transform, which enables operator. We prove stable explainable results as an advantage comparison to machine approaches. The numerical experiments correlate theoretical model settings show...
In this paper, we focus on learning optimal parameters for PDE-based image regularization and decomposition. First learn the parameter differential operator gray-scale denoising using fractional Laplacian in combination with a bilevel optimization problem. our setting allows use of Fourier transform, which enables operator. We prove stable explainable results as an advantage comparison to other machine approaches. The numerical experiments correlate theoretical model show reduction computing...
Scenario-based testing is a promising approach to solve the challenge of proving safe behavior vehicles equipped with automated driving systems. Since an infinite number concrete scenarios can theoretically occur in real-world road traffic, extraction relevant terms safety-related these systems key aspect for their successful verification and validation. Therefore, method extracting multimodal urban traffic from naturalistic data unsupervised manner, minimizing amount (potentially biased)...