A5017474568- Advanced Neural Network Applications
- Advanced Proteomics Techniques and Applications
- Protein Degradation and Inhibitors
- Remote Sensing and LiDAR Applications
- Histone Deacetylase Inhibitors Research
- Autonomous Vehicle Technology and Safety
- Image and Object Detection Techniques
- Microbial Natural Products and Biosynthesis
- Infrastructure Maintenance and Monitoring
- Bioinformatics and Genomic Networks
- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
- Advanced biosensing and bioanalysis techniques
- Face recognition and analysis
- Cell Image Analysis Techniques
- Cancer Research and Treatments
- Face and Expression Recognition
- Computer Graphics and Visualization Techniques
- Machine Learning in Bioinformatics
- Cancer therapeutics and mechanisms
- Additive Manufacturing and 3D Printing Technologies
- Industrial Vision Systems and Defect Detection
- 3D Shape Modeling and Analysis
- Cell death mechanisms and regulation
- Vehicle License Plate Recognition
Technical University of Munich
2014-2025
Leibniz-Institute for Food Systems Biology at the Technical University of Munich
2023
Universität Ulm
2017-2018
Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding extent and time- dose-response characteristics drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands PTMs in cells to shed light on target engagement drug mechanism action. Examples range from detecting DNA damage chemotherapeutics, identifying drug-specific PTM...
Abstract Post-translational modifications (PTMs) play pivotal roles in regulating cellular signaling, fine-tuning protein function, and orchestrating complex biological processes. Despite their importance, the lack of comprehensive tools for studying PTMs from a pathway-centric perspective has limited our ability to understand how modulate pathways on molecular level. Here, we present PTMNavigator, tool integrated into ProteomicsDB platform that offers an interactive interface researchers...
Recent improvements in object detection are driven by the success of convolutional neural networks (CNN). They able to learn rich features outperforming hand-crafted features. So far, research traffic light mainly focused on features, such as color, shape or brightness bulb. This paper presents a deep learning approach for accurate adapting single shot (SSD) approach. SSD performs proposals creation and classification using CNN. The original struggles detecting very small objects, which is...
ProteomicsDB (https://www.ProteomicsDB.org) is a multi-omics and multi-organism resource for life science research. In this update, we present our efforts to continuously develop expand ProteomicsDB. The major focus over the last two years was improving findability, accessibility, interoperability reusability (FAIR) of data as well its implementation. For purpose, release new application programming interface (API) that provides systematic access essentially all in Second, open-source user...
Abstract Machine learning (ML) and deep (DL) models for peptide property prediction such as Prosit have enabled the creation of high quality in silico reference libraries. These libraries are used various applications, ranging from data‐independent acquisition (DIA) data analysis to data‐driven rescoring search engine results. Here, we present Oktoberfest, an open source Python package our spectral library generation pipeline originally only available online via ProteomicsDB. Oktoberfest is...
Abstract Proteomics is making important contributions to drug discovery, from target deconvolution mechanism of action (MoA) elucidation and the identification biomarkers response. Here we introduce decryptE, a proteome-wide approach that measures full dose–response characteristics drug-induced protein expression changes informs cellular MoA. Assaying 144 clinical drugs research compounds against 8,000 proteins resulted in more than 1 million curves can be interactively explored online...
Autonomous driving is a topic in computer vision which has captured great deal of attention recent years. One key problem the detection and state analysis traffic lights. Even over time, very few datasets for research this have been published they vary widely quantity quality. To address complexity light recognition, we introduce DriveU**driveU joint innovation center Daimler AG University Ulm Traffic Light Dataset (DTLD), large-scale dataset consisting more than 230,000 annotations. All...
Abstract The DNA-damaging agent gemcitabine (GEM) is a first-line treatment for pancreatic cancer but chemoresistance frequently observed. Several clinical trials investigate the efficacy of GEM in combination with targeted drugs including kinase inhibitors experimental evidence such rational often unclear. Here, we phenotypically screened 13 human adenocarcinoma (PDAC) cell lines against 140 and observed strong synergy ATR inhibitor Elimusertib most lines. Dose-dependent phosphoproteome...
Abstract Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect particularly apparent in entities such as sarcomas for which the oncogenic drivers clear. To investigate more systematically how cellular proteotypes of sarcoma cells shape their response to targeted drugs, we profiled proteomes and phosphoproteomes 17 cell lines screened same against 150 drugs. The resulting 2550 phenotypic profiles revealed...
This paper introduces three methods to improve traffic light recognition by using the stereo camera color image in tandem with disparity image. The first method is object candidate filtering analyzing values inside an candidate. second applies relative positioning filter. Using depth measurement obtained from as well intrinsic and extrinsic calibration, a dimensional distance vehicle can be calculated. Based on known real world locations, filter able suppress thirty seventy percent of false...
Traffic light recognition is an object detection task mainly investigated on monocular images from a single camera [1], [2], [3], [4], [5] usually one with small field of view. They guarantee high resolution and less distortion. Both properties support common state the art detectors. However, single-camera setup only covers certain distance range. lights in close range disappear When stopped at stop line intersection, vehicle can-not recognize toggle process traffic light. In this paper...
Traffic light recognition belongs to the most difficult topics in context of autonomous driving. Most described systems literature follow a classical object approach consisting detection, verification and tracking. Proceeding from these three tasks, detection part is crucial importance, as overlooked traffic lights can likely not be recovered subsequent steps. Many published rely on feature detectors which try detect lamp. The frequently used include spotlight detector, color based...
Sliding window approaches have been widely used for object recognition tasks in recent years [19], [4], [5], [18]. They guarantee an investigation of the entire input image to be detected and allow a localization that object. Despite current trend towards deep neural networks, sliding methods are still combination with convolutional networks [22]. The risk overlooking is clearly reduced compared alternative detection which detect objects based on shape, edges or color. Nevertheless,...
Abstract Post-translational modifications (PTMs) play pivotal roles in regulating cellular signaling, fine-tuning protein function, and orchestrating complex biological processes. Despite their importance, the lack of comprehensive tools for studying PTMs from a pathway-centric perspective has limited our ability to understand how modulate pathways on molecular level. Here, we present PTMNavigator, tool integrated into ProteomicsDB platform, which offers an interactive interface researchers...
This paper presents an evaluation of algorithm that optimises the infills geometries contain at least one pointed end. Computation infills, as a part path planning, falls within slicing procedure, which in turn is standard process step creating 3D via rapid prototyping techniques. The computation infill trajectories were conducted according to its final application — droplet generating printer extrudes plastic droplets on moving platform. most commonly used techniques are several boundary...