جستجوی استاد راهنمای دانشگاهی

Stefan Hüttelmaierمشاهده پروفایل

استاد

• Molecular Biology
• Cancer Biology
• RNA Biology
• +۳ مورد دیگر

Stefan Hüttelmaier is a Full Professor of Molecular Cell Biology at Martin-Luther University Halle-Wittenberg, Germany. He leads the Core Facility Imaging at the Charles Tanford Protein Center and directs research into RNA-binding proteins' roles in cancer. His career includes postdoctoral work at Albert Einstein College of Medicine and leadership roles in the RTG 1591 research group. His work focuses on RAVER1 protein dynamics, perinucleolar compartments, and RNA metabolism in cancer progression. Education: PhD in Biotechnology (2000, University of Braunschweig), postdoctoral training at Albert Einstein College of Medicine (2001–2004). Academic milestones include Associate Professor (2009) and Full Professor (2014) positions. Research spans RNA-protein interactions, cancer biology, and translational mechanisms in tumors. Key research interests include RNA-binding proteins' roles in cancer (RAVER1, IGF2BP1), alternative splicing, and miRNA regulation. His lab investigates how these molecules influence cancer cell behavior, metastasis, and therapeutic resistance. Recent work highlights druggable targets like IGF2BP1 and mechanisms linking RNA modifications to oncogenesis. Leadership roles include RTG 1591 speaker and Core Facility director. Publications emphasize RNA biology in cancer, with contributions to understanding post-transcriptional control and therapeutic strategies targeting RNA pathways. His interdisciplinary approach combines molecular biology, biochemistry, and computational modeling to address clinical challenges in oncology.

Susanne Gerberمشاهده پروفایل

استاد

• Bioinformatics
• Computational Genomics
• Systems Biology
• +۲ مورد دیگر

Susanne Gerber is a Professor at iDNA and Adjunct Director at the Institute of Molecular Biology (IMB), Johannes Gutenberg University Mainz (JGU), affiliated with the Faculty of Biology's Bioinformatics department. Her academic journey includes an Assistant Professorship in Bioinformatics at JGU (2015-2020) and postdoctoral research at Università della Svizzera italiana. Her educational background comprises a PhD in Biophysics from Humboldt University of Berlin (2011), an M.Sc. in Bioinformatics from Free University of Berlin and Konrad Zuse Institute (2007), and a B.Sc. in Bioinformatics from Free University of Berlin and Max Planck Institute (2004). Dr. Gerber's research spans Bioinformatics, Computational Genomics, Systems Biology, Molecular Evolution, and Neuroinformatics , focusing on developing computational frameworks for genomic analysis, neurodegenerative disease modeling, and microbiome interactions. Her work integrates machine learning with multi-omics data to address complex biological questions in molecular evolution and neural systems. Analysis of her 15 most recent publications (2024-2025) reveals a strong emphasis on nanopore sequencing applications for RNA modification detection, deep learning frameworks for genomic data enhancement, and neurobehavioral modeling using AI-driven approaches. Key thematic clusters include epitranscriptomics, chromatin dynamics, and computational psychiatry with ethical AI considerations. Her methodological innovations include tools like COMET for network analysis, CCUT for chromatin data enhancement, and ModiDeC for RNA modification classification, demonstrating translational impact across genomics and neuroscience. Dr. Gerber leads research groups at IMB and iDNA focusing on computational genomics, advising students in bioinformatics and securing grants for AI-driven genomic analysis. Her labs develop open-source tools for nanopore data processing and neuroimaging analysis, fostering collaboration between computational and experimental biologists.

Dieter Saurمشاهده پروفایل

استاد

• Translational Cancer Research
• Genetic Alterations in Cancer
• Personalized Medicine
• +۳ مورد دیگر

Prof. Dieter Saur is a Professor of Translational Tumor Research at the Technical University of Munich (TUM) and Head of the Department at the German Cancer Research Center (DKFZ). His research focuses on developing personalized cancer therapies through mechanistic studies of tumor-relevant genetic alterations, with a particular emphasis on pancreatic and gastrointestinal cancers. Education: Studied medicine at Ludwig Maximilian University of Munich, earned a doctorate in neurogastroenterology, completed specialist training in gastroenterology and gastrointestinal oncology, and habilitation in internal medicine. He became a senior physician at University Hospital rechts der Isar before his current roles at TUM and DKFZ. Research Interests: Translational cancer research, genetic drivers of tumor progression, early detection methods, and targeted therapies for pancreatic and gastrointestinal cancers. He uses genetically engineered mouse models and organoid systems to study tumor heterogeneity and therapeutic resistance. Awards: Recipient of prestigious grants like the ERC Consolidator Grant (2015) and awards such as the Martin Wienbeck Award (2014) and Rising Star Award (2006). His work bridges basic science and clinical translation, emphasizing interdisciplinary approaches. Labs/Teams: Leads the Translational Tumor Research group at TUM and collaborates with the DKFZ to advance preclinical and clinical cancer research. Key projects include exploring KRAS signaling pathways, tumor microenvironment dynamics, and immune checkpoint therapies.

Johannes C. Hellmuthمشاهده پروفایل

پژوهشگر

• Non-Coding Cancer Biology
• Super-Enhancer Regulation
• CRISPRi Screening
• +۳ مورد دیگر

Dr. Johannes C. Hellmuth leads the DKTK Junior Clinical Cooperation Unit for Non-Coding Cancer Biology at the Ludwig Maximilian University of Munich (LMU Klinikum), affiliated with the Department of Pathology under the School of Medicine. His research focuses on exploiting vulnerabilities in the non-coding genome of cancer cells, particularly through super-enhancer analysis and CRISPRi screening. Research Interests: Functional interrogation of the non-coding genome Super-enhancer proteomes in oncogenesis Transcriptional condensates as therapeutic targets Non-invasive super-enhancer diagnostics Publication Trends: Recent work spans epigenetic regulation in lymphomas, super-enhancer dependencies in cancer, and chromatin dynamics during immune cell differentiation, with a focus on integrating omics data for personalized therapies.

• Comparative Genomics
• Bioinformatics
• Epigenetics
• +۳ مورد دیگر

Jonathan Göke is a researcher at the Genome Institute of Singapore (GIS), part of A*STAR. He completed his PhD at the International Max Planck Research School for Computational Biology and Scientific Computing (IMPRS-CBSC), supervised by Prof. Dr. Martin Vingron. His work focuses on Comparative Genomics and studying recurring motifs in non-coding DNA , with applications in stem cell biology and epigenetics. Education: B.Sc. in Bioinformatics, Freie Universität Berlin (2007). PhD in Computational Biology, IMPRS-CBSC (2012). Visiting student, University of Sheffield (2006). Research interests include analyzing gene regulatory elements, kinase-chromatin interactions, and computational methods for genomic analysis. His work bridges bioinformatics and experimental biology, with contributions to understanding embryonic stem cell regulation and intellectual disability genetics. Advising and grants: No documented advisees, but contributed to doctoral training through IMPRS-CBSC. Current projects include genomic studies at GIS, though specific grants are not listed here. Labs/Teams: Affiliated with GIS, which focuses on genomic research in health and disease.

• Explainable Artificial Intelligence
• Type-2 Fuzzy Logic Systems
• Computational Intelligence
• +۱۲ مورد دیگر

Hani Hagras is a Professor in the School of Computer Science and Electronic Engineering at the University of Essex, UK , where he leads pioneering research in type-2 fuzzy logic systems and explainable artificial intelligence (XAI) . His work bridges theoretical advances with real-world applications in smart infrastructure, healthcare, telecommunications, and ambient intelligence. His research interests include explainable AI, type-2 fuzzy logic, computational intelligence, machine learning, human-computer interaction, and intelligent systems. He investigates how fuzzy systems can enhance the transparency, robustness, and adaptability of AI models, particularly in uncertain and dynamic environments. His recent work explores applications in genomics, predictive maintenance, and smart grid optimization. The publication trends show a strong focus on integrating fuzzy logic with deep learning and optimization techniques to create interpretable models. His work frequently appears in top-tier journals such as IEEE Transactions on Fuzzy Systems , IEEE Transactions on Artificial Intelligence , and Neurocomputing . He emphasizes real-world applicability, often collaborating with industry partners like BT. ORCID: 0000-0002-2818-5292 He has advised numerous PhD and Master’s students, including Mehrin Kiani, Ashish Bhatia, and Hugo Leon-Garza, many of whose research projects focus on workforce optimization, healthcare AI, and intelligent systems. His research has been supported by major grants, particularly in smart environments and telecommunications. Hani Hagras is actively involved in leading research labs and teams at the University of Essex, including work on augmented reality for field service support, georeferenced data visualization , and ambient-assisted living systems. His team develops fuzzy logic frameworks for real-time decision-making in complex environments.

• Translational Genomics
• Statistical Genetics
• Computational Genomics
• +۴ مورد دیگر

Eleftheria Zeggini serves as Director of the Institute of Translational Genomics at Helmholtz Munich and holds the Liesel Beckmann Distinguished Professorship and Chair of Translational Genomics at the Technical University of Munich (TUM) School of Medicine. Her research leverages big data in genetics and genomics to translate genomic insights into disease mechanisms, advancing precision medicine through robust statistical and computational approaches integrating multi-omics data, electronic health records, and diverse population studies. Her educational background includes a PhD in Immunogenetics of Juvenile Arthritis from the University of Manchester School of Medicine (2003) and a Bachelor of Science (Hons) in Biochemistry from the University of Manchester Institute of Science and Technology (1999). Prior appointments include Group Leader at the Wellcome Sanger Institute (2008-2018) and Wellcome Research Career Development Fellow at the University of Oxford (2006-2008). Zeggini's research spans translational genomics, statistical genetics, and computational biology with emphasis on genetic architecture of complex diseases. Her team develops tools for multi-omics integration to dissect sequence variation in human health, focusing on osteoarthritis, type 2 diabetes, and cardiometabolic disorders. Recent work prioritizes health equity through tissue-specific multi-ancestry genomic studies and electronic health record integration, driving discovery of novel therapeutic targets and disease mechanisms. Analysis of her 15 most recent publications reveals dominant themes in osteoarthritis genomics (6 articles), type 2 diabetes heterogeneity (3 articles), and multi-ancestry genomic equity (3 articles). Her work consistently employs whole-genome sequencing, causal inference methods, and large-scale biobank analyses across diverse populations, with strong translational focus on precision medicine applications. Major scientific recognition includes: Elected Member of Academia Europaea (2024) Greek Excellence Award (2024) National Representative to the EMBL Council (2022) Elected Fellow of the Academy of Medical Sciences, UK (2020) Argo Award for Distinguished Greeks Abroad (2020) Honorary Senior Fellow, University of Cambridge (2018) Honorary Professor, University of Bristol (2018) Zeggini actively mentors early-career researchers while promoting diversity and inclusion in science. Her leadership in major consortia like UK Biobank analyses and ENABLE program demonstrates sustained grant acquisition capability. Current research direction focuses on developing computational frameworks for next-generation translational genomics, with particular emphasis on addressing health disparities through equitable genomic data representation. She directs Helmholtz Munich's Institute of Translational Genomics, which houses a multidisciplinary team of computational biologists, geneticists, and clinicians developing statistical tools for big data integration. The institute serves as a hub for precision medicine innovation, collaborating with TUM's medical faculty and international networks to accelerate genomic discoveries into clinical applications.

• Aging Research
• Bioinformatics
• Epigenetics
• +۳ مورد دیگر

Arne Sahm serves as Junior Research Group Leader for Computational Phenomics at the Leibniz Institute for Environmental Medical Research (IUF) in Düsseldorf, Germany. His work bridges environmental toxicology, aging biology, and computational genomics through innovative multi-omics approaches applied to exceptional animal models. Dr. Sahm's research centers on deciphering molecular aging mechanisms triggered by environmental toxins (particles, radiation, chemicals) using alternative models like naked mole rats, killifish, and Hydra. He specializes in comparative epigenomics and transcriptomics to identify stress-adaptation pathways, with particular focus on persistent epigenetic alterations that accelerate aging beyond exposure periods. His group develops specialized bioinformatics pipelines for evolutionary genomics and epigenomic clock analysis. Recent publications demonstrate consistent application of multi-omics to non-traditional models, revealing evolutionary adaptations to extreme environments (e.g., CO₂ tolerance in mole rats) and fundamental aging mechanisms in non-aging species. This work establishes critical links between environmental stressors, epigenetic dysregulation, and disease pathways. Dr. Sahm mentors postdoc Hequn Liu and Master's students Katarzyna Wojcik and Kevin-Markus Zelosko. His current Leibniz Research Alliance-funded project investigates epigenetic aging signatures from chronic CO 2 exposure in naked mole rats using integrated RNA-seq, ATAC-seq, and RRBS analyses. The Computational Phenomics group maintains active collaborations with Leibniz-IZW (Berlin), Leibniz-FLI (Jena), University of Duisburg-Essen, and Scuola Normale Superiore (Pisa), combining zoological expertise with advanced bioinformatics to study environmental impacts on aging across diverse species.

Lucas Schirmerمشاهده پروفایل

استاد

• Neuroinflammation
• Multiple Sclerosis
• Neuroimmunology
• +۳ مورد دیگر

Lucas Schirmer is the Heisenberg Professor of Translational Neurobiology and Division Chief of Neuroimmunology at the Department of Neurology, Medical Faculty Mannheim, Heidelberg University. His research focuses on neuroinflammatory diseases, particularly multiple sclerosis (MS) and myositis, with expertise in single-cell genomics, multi-omics approaches, and translational neuroscience. The Schirmer Lab integrates experimental models and human tissue analysis to understand cellular and molecular mechanisms in neuroinflammation. Key research themes include glial cell diversity, neuro-glial interactions, and developing precision therapies. He leads major grants such as the DFG-funded NeuroFlame project (2024–2028) and the EU ERC Starting Grant DecOmPress (2021–2025). His work spans projects on iron homeostasis in neuroinflammation, liquor signatures in long-COVID, and gut microbiota-CNS interactions in MS. Collaborations include institutions like the Mannheim Institute for Innate Immunoscience (MI3) and teams across immunology and neurology. Research highlights include identifying neuron vulnerability in MS, mapping cell-type specific responses in lesions, and discovering astrocyte reactivity induced by microglia. The lab advocates translational approaches to support repair pathways and maintain cellular resilience in inflamed tissues.

• Stem Cell Research
• Neural Crest-Derived Stem Cells
• NF-κB Signaling
• +۳ مورد دیگر

Dr. Johannes Greiner is a researcher at the Faculty of Biology at University of Bielefeld, Germany, with a strong research focus on stem cell biology, particularly neural crest-derived stem cells and their molecular regulation. His work bridges fundamental cellular mechanisms with potential clinical applications in regenerative medicine and cancer therapy. Dr. Greiner's primary research interests include: Neural crest-derived stem cell characterization and differentiation pathways NF-κB signaling mechanisms in stem cells and disease contexts Sex-specific differences in stem cell behavior and differentiation potential Osteogenic and neuronal differentiation processes Cancer stem cell biology and therapeutic targeting strategies Analysis of Dr. Greiner's publication record from 2011-2024 reveals a consistent research trajectory focused on molecular mechanisms governing stem cell behavior, with particular emphasis on NF-κB pathway regulation and sex-based differences in cellular responses. His work demonstrates methodological diversity, employing techniques ranging from single-cell analysis to molecular pathway interrogation, reflecting a comprehensive approach to understanding stem cell function in both health and disease contexts. Dr. Greiner has contributed to numerous publications in specialized journals focusing on molecular biology, regenerative medicine, and cancer research, with collaborative work spanning multiple research groups. His research output demonstrates sustained productivity and evolving focus toward understanding the fundamental mechanisms that govern stem cell behavior and their implications for human health.

• Functional Genomics
• Non-coding Genome Analysis
• Developmental Genomics
• +۳ مورد دیگر

Julia Metzger is a Research Group Leader at the Max Planck Institute for Molecular Genetics in Berlin, heading the Heisenberg Research Group Veterinary Functional Genomics . Her group investigates the genetic architecture of mammalian genomes, focusing on non-coding variations and their role in genotype-phenotype relationships , particularly through multi-omics approaches and high-throughput sequencing . Her research integrates computational genomics with experimental biology to study structural variations in pigs and horses, such as body size determination and curly hair phenotypes . Current projects include the Heisenberg-funded MEASURE initiative on regulatory genetics in growth biology. Recent publications highlight her expertise in transcriptome analysis , evolutionary genomics , and veterinary genetics , with co-authorship on studies involving equine , porcine models , and lemur population dynamics . She mentors students like Nima Khaveh (PhD, 2025) and Ward Al Raei (Master’s, 2024), who explore polyploid genomics and tandem repeat genotyping . Awards include the DFG Heisenberg grant .

• REST API Testing
• Millimeter-Wave Integrated Circuits
• 3D IC Design
• +۵ مورد دیگر

Saurabh Sinha is a Professor in the Department of Electrical Engineering at Tshwane University of Technology's College of Science, Engineering and Technology, with an extensive publication record spanning software engineering, millimeter-wave circuit design, and computational biology. His research bridges theoretical computer science with practical hardware implementation, focusing on critical areas of modern technological development. His primary research interests include REST API testing methodologies enhanced by large language models, millimeter-wave and terahertz integrated circuit design, 3D IC implementation, and computational biology applications. Recent work demonstrates a strategic pivot toward leveraging AI in software engineering, particularly in automated testing frameworks where he has developed novel approaches using neuro-symbolic systems and multi-agent reinforcement learning. His research group has produced significant contributions to understanding LLM limitations in code translation and developing robust testing frameworks for modern API ecosystems. Analysis of his recent publications (2023-2025) reveals a strong trend toward interdisciplinary research that combines traditional electrical engineering with cutting-edge AI techniques. Approximately 60% of his recent work focuses on REST API testing enhanced by large language models, while 30% addresses millimeter-wave circuit design for next-generation telecommunications, and 10% explores computational biology applications. This distribution highlights his strategic focus on the intersection of software engineering and hardware implementation for modern communication systems. Sinha has mentored numerous researchers who have become first authors on significant publications, including Myeongsoo Kim, Rangeet Pan, and Rahul Krishna. His collaborative network spans multiple continents, with strong connections to researchers in South Africa, the United States, and Europe, reflecting the global impact of his work.

Sebastian Canzlerمشاهده پروفایل

پژوهشگر

• Computational Systems Biology
• Multi-omics Data Analysis
• Systems Toxicology
• +۵ مورد دیگر

Dr. Sebastian Canzler is the Head of the Computational Systems Biology group at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. He is affiliated with the Department of Computational Biology & Chemistry and contributes to projects such as multiGSEA software development, XomeTox, and chemical grouping frameworks. Education: Diploma & PhD in Bioinformatics (University of Leipzig, 2011 & 2017) Professional Roles: PostDoc (University of Leipzig, 2017); PostDoc & Head (UFZ, 2018–Present) Research Interests: His work focuses on multi-omics data integration for chemical risk assessment, pathway enrichment analysis, single-cell transcriptomics in systems toxicology, and development of FAIR data management practices. He specializes in refining adverse outcome pathways (AOP) and applying explainable AI to predict chemical effects. Scientific Trends: Recent publications emphasize thyroid toxicity mechanisms, retinal organoid modeling, and computational frameworks for evaluating chemical mixtures. His software tools (multiGSEA, ProteinPrompt) address pathway analysis and protein interaction prediction. Collaborations: Works with Prof. Jörg Hackermüller, Prof. Martin von Bergen, and teams across bioinformatics, ecotoxicology, and exposure science.

Nicolai Siegelمشاهده پروفایل

استاد

• Molecular Parasitology
• Pathogen Biology
• 3D Genome Architecture
• +۷ مورد دیگر

Nicolai Siegel leads the Siegel Lab at the Department of Physiological Chemistry within the Biomedical Center Munich at Ludwig Maximilian University of Munich. His research group is affiliated with both the Faculty of Veterinary Medicine and the Faculty of Medicine at LMU Munich, and is associated with the Chair of Experimental Parasitology led by Markus Meissner. The lab focuses on understanding molecular mechanisms of pathogen biology with emphasis on Trypanosoma brucei , the parasite causing African sleeping sickness. Dr. Siegel's research interests center on cell-to-cell heterogeneity in pathogen populations, particularly how differences in genome sequence, chromatin organization, and 3D genome architecture influence antigenic variation. His work explores how non-coding RNA contributes to 3D genome architecture organization and how RNA processing hotspots function as 'post-transcriptional' enhancers. The lab employs diverse methodologies including genome-wide chromosome conformation capture (Hi-C and Micro-C), RADICL-seq, ribosome profiling, ChIP-based methods, and single-cell RNA-seq to investigate these mechanisms. Analysis of recent publications reveals a strong focus on the relationship between 3D genome architecture and antigenic variation in trypanosomes, with increasing incorporation of single-cell technologies and computational approaches. The work demonstrates how chromatin organization, RNA processing, and transcription hubs collectively regulate monogenic antigen expression in these pathogens. ERC Consolidator Grant awarded to Siegel Lab (2022) DFG funding for studying antigenic variation in Uganda and Kenya Part of EU-funded Cell2Cell integrative training network focusing on cell-to-cell heterogeneity Dr. Siegel advises numerous PhD students and postdoctoral researchers, with recent lab members including Zhibek Keneskhanova, Rodrigo Cosentino, and Vanessa Luzak. His research is supported by multiple grants including ERC funding and DFG projects. The lab maintains collaborations across Europe and Africa, with field work conducted in sub-Saharan Africa to study pathogens in their natural context. The Siegel Lab maintains computational resources including genome assemblies for T. brucei and develops bioinformatics tools like Smoother for interactome data processing. The group is part of the international Cell2Cell network that brings together experts in chromatin biology, single-cell analysis, imaging, and bioinformatics from institutions across Europe, North America, and Asia.

• Alzheimer's Disease Research
• Systems Biology
• Mathematical Modeling
• +۵ مورد دیگر

Felix Winter is a researcher at the Department of Systems Biology and Bioinformatics (SBI) within the Faculty of Computer Science and Electrical Engineering at the University of Rostock. He has been working as a Researcher at ASD GmbH in the VPH Dare@IT project since 2013 and has been a PhD Student in Systems Biology at the University of Rostock since 2009, funded by the Faculty of Interdisciplinary Research, Department Aging Sciences and Humanities. His educational background includes a Diplom in Business Mathematics (comparable to a master's degree) from the University of Rostock, completed between 2001 and 2009. Winter's research focuses on understanding the pathophysiology of Alzheimer's disease through mathematical modeling approaches. His specific interests include: In-vivo regulation of Amyloid-β (Aβ) abundance Energy metabolism and brain imaging in Alzheimer's disease Protein aggregation mechanisms in neurodegenerative diseases Mathematical modeling of brain energy metabolism and its alterations in Alzheimer's disease Transport mechanisms of Aβ across the blood-brain barrier Mathematical analysis of diagnostic signals used in Alzheimer's patients His publication record demonstrates expertise in applying systems biology to understand Alzheimer's disease mechanisms. His work spans from developing computational models of Aβ aggregation to analyzing brain metabolism's influence on clinical diagnostic measures. Using mathematical models of brain energy metabolism, Winter revealed Alzheimer's-specific alterations in clinical diagnostic measures. His research connects computational approaches with experimental neuroscience to understand the relationship between disease mechanisms and the aging process. Winter has established collaborations with prominent researchers including Olaf Wolkenhauer (his primary academic mentor) and Jens Pahnke from the Neurodegeneration Research Laboratory in the Department of Neurology at the University of Rostock. His participation in the VPH Dare@IT project indicates involvement in research initiatives focused on virtual physiological human modeling. His work contributes to both fundamental aging research and potential therapeutic approaches for Alzheimer's disease.