جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence in Surgery
• Clinical Decision Support Systems
• Trauma Outcomes Research
• +۳ مورد دیگر

Christopher Tignanelli is an Associate Professor at the University of Minnesota Medical School , affiliated with the Division of Critical Care & Acute Care Surgery . He serves as Co-Director of Clinical Quality, Outcomes, Discovery and Evaluation (CQODE) , Scientific Co-Director of the Program for Clinical, Center for Learning Health System Sciences , and Associate Dean for Data Science . Educational background includes MD, MS in Clinical Research , and MBA in Healthcare Innovation Specializes in Artificial Intelligence in Surgery , Clinical Decision Support Systems , and Trauma Outcomes Research Key research themes: Machine Learning for Readmission Prediction , Venous Thromboembolism Prophylaxis , Post-COVID-19 Condition Analysis His work integrates AI/ML with clinical outcomes across trauma care and pandemic medicine , focusing on real-world evidence and health informatics . Notable contributions include multicenter clinical trial leadership and statewide trauma collaborative innovations . Scientific Awards : American Association for the Surgery of Trauma Clinical Protocol Development Award MBA in Healthcare Innovation MS in Clinical Research MD Degree Statewide Trauma Collaborative Process Measure Innovation Recognition Multicenter Trial Leadership Award

• Bioinformatics
• Biostatistics
• Infectious Diseases
• +۶ مورد دیگر

Yong Kong is a Senior Research Scientist in the Department of Biostatistics at the Yale School of Public Health , affiliated with the W.M. Keck Foundation Biotechnology Laboratory and the NIDA Neuroproteomics Center . His research bridges computational biology, infectious disease modeling, and genomic data science with applications to public health. PhD in Computational Biology (Washington University School of Medicine, 1997) BA in Biomedical Engineering/Computer Science (Tsinghua University) MS in Neurobiology (Shanghai Institute of Physiology, Chinese Academy of Sciences) Research Interests: Host-pathogen interaction profiling using multidimensional data Microbiome dynamics in respiratory and gastrointestinal infections Statistical methods for genomic sequence analysis Computational modeling of inflammatory and immune response pathways Public health applications of combinatorics and run statistics Recent Publication Trends: Focus on bat virus immune evasion mechanisms, multivariate run statistics, and microbiome-resistome interactions across veterinary and human health contexts. Collaborates extensively with immunologists (A. Iwasaki, M. Pettigrew) and infectious disease specialists. Labs & Collaborations: Core member of the Keck Biotechnology Laboratory at Yale, contributing to bioinformatics infrastructure and interdisciplinary research initiatives.

• Biostatistics
• Bioinformatics
• High-dimensional data analysis
• +۷ مورد دیگر

Tao Wang is an Assistant Professor Adjunct in the Department of Biostatistics at Yale School of Public Health and a tenure-track Associate Professor and Principal Investigator in the SJTU-Yale Joint Center for Biostatistics and Data Science at Shanghai Jiao Tong University. His work focuses on statistical methods for high-dimensional biomedical data, especially dimension reduction, microbiome analysis, and integrative genomic modeling. Education: PhD in Statistics, Hong Kong Baptist University, 2013 MS, East China Normal University, 2010 Research Interests: Dr. Wang develops statistical and computational techniques to tackle complex, high-dimensional data arising from modern biotechnologies. His methodological portfolio includes adaptive independence tests for microbiome community data, penalized prediction models for sequencing counts, and counting-process-based dimension reduction for censored survival outcomes. He also works on Bayesian tree-structured models linking dietary nutrients to gut microorganisms and joint estimation of Gaussian graphical models over spatial and temporal domains. These interests sit at the intersection of biostatistics, bioinformatics, machine learning, and epidemiology , with applications spanning the human microbiome, epigenomics, and large-scale cohort studies. Publications at a Glance: Across six major papers (2015-2019) in Biometrics and Biometrika , Wang has consistently advanced methodology for high-dimensional count, compositional, and censored data. Themes include adaptive testing, predictive modeling, dimension reduction, and network estimation, often motivated by collaborative projects in genomics and microbiome science. Honours: Elected Member, International Statistical Institute (2020) Collaboration & Advising: He maintains an active collaboration with Yale’s Dr. Hongyu Zhao, co-authoring all showcased publications. No formal advisees are listed in the provided material. Laboratories & Teams: He leads research activities within the SJTU-Yale Joint Center for Biostatistics and Data Science, integrating resources from both Shanghai Jiao Tong University and Yale to advance data-intensive biomedical science.

Genevieve Wojcikمشاهده پروفایل

دانشیار

• Genetic Epidemiology
• Diverse Populations
• Infectious Diseases
• +۸ مورد دیگر

Genevieve Wojcik is an Associate Professor in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health , where she leads the RAGE Lab (Research on Ancestry in Genetic Epidemiology). Her work focuses on improving genetic and genomic methods for diverse and admixed populations to address health inequities. Her research interests include: Genetic epidemiology Polygenic risk scores Host-pathogen dynamics Multi-ethnic GWAS Population genetics Health equity Recent research trends emphasize: Developing frameworks for population descriptors in genomics Understanding gene-environment interactions in Latino populations Advancing HBV sequence analysis tools Promoting precision health through diverse ancestry studies

• Genetics
• Microbiology
• Evolutionary Biology
• +۴ مورد دیگر

Fang Wang is a Research Fellow at the School of Medical Sciences , University of Sydney , and a member of the Charles Perkins Centre . Her research integrates microbial genetics, evolutionary biology, and bioinformatics to analyze the human oral microbiome and its role in childhood oral diseases. PhD in Genetics, University of Cambridge (UK) Postdoctoral work on molecular evolution of Amoebozoa, Spelman College (US) Her current work leverages a longitudinal Australian twin cohort with oral metagenomic data to investigate how host and environmental factors influence microbiome dynamics. Key research questions include the evolution of oral microbial communities in childhood, early prediction of dental caries via microbial features, and environmental impacts on oral health. Recent publications focus on Amoebozoa gene trafficking, oral resistome development, and deep learning applications in stochastic analysis. She has received the FMH Researcher Accelerator Scheme 2025 Grant for her research. Member, Society for Molecular Biology and Evolution

• Environmental DNA
• Diversity monitoring
• Terrestrial ecology
• +۵ مورد دیگر

Dr. Andjin Siegenthaler is a researcher at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), specializing in environmental DNA (eDNA) applications for biodiversity monitoring. Their work integrates remote sensing technologies with molecular tools to advance ecosystem analysis across terrestrial and marine environments. Affiliation: Department of Natural Resources, University of Twente Key methodologies: eDNA analysis, remote sensing, big data analytics Research focuses on Earth observation techniques for environmental diversity profiling, particularly through next-generation molecular approaches. Current work explores satellite-based biodiversity prediction models and spatial variation analysis in forest ecosystems. Their publication record demonstrates expertise in environmental DNA, soil microbiology, and hyperspectral remote sensing technologies. Collaborative projects involve international partners across Europe, with emphasis on temperate forest biodiversity and soil health assessment. Active contributions to UN Sustainable Development Goals include environmental monitoring frameworks and ecological data integration. Professional activities span peer-review for Ecological Indicators and oral presentations at scientific conferences.

Terrence Fureyمشاهده پروفایل

استاد

• Epigenetics
• Gene Regulation
• Inflammatory Bowel Diseases (IBD)
• +۴ مورد دیگر

Dr. Terrence (Terry) Furey is a Professor in the Department of Genetics and Biology at the UNC School of Medicine. His research focuses on gene regulatory processes, particularly epigenetically controlled mechanisms, and their role in complex diseases like inflammatory bowel diseases (IBD). The Furey Lab specializes in computational analysis of genome-wide open chromatin, histone modifications, miRNA, and gene transcription data from high-throughput sequencing experiments. Key research areas: Epigenetics, Chromatin Biology, IBD Pathogenesis, Computational Genomics, Microbiome Interactions Specialized methodologies: Development of statistical and computational tools for genomic data analysis Research highlights include investigating genetic and epigenetic contributors to IBD through collaborations with Dr. Shehzad Sheikh, particularly analyzing chromatin reprogramming, miRNA expression, and microbial composition in both IL-10 knockout models and human intestinal tissues. The lab has identified distinct molecular signatures of Crohn's disease associated with clinical phenotypes. Article trends demonstrate expertise spanning Chromatin accessibility analysis in disease states MicroRNA biomarker discovery in IBD Computational tool development (ROCCO, DeFCoM, GSAASeqSP) Multi-omics integration in complex phenotypes Environmental-genetic interaction studies Translational IBD research Dr. Furey actively collaborates with researchers across the Center for Gastrointestinal Biology and Disease (CGIBD), including Drs. Sartor, Sheikh, and Rusyn. His work bridges clinical/translational research with microbiome studies , focusing on how epigenetic landscape alterations contribute to disease progression.

Amanda Zieglerمشاهده پروفایل

استادیار

• Gastroenterology
• Intestinal Barrier Repair
• Enteric Nervous System
• +۴ مورد دیگر

Amanda Ziegler, DVM, PhD is an Assistant Research Professor in the Department of Clinical Sciences at North Carolina State University. She leads the Comparative Gastroenterology Lab, focusing on intestinal barrier repair mechanisms, particularly in neonatal and juvenile large animal models. Her work bridges veterinary medicine, gastroenterology, and developmental biology to understand intestinal wound healing processes. Dr. Ziegler's primary research interests center on gastrointestinal biology and disease, with specific focus on: Intestinal barrier repair and restitution mechanisms Enteric nervous system development and function Neonatal intestinal development and repair Large animal models (particularly porcine) for translational research Comparative gastroenterology across species Intestinal wound healing following ischemic injury Her recent publications demonstrate a strong emphasis on molecular mechanisms of intestinal repair, particularly examining the role of enteric glial cells in regulating epithelial restitution. She has pioneered the use of single-cell transcriptomics to compare pig and human epithelial phenotypes, identifying a "restitution/hybrid EMT phenotype." Her work increasingly incorporates microbiome research, prebiotic interventions, and comparative approaches across species to understand fundamental mechanisms of intestinal healing. Dr. Ziegler has received notable recognition including a K01 award and the CGIBD Pilot and Feasibility Award in 2018. Her research has been supported by grants focused on understanding intestinal barrier repair in early life. As principal investigator of the Comparative Gastroenterology Lab, Dr. Ziegler leads research investigating how the developing enteric glial cell network regulates intestinal barrier repair in postnatal life. Her lab employs innovative large animal models to study intestinal wound healing with translational applications for neonatal care in both veterinary and human medicine.

Ming-Zhi Zhangمشاهده پروفایل

استاد

• Nephrology
• Endocrinology
• Immunology
• +۳ مورد دیگر

Ming-Zhi Zhang is a Professor of Medicine at Vanderbilt University Medical Center, affiliated with Monroe Carell Jr. Children's Hospital. His research bridges nephrology, endocrinology, and microbiology. Research Interests: He investigates hormonal regulation of renal physiology, focusing on COX-2 and 11βHSD2 interactions in kidney pathophysiology. His work connects colorectal cancer with glucocorticoid metabolism, while pioneering immunohistochemistry techniques in kidney research via tissue microarrays. Recent Publications highlight virome diversity in ticks, mechanisms of kidney fibrosis, and metabolic risk factors for hypertension. His lab employs genetically modified mouse models and genomic tools to explore renal dopaminergic-renin-angiotensin crosstalk. Collaborations: Engaged with the Tick Genome and Microbiome Consortium (TIGMIC), Vanderbilt Institute for Infection, Immunology and Inflammation, and labnodes.vanderbilt.edu for tissue microarray analysis.

Antonio Ribeiroمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Computational Biology
• DNA Sequence Analysis
• +۳ مورد دیگر

Dr. Antonio Ribeiro serves as a Bioinformatician at the Centre for Genome-Enabled Biology and Medicine (CGEBM) within the School of Medicine, Medical Sciences and Nutrition at the University of Aberdeen. He joined the institution in August 2015, bringing extensive expertise in DNA sequence alignment, SNP calling, and next-generation sequencing data analysis. His technical proficiency spans Bash scripting, Java, and Perl for developing and optimizing bioinformatics pipelines. Dr. Ribeiro holds an MSc in Computational and Systems Biology from FIOCRUZ-RJ in Brazil, along with specializations in Computer Networks (PUC-Rio) and Information Systems Development (NCE-UFRJ). Prior to his academic career, he accumulated over 20 years of industry experience as a Customer Service Engineer with companies including Nokia-Siemens Networks and Xerox. His research focuses on advanced bioinformatics applications in microbial genomics, molecular epidemiology, and NGS data analysis. Dr. Ribeiro's work bridges computational methods with medical and biological applications, particularly in bacterial pathogen analysis, antimicrobial resistance studies, and genomic variation detection. His technical background enables sophisticated analysis of complex genomic datasets across diverse biological contexts. Analysis of his publication history reveals a strong trajectory in computational genomics with increasing focus on medical applications. His recent work (2023-2025) centers on molecular epidemiology of bacterial bloodstream infections, antimicrobial resistance mechanisms, and clinical applications of genomic analysis. Earlier publications (2012-2016) demonstrate foundational work in NGS data processing, SNP validation, and bioinformatics tool development. Dr. Ribeiro's technical expertise in processing and analyzing NGS data using both third-party open-source tools and custom scripts positions him at the intersection of computational science and biological research. His work supports critical medical research through advanced genomic analysis capabilities, contributing to understanding of bacterial pathogens, antimicrobial resistance, and genomic variation.

Stuart Bearhopمشاهده پروفایل

استاد

• Animal Ecology
• Wildlife Conservation
• Seabird Ecology
• +۵ مورد دیگر

Stuart Bearhop is a Professor of Animal Ecology at the University of Exeter's Centre for Ecology and Conservation in Cornwall. With a PhD in Evolutionary and Environmental Biology, he has established himself as a leading researcher in animal ecology, particularly focusing on seabirds, migration patterns, and human-wildlife conflicts. His extensive publication record includes 273 publications with over 125,814 reads and 30,009 citations, demonstrating significant impact in his field. Professor Bearhop's research spans multiple areas of ecology and conservation biology. He specializes in studying the movement ecology of migratory birds, particularly seabirds and geese, using advanced tracking technologies and stable isotope analysis. His work investigates how environmental changes, human activities, and management strategies affect wildlife populations and their behaviors. Notably, he has developed methodological tools like the "cosimmr" and "simmr" R packages for stable isotope mixing models, which have advanced dietary analysis in ecological research. His recent publications (2023-2025) reveal a continued focus on critical conservation issues including human-wildlife conflict management, impacts of climate change on migratory patterns, and the development of innovative analytical tools. The research demonstrates strong international collaboration and addresses pressing conservation challenges through both empirical field studies and methodological advancements. Professor of Animal Ecology at University of Exeter's Centre for Ecology and Conservation Expertise in wildlife ecology, conservation biology, and stable isotope analysis Extensive publication record with significant citation impact Active research in migratory bird ecology and human-wildlife conflict Professor Bearhop's research group likely provides opportunities for students interested in animal ecology, conservation, and methodological development. His work bridges fundamental ecological research with practical conservation applications, addressing real-world challenges in wildlife management.

Claus O. Wilkeمشاهده پروفایل

استاد

• Computational Biology
• Molecular Evolution
• Protein Biochemistry
• +۶ مورد دیگر

Claus O. Wilke is a Professor and holds the Jane and Roland Blumberg Centennial Professorship in Molecular Evolution at The University of Texas at Austin, with appointments in the Department of Integrative Biology, Statistics and Data Sciences, and Interdisciplinary Life Sciences Graduate Programs. Wilke earned his PhD in Theoretical Physics from Ruhr-University Bochum, Germany, and completed postdoctoral training with Chris Adami at Caltech. His research focuses on computational evolutionary biology, bioinformatics, and biostatistics, with particular emphasis on molecular evolution (virus evolution and protein evolution biophysics), systems biology, and bacterial physiology. His work bridges theoretical approaches with biological applications through frequent collaborations with experimental groups. Wilke has made significant contributions to data visualization through his R packages including cowplot, ggridges, and ggtext, and as a core contributor to ggplot2. His 2019 book Fundamentals of Data Visualization has become a standard reference in the field, providing comprehensive guidance on effective visualization principles and techniques. Fellow, American Association for the Advancement of Science (AAAS) (2023) Fellow, American Physical Society (APS), Division of Biological Physics (2019) Kavli Frontiers of Science Fellow (2013) Leading Texas Innovator by The Academy of Medicine, Engineering, and Science of Texas (TAMEST) (2011) Teaching Excellence Award, College of Natural Sciences, UT Austin (2010) His nearly 200 publications demonstrate consistent productivity across computational biology, molecular evolution, and data visualization. Wilke leads The Wilke Lab at UT Austin, which provides research opportunities for graduate students and postdoctoral researchers interested in computational approaches to evolutionary questions. Beyond research, he maintains an active blog discussing data visualization techniques, R programming, and scientific computing best practices.

Claudia Solís-Lemusمشاهده پروفایل

استادیار

• Statistical Modeling
• Phylogenetics
• Microbiome Analysis
• +۳ مورد دیگر

Claudia Solís-Lemus is an Assistant Professor in the Department of Plant Pathology at the University of Wisconsin-Madison, where she develops statistical and machine learning methods to solve complex biological problems. Her work bridges computational statistics with plant pathology and evolutionary biology, focusing on network-based approaches to genomic and microbiome data. Educational background: PhD in Statistics, University of Wisconsin–Madison Her research centers on phylogenetic network inference , microbiome analysis , and high-dimensional statistical modeling . She creates open-source tools like CMiNet and MiNAA to empower biologists with robust network analysis capabilities. Her lab tackles challenges in biodiversity research, agricultural disease prediction, and microbial ecology through innovative computational frameworks that handle massive biological datasets. Analysis of her 2024-2025 publications reveals a cohesive focus on scalable network inference methods across phylogenetics and microbiome studies. She integrates Bayesian statistics, regularization techniques (e.g., spike-and-slab LASSO), and high-performance computing to address data complexity. Her work consistently emphasizes practical software implementation (R packages, Shiny apps, Julia tools) for real-world biological applications including potato disease prediction, hornwort evolution, and freshwater ecosystem dynamics. Scientific recognition: NSF CAREER Award (2022) for "Towards Scalable and Robust Inference of Phylogenetic Networks" Dr. Solís-Lemus leads an interdisciplinary research group at the Wisconsin Institute for Discovery, securing competitive grants to advance phylogenetic network methodology. Her CAREER project combines algorithmic innovation with educational outreach to train next-generation computational biologists. Current efforts focus on improving network inference for polyploid genomes and developing consensus methods for microbiome data integration across diverse environmental conditions. The Solís-Lemus Lab operates within UW-Madison's Wisconsin Institute for Discovery ecosystem, fostering collaborations between statisticians, computer scientists, and biologists. Her team actively develops user-friendly software to lower computational barriers for life scientists studying evolutionary processes and microbial communities.

Jake Quallsمشاهده پروفایل

دانشیار

• Bioinformatics
• Artificial Intelligence
• Medical Imaging Analysis
• +۴ مورد دیگر

Dr. Jake Qualls is an Associate Professor of Bioinformatics at the Computer Science & Mathematics Department, Arkansas State University, within the Beck College of Sciences & Mathematics. His research bridges computational methods with biomedical applications. Research Interests Dr. Qualls specializes in Bioinformatics , Artificial Intelligence , and Medical Imaging , with a focus on improving diagnostic accuracy and addressing learning disabilities through computational approaches. His work spans AI-driven font optimization for dyslexia Lung cancer detection via CT scans Emergency room patient classification using X-rays Machine learning in genomic analysis Publications Dr. Qualls' recent publications (2020-2024) emphasize Transfer Learning , 3D Convolution , and U-Net Architectures applied to medical imaging and genomics, particularly for lung/renal cancer diagnostics, Alzheimer's disease, and dyslexia interventions.

Qin Liuمشاهده پروفایل

استاد

• Biostatistics
• Cancer Research
• Immunotherapy
• +۵ مورد دیگر

Qin Liu, Ph.D., M.D., is a Professor in the Molecular and Cellular Oncogenesis Program at The Wistar Institute's Ellen and Ronald Caplan Cancer Center. She leads the Biostatistics Unit, providing statistical expertise for translational and pre-clinical cancer research across the institution. Dr. Liu earned her medical degree and master's in health statistics at Shanxi Medical University in China, followed by a Ph.D. in biostatistics from Shanghai Medical University in 1998. She completed a postdoctoral fellowship in biostatistics and epidemiology at the University of Massachusetts, where she also earned a second master's degree in public health and epidemiology. She served as assistant professor in the Department of Cancer Biology at UMMS starting in 2005, then joined the Biostatistical Research Group in 2007. She joined The Wistar Institute in 2011 as an associate professor and was promoted to professor in 2017. Her research applies biostatistics to multiple areas including basic cancer research, clinical trials of cancer immunotherapy, infectious diseases, behavioral and educational intervention research, and health care outcomes. The Biostatistics Unit under her supervision provides statistical support to biological laboratories at The Wistar Institute, including large data management, experiment design, statistical data analysis, and manuscript preparation. Analysis of Dr. Liu's recent publications reveals a strong focus on statistical approaches to complex biological problems, particularly in cancer immunology, HIV research, and biomarker discovery. Her work often involves collaborations across multiple disciplines, combining biostatistical expertise with laboratory and clinical research. Dr. Liu has secured significant funding for collaborative projects, including three NIH P01 Program Project grants on molecular therapies for prostate cancer, melanoma, and EBV-related cancers. Her statistical expertise has contributed to numerous published papers and funded grant proposals for clinical and basic science investigators. The Biostatistics Unit she supervises provides in-house expertise to accommodate the growth in translational cancer research at Wistar. Her team includes scientific programmers and statistical analysts who work closely with laboratory researchers to design experiments and analyze complex biological data.