A5060733666- Advanced Software Engineering Methodologies
- Software Engineering Research
- Service-Oriented Architecture and Web Services
- Software System Performance and Reliability
- Birth, Development, and Health
- Human Mobility and Location-Based Analysis
- Software Engineering Techniques and Practices
- Data Management and Algorithms
- Housing Market and Economics
- Real estate and construction management
- Inertial Sensor and Navigation
- Robotics and Sensor-Based Localization
- Pregnancy and preeclampsia studies
- Linguistic research and analysis
- Data Mining Algorithms and Applications
- Graphite, nuclear technology, radiation studies
- Single-cell and spatial transcriptomics
- Insurance and Financial Risk Management
- Preterm Birth and Chorioamnionitis
- Target Tracking and Data Fusion in Sensor Networks
- Real-Time Systems Scheduling
- Software Reliability and Analysis Research
- Context-Aware Activity Recognition Systems
- Sociology and Education Studies
- Model-Driven Software Engineering Techniques
University of Rostock
2022-2025
Stanford University
2020-2025
Fraunhofer Institute for Experimental Software Engineering
2015-2025
Justus-Liebig-Universität Gießen
2021-2024
Stanford Medicine
2020-2023
IBM (Germany)
2022
University of Würzburg
2012-2021
Universidad de Navarra
2007-2021
ORCID
2021
Technische Universität Braunschweig
2010-2019
Over more than two decades, numerous variability modeling techniques have been introduced in academia and industry. However, little is known about the actual use of these techniques. While dozens experience reports on software product line engineering exist, only very few focus modeling. This lack empirical data threatens validity existing techniques, hinders their improvement. As part our effort to improve understanding modeling, we present results a survey questionnaire distributed...
Many companies develop software product lines-collections of similar products-by cloning and adapting artifacts existing variants. Transforming such cloned variants into a "single-copy" line representation is considered an important re-engineering activity, as reflected in numerous tools methodologies available. However, development practices that use to implement lines have not been systematically studied. This lack empirical knowledge threatens the validity applicability approaches...
Peripheral blood dynamics in the 100 days before delivery reveal a transition from pregnancy maintenance to prelabor biology.
In this paper, we present an integrated system concept for the living assistance domain based on ambient intelligence technology and discuss resulting challenges software engineering discipline. Automated systems represent a promising approach prolongation of independent self-conducted life handicapped elderly people thereby, enhancing their quality minimizing need manual social/medical care. It is demonstrated that must realize flexibility adaptability at algorithmic, architectural human...
The notion of features is commonly used to describe the functional and non-functional characteristics a system. In software product line engineering, often become prime entities reuse are distinguish individual products line. Properly decomposing into features, correctly using in all engineering phases, core immediate long-term success such Yet, although more than ten different definitions term feature exist, it still very abstract concept. Definitions lack concrete guidelines on how use practice.
<h3>Importance</h3> Worldwide, preterm birth (PTB) is the single largest cause of deaths in perinatal and neonatal period associated with increased morbidity young children. The PTB multifactorial, development generalizable biological models may enable early detection guide therapeutic studies. <h3>Objective</h3> To investigate ability transcriptomics proteomics profiling plasma metabolomics analysis urine to identify measurements PTB. <h3>Design, Setting, Participants</h3> This...
Although prematurity is the single largest cause of death in children under 5 years age, current definition prematurity, based on gestational lacks precision needed for guiding care decisions. Here, we propose a longitudinal risk assessment adverse neonatal outcomes newborns deep learning model that uses electronic health records (EHRs) to predict wide range over period starting shortly before conception and ending months after birth. By linking EHRs Lucile Packard Children’s Hospital...
Reference architectures have emerged as a special type of software architecture that achieves well-recognized understanding specific domains, promoting reuse design expertise and facilitating the development, standardization, evolution systems. Designed for various domains purpose, they increasingly impacted important aspects system such productivity quality However, reference been sometimes established without an adequate concern about which elements should encompass. Besides that, there is...
The development of ICT infrastructures has facilitated the emergence new paradigms for looking at society and environment over last few years. Participatory environmental sensing, i.e. directly involving citizens in monitoring, is one example, which hoped to encourage learning enhance awareness issues. In this paper, an analysis behaviour individuals involved noise sensing presented. Citizens have been measuring activities through WideNoise smartphone application. This application designed...
Abstract The incidence of autism spectrum disorder (ASD) has been rising, however ASD-risk biomarkers remain lacking. We previously identified the presence maternal autoantibodies to fetal brain proteins specific ASD, now termed autoantibody-related (MAR) ASD. current study aimed create and validate a serological assay identify ASD-specific autoantibody patterns reactivity against eight (CRMP1, CRMP2, GDA, NSE, LDHA, LDHB, STIP1, YBOX) that are highly expressed in developing brain, determine...
Preeclampsia is a complex disease of pregnancy whose physiopathology remains unclear. We developed machine-learning models for early prediction preeclampsia (first 16 weeks pregnancy) and over gestation by analyzing six omics datasets from longitudinal cohort pregnant women. For pregnancy, model using nine urine metabolites had the highest accuracy was validated on an independent (area under receiver-operating characteristic curve [AUC] = 0.88, 95% confidence interval [CI] [0.76, 0.99]...
Human milk contains all of the essential nutrients required by infant within a complex matrix that enhances bioavailability many those nutrients. In addition, human is source bioactive components, living cells and microbes facilitate transition to life outside womb. Our ability fully appreciate importance this relies on recognition short- long-term health benefits and, as highlighted in previous sections supplement, its ecology (i.e., interactions among lactating parent breastfed well...
Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling multivariate modeling to investigate biological signatures these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples 231...
Abstract Advanced measurement and data storage technologies have enabled high-dimensional profiling of complex biological systems. For this, modern multiomics studies regularly produce datasets with hundreds thousands measurements per sample, enabling a new era precision medicine. Correlation analysis is an important first step to gain deeper insights into the coordination underlying processes such However, construction large correlation networks in remains major computational challenge...
Abstract Preterm birth (PTB) is the leading cause of infant mortality globally. Research has focused on developing predictive models for PTB without prioritizing cost-effective interventions. Physical activity and sleep present unique opportunities interventions in low- middle-income populations (LMICs). However, objective measurement physical remains challenging self-reported metrics suffer from low-resolution accuracy. In this study, we use data collected using a wearable device comprising...
Abstract High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity cellular systems. We introduce VoPo ( https://github.com/stanleyn/VoPo ), a machine learning algorithm predictive modeling and comprehensive visualization captured in large datasets. In three mass cytometry datasets, with largest measuring hundreds millions cells over samples, defines phenotypically functionally homogeneous cell populations. further...
Abstract Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) accurately depicts the chromatin regulatory state and altered mechanisms guiding gene expression in disease. However, bulk entangles information from different cell types obscures cellular heterogeneity. To address this, we developed Cellformer, a deep learning method that deconvolutes ATAC-seq into type-specific across whole genome. Cellformer enables cost-effective open profiling large cohorts. Applied to 191...
The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques, tools. In this paper, we focus on the Ubicon platform, its applications, a large spectrum analysis results. provides extensible framework for building hosting applications targeting both environments. We summarize architecture exemplify implementation using four real-world built top Ubicon. addition, discuss several scientific experiments in...