جست‌وجوی استاد و پژوهشگر

Martin Peiferمشاهده پروفایل

استاد

• Computational Cancer Genomics
• Tumor Evolution
• Genome Instability
• +۵ مورد دیگر

Professor Martin Peifer is a computational cancer genomics researcher at the University of Cologne, where he leads the Department of Translational Genomics. He serves as Principal Investigator of the Peifer Lab, which focuses on developing computational methods to analyze cancer genome sequencing data. His work is deeply integrated with the Center for Data and Simulation Science and he is an active member of the International Cancer Genome Consortium and the Pan-Cancer Analysis of Whole Genomes project. Peifer's research interests center on computational approaches to understanding cancer biology, with particular emphasis on tumor evolution and genome instability mechanisms. His lab develops methods to analyze somatic genome alterations including point mutations, copy number changes, and rearrangements. They also create computational tools for integrative genome analyses, tumor evolution reconstruction, and single-cell sequencing data analysis (both RNA and DNA). His interdisciplinary team applies high-performance computing and machine learning to interpret complex cancer sequencing data, aiming to better understand tumorigenesis, clonal evolution, and therapy resistance. Analysis of Peifer's extensive publication record reveals a strong focus on neuroblastoma and lung cancer genomics, with particular attention to tumor evolution patterns and genomic instability mechanisms. His work spans multiple cancer types but maintains consistent themes of computational methodology development and application to understand cancer progression and treatment resistance. The publications demonstrate increasing sophistication in analyzing intra-tumor heterogeneity and clonal dynamics over time. Peifer leads an active research group including postdoctoral fellows (Joel Kaufmann, Dr. Stephanie Pabel, Agnieszka Rumińska) and PhD students (Magdalena Seiffert, Justinas Valiulis). His lab is involved in the Collaborative Research Center 1399 focused on Mechanisms of Drug Sensitivity and Resistance in Small Cell Lung Cancer, indicating significant grant funding and collaborative research efforts. The Peifer Lab operates at the intersection of computational biology and cancer research, maintaining an interdisciplinary approach that combines bioinformatics, machine learning, and high-performance computing to address complex questions in cancer genomics. Their work has significant implications for understanding cancer evolution and developing more effective treatment strategies.

• Neuro-oncology
• Neuropathology
• Glioblastoma
• +۳ مورد دیگر

Professor Patrick Harter is a faculty member at the Institute of Neuropathology, Ludwig Maximilian University of Munich (LMU), where he leads research in neuro-oncology and molecular diagnostics of CNS tumors. His work focuses on glioblastoma, meningioma, and brain metastasis, with emphasis on epigenetic mechanisms like DNA methylation and metabolic adaptations in the tumor microenvironment. Research interests span: Molecular classification of brain tumors using DNA methylation profiling Therapeutic targeting of BRAF/MEK and PI3K/Akt/mTOR pathways Role of hypoxia and metabolic plasticity in treatment resistance Liquid biopsy development for non-invasive tumor monitoring His recent publications demonstrate a strong trend toward integrating epigenetic, metabolic, and immunotherapeutic approaches. Articles frequently explore: Novel biomarkers for tumor grading and prognosis Mechanisms of therapy resistance in gliomas Impact of tumor microenvironment on metastasis

• Plant Biochemistry
• Specialized Metabolism
• Solanaceae Family
• +۴ مورد دیگر

Cornelius Barry is an Associate Professor in the Department of Horticulture at Michigan State University, with affiliations to the Plant Breeding, Genetics and Biotechnology program, AgBioResearch, and the Molecular Plant Sciences Graduate Program. He joined MSU in July 2007 with a 75% research and 25% teaching appointment. Education: PhD and BSc from the University of Nottingham and University College of Wales Current roles: Director of NSF REU Site: Plant Genomics @ MSU His research focuses on the evolution of biochemical diversity within the Solanaceae family , particularly specialized metabolites like terpenoids, flavonoids, and alkaloids. He investigates their roles in plant defense, pollinator attraction, and human applications through genomics, metabolite profiling, and synthetic biology. Recent publications show expertise in alkaloid biosynthesis , trichome chemistry , and metabolic pathway engineering . Key collaborations include teams at Boyce Thompson Institute, Texas A&M, and University of Nottingham. He advises graduate students in Genetics , Biochemistry & Molecular Biology , and Molecular Plant Sciences programs.

Mandi de Mestreمشاهده پروفایل

استاد

• Reproductive Biology
• Placental Development
• Equine Medicine
• +۵ مورد دیگر

Dr. Mandi de Mestre is a Professor in the Department of Biomedical Sciences at Cornell University's College of Veterinary Medicine. As Director of the Baker Institute for Animal Health and holder of the Dorothy Havemeyer McConville Professorship of Equine Medicine, her research focuses on equine pregnancy biology, placental development, and fetal health. Director, Baker Institute for Animal Health Dorothy Havemeyer McConville Professor of Equine Medicine Affiliated with Cornell's College of Veterinary Medicine Her laboratory investigates: Molecular mechanisms of placental development Genetic causes of early pregnancy loss Congenital musculoskeletal disorders in Thoroughbreds Non-invasive diagnostics for fetal health Comparative studies linking equine and human pregnancy pathologies Recent research trends show strong emphasis on genomic stability, immune interactions during implantation, and epidemiological factors affecting equine pregnancies. Collaborations with institutions like the University of Nottingham and Royal Veterinary College UK highlight her interdisciplinary approach. The Equine Pregnancy Laboratory employs molecular biology, immunology, and genetics to address critical gaps in placental biology, with implications for both veterinary and human medicine.

Leif Anderssonمشاهده پروفایل

استاد

• Genetics and Genomics
• Evolutionary Biology
• Comparative Genomics
• +۳ مورد دیگر

Leif Andersson is a Professor at Uppsala University's Department of Medical Biochemistry and Microbiology, leading a research group focused on functional genomics in domestic animals and fish. His work bridges genetics, ecology, and evolutionary biology to explore phenotypic variation and adaptation. His research includes comparative genomics of domesticated species, identifying mutations linked to traits like horse gaits , chicken comb morphology , and herring ecological adaptation . Recent studies highlight genetic mechanisms in species such as corn snakes , Grey horses , and Darwin's finches , emphasizing environmental interactions and molecular pathways. Key article trends include supergenes in herring adaptation, RNA-binding proteins in cancer and development, and mutation-discovery in domesticated animals. His group's work spans genetic variation , ecological pressures , and evolutionary genetics . Students in his group include Arianna Cocco Ryan Joseph Daniels Jake Goodall Zheng Li Cheng Ma Giulia Maestri Fahime Mohamadnejad Sangdehi Mats Pettersson Matteo Sebastianelli Leyi Su Dandan Wang His contact details include the email Leif.Andersson@imbim.uu.se and phone number 070-425 02 33 , with an office at BMC, Husargatan 3, Uppsala.

David R. Raleighمشاهده پروفایل

استادیار

• Neuro-oncology
• Radiation Oncology
• Molecular Mechanisms of Brain Tumors
• +۳ مورد دیگر

David R. Raleigh, MD, PhD, is an Assistant Professor in the Departments of Radiation Oncology and Neurological Surgery at the University of California San Francisco (UCSF). He serves as a Principal Investigator at the Brain Tumor Center and Director of the Preclinical Therapeutics Core. Education: BA in Molecular and Cell Biology and Cognitive Science (UC Berkeley, 2004), MD and PhD in Pathology (University of Chicago, 2012), Residency in Radiation Oncology (UCSF, 2017) His research focuses on the molecular mechanisms of brain tumor growth, particularly meningiomas, integrating developmental biology with oncology to identify novel treatments. Methodologies include biochemistry, mouse genetics, genomics, and pharmacology. Dr. Raleigh's recent publications highlight molecular classification of meningiomas, genomics, and targeted therapies. Awards include Phi Beta Kappa, multiple travel grants, and the Robert and Ruth Halperin Endowed Chair in Meningioma Research.

• Skeletal Muscle Physiology
• Ribosome Biogenesis
• Transcriptional Regulation
• +۴ مورد دیگر

Gustavo Alberto Nader is a Professor of Kinesiology at The Pennsylvania State University , holding the Dorothy Foher and J. Lloyd Huck Chair in Molecular, Cellular and Integrative Physiology. His research focuses on skeletal muscle growth control , ribosome biogenesis , and transcriptional/epigenetic regulation in health and disease contexts. Affiliated with the Huck Institutes of the Life Sciences and College of Health and Human Development Principal Investigator on NIH-funded projects examining ribosomal control of muscle mass Research Interests span molecular mechanisms of muscle adaptation to exercise, cancer cachexia, chronic disease impacts on muscle, and cross-species Wnt signaling regulation by CO₂ levels. Key methodologies include human/animal/cell models, ribosomal analysis, and epigenetic profiling. Publication Trends show sustained focus on: Ribosome biogenesis in muscle hypertrophy (2012–2025) Cancer-induced muscle wasting mechanisms (2015–2024) CO₂/Wnt pathway interactions (2015–2019) Exercise-induced transcriptional responses (2001–2016) Scientific Awards include the Huck Chair, while his Grants & Collaborations involve NIH-funded studies on transcriptional/epigenetic mechanisms (2019–2026) with cross-disciplinary teams in physiology, oncology, and respiratory medicine.

Annette Byrneمشاهده پروفایل

استاد

• Precision Medicine
• Molecular Imaging
• Angiogenesis
• +۷ مورد دیگر

Professor Annette Byrne is a leading academic at RCSI University of Medicine and Health Sciences , where she serves as Professor of Physiology and Head of the Precision Cancer Medicine (PCM) Group. She has held this position since 2019 after progressing through roles as Lecturer (2008), Senior Lecturer (2013), and Associate Professor (2017). Her research focuses on precision medicine approaches for colorectal and brain cancers , integrating multi-modality molecular imaging , Next Generation Sequencing , and patient-derived xenograft models . PhD in Cell Biology (University of York, 1999) John Kerner Fellowship in Gynaecologic Oncology (UCSF, 1999-2001) Scientist at Pharmacyclics Inc. (2001-2003) Senior Scientist at Angion Biomedica Corp. (2003-2005) Principal Investigator at UCD Conway Institute (2005-2008) Her research interest lies in precision cancer medicine , particularly elucidating predictive biomarkers (genomic, transcriptomic, proteomic) and identifying novel therapeutic targets . Key methodologies include radiomics , fluorescence-guided surgery , and systems modeling of apoptosis pathways. She has pioneered Ireland's first Tumour Xenograft Facility and Translational In Vivo Imaging Centre . Recent publications highlight her work on cross-species radiomics , cell-free DNA analysis , and glioblastoma microenvironment subtyping . Her Marie Curie networks (Gliotrain, Glioresolve) and COLOSSUS project have trained 25+ PhD researchers in brain cancer therapeutics. Over €45M in national/international grants Member of Royal Irish Academy (2025) Highly cited in Cancer Discovery , Annals of Oncology , and Nature journals She supervises multiple PhD candidates and leads the RCSI Precision Cancer Medicine Group , which utilizes computational approaches and molecular imaging to improve cancer treatment outcomes. Her GLIORESOLVE and EDIReX projects focus on tumor microenvironment manipulation and distributed PDX infrastructure.

Jie Pengمشاهده پروفایل

استاد

• Graphical Models
• High Dimensional Inference
• Functional Data Analysis
• +۴ مورد دیگر

Jie Peng, Ph.D., is a Professor and Vice-Chair for Graduate Affairs in the Department of Statistics at the University of California, Davis. Her research focuses on statistical methodologies with applications in genomics, neuroimaging, and functional data analysis. She holds a Ph.D. from Stanford University and is actively involved in advancing statistical theory and its practical implementations in biomedical and computational sciences. Education Ph.D. in Statistics, Stanford University Research Interests Dr. Peng’s work spans several key areas including graphical models, high-dimensional inference, and neuroimaging analysis. She develops innovative statistical tools for analyzing complex biological data, such as tumor genomics and brain connectivity patterns derived from diffusion MRI. Her research emphasizes the interplay between theoretical statistics and real-world applications in healthcare and precision medicine. Professional Contributions She serves as an Associate Editor for the Journal of Computational and Graphical Statistics and has contributed to numerous high-impact publications. Her methods have been applied to identify biomarkers in ovarian cancer and to study brain lateralization using Human Connectome Project (HCP) data. Dr. Peng also leads efforts in developing computational frameworks for spatial transcriptomics and dynamic network modeling.

Hao Chenمشاهده پروفایل

دانشیار

• Anomaly/signal detection for streaming data
• Graph-based methods
• Two-sample test for high-dimensional and non-Euclidean data
• +۷ مورد دیگر

Hao Chen, Ph.D. is an Associate Professor in the Department of Statistics at the University of California, Davis. His research focuses on statistical methodology for high-dimensional and non-Euclidean data, including anomaly detection, graph-based methods, and change-point analysis. He also explores AI security, multimodal models, and geospatial applications. His work bridges statistical theory and practical machine learning challenges. Education: Ph.D., Graduate Group in Biostatistics, Stanford University Research Interests: Dr. Chen’s expertise spans statistical methods for streaming data, categorical data analysis, and allele-specific copy number variation. He has pioneered work in detecting signals in complex datasets and developing robust AI systems. His recent focus includes mitigating modality interference in LLMs, enhancing model safety via guardrails, and advancing geospatial AI through projects like GeoLM. Publications: His recent work addresses cutting-edge topics such as multimodal model vulnerabilities, unlearning algorithms, and clinical radiology applications. Key themes include improving model robustness, ethical AI design, and interdisciplinary data integration. Labs/Teams: Engages in collaborative projects at UC Davis, though specific lab names are not listed in the provided information.

• Autism Genetics
• Genetic Architecture
• Copy Number Variants
• +۵ مورد دیگر

Lauren Weiss, PhD is a Professor of Psychiatry at the University of California, San Francisco (UCSF) School of Medicine and a faculty member at the UCSF Weill Institute for Neurosciences. Her research focuses on understanding the genetic architecture of autism spectrum disorder through genome-wide genetic data analysis and human induced pluripotent stem cell (iPSC) models. Dr. Weiss's laboratory investigates the genetic mechanisms by which DNA variants influence autism risk, examining questions about copy number vs. SNP variation, rare vs. common variation, gene-sex interaction, gene-gene interaction, and gene-environment interaction. Her team uses rich genetic datasets to identify susceptibility loci and the physiological pathways these risk loci implicate. Additionally, they employ iPSC models to study known mutations or copy number variants predisposing to autism, first identifying the effects of genetic risk variants and then determining whether these effects can be modified at the cellular level by environmental or pharmacological agents. Analysis of Dr. Weiss's recent publications reveals a strong focus on sex differences in autism genetics, the role of specific copy number variants (particularly 16p11.2 and 22q11.2), maternal environmental factors during pregnancy, and the integration of multi-omics data to understand neurodevelopmental pathways. Her work bridges basic genetic research with potential clinical applications for improving understanding, prevention, diagnosis, and treatment of autism and related traits. Dr. Weiss has secured significant research funding as Principal Investigator on multiple NIH grants, including R01MH114924 (Decoding the Genetics of Sexual Dimorphism in Autism Spectrum Disorders), R01MH107467 (Utilizing eQTL networks to gain biological insight into multigenic CNVs), and DP2OD007449 (Dissecting Epistasis and Pleiotropy in Autism towards Personalized Medicine). Her laboratory offers research opportunities for students interested in analytical genetics projects related to gene-environment effects, gene-sex effects, gene-gene effects, and the relationship between ASD and brain size. Dr. Weiss actively collaborates with numerous researchers across institutions, particularly on large-scale genomic studies of autism and other neurodevelopmental disorders. Her work has contributed significantly to our understanding of the complex genetic architecture underlying autism spectrum disorder and related conditions.

Fabiola Ceroniمشاهده پروفایل

پژوهشگر ارشد

• Developmental Eye Disorders
• Genomics
• Structural Variants
• +۳ مورد دیگر

Fabiola Ceroni is a Senior Research Fellow at Oxford Brookes University's School of Biological and Medical Sciences, specializing in the Molecular Genetics of Human Eye Development . Her research focuses on identifying novel genes and molecular mechanisms underlying developmental eye disorders through advanced genomic techniques. Institution: Oxford Brookes University School: School of Biological and Medical Sciences Role: Senior Research Fellow in Professor Ragge's team Her work primarily addresses developmental eye disorders such as anophthalmia, microphthalmia, and coloboma, utilizing whole genome/exome sequencing and copy number variant analysis . Recent publications highlight her contributions to understanding genetic regulation in eye development and neurodevelopmental disorders. Key trends in her publications include: Genotype-phenotype correlations in developmental eye disorders Role of structural variants and non-coding sequences in congenital anomalies Genetic mechanisms in autism spectrum disorder and neurodevelopmental syndromes CRISPR/Cas9 applications for functional validation She collaborates with multidisciplinary teams and contributes to open-access research, with publications available via Oxford Brookes' Research Repository (RADAR).

• Machine Learning
• Bioinformatics
• Medical Imaging
• +۵ مورد دیگر

Paul J. Kennedy is a Professor at the University of Technology Sydney's Centre for Artificial Intelligence. He holds a PhD from the same institution (1999). His research focuses on machine learning applications in healthcare, bioinformatics, medical imaging, and data mining. Key areas include developing algorithms for genomic data analysis, healthcare pathway modeling, and edge-cloud frameworks for omics data. Education: PhD in Artificial Intelligence (1999, UTS). Research interests span machine learning, health informatics, and data compression. Notable work includes studies on administrative health records, lung nodule detection, and virtual reality-based cancer cohort analysis. He has co-authored over 100 publications across journals like BMC Bioinformatics, IEEE Transactions, and Artificial Intelligence in Medicine. Advising: Collaborates extensively with students/researchers but no explicit student list provided. Grants and labs: Active in interdisciplinary projects involving medical and computational teams, though specific grants are not detailed here.

• Computational Biology
• Genomics
• Cancer Research
• +۵ مورد دیگر

Adam Olshen, PhD, MA is a Professor in the Department of Epidemiology & Biostatistics at the University of California, San Francisco School of Medicine. His research program bridges advanced statistical methodology with cancer genomics and clinical applications, focusing on developing computational approaches to analyze complex genomic data and understand cancer biology and patient outcomes. Dr. Olshen's research spans multiple critical areas in computational biology and cancer genomics. He is best known for developing the circular binary segmentation algorithm, a foundational method for analyzing DNA copy number data that has become standard in cancer genomics research. His work consistently applies sophisticated statistical models to address biological questions, particularly in cancer research where he examines tumor biology, treatment response mechanisms, and patient symptomatology. Recent work demonstrates expertise in multi-omic analyses, single-cell sequencing methodologies, and machine learning applications for understanding cancer stem cells, treatment resistance mechanisms, and symptom biology. His research has particular strength in translating complex genomic data into clinically relevant insights. Analysis of Dr. Olshen's recent publications reveals a strong focus on applying cutting-edge computational methods to understand cancer biology at increasingly granular levels. His work spans multiple cancer types including breast cancer, leukemia, prostate cancer, and others, with particular attention to genomic alterations, epigenetic changes, and their relationship to clinical outcomes. A notable trend is the application of advanced computational techniques to analyze single-cell and multi-omic data to uncover novel biological insights about cancer heterogeneity, progression, and symptom biology. His publications frequently appear in high-impact journals across computational biology, oncology, and clinical medicine. Dr. Olshen maintains an active collaborative research program across UCSF, working extensively with clinicians and basic scientists to apply sophisticated statistical methods to complex biological questions. His work has contributed significantly to the development of novel biomarkers, improved understanding of cancer biology, and better methods for analyzing genomic data in clinical contexts. He has been instrumental in numerous studies examining the relationship between genomic alterations and clinical outcomes, as well as the development of novel computational methods for genomic data analysis that have been widely adopted by the research community.

Kaitlyn Crawfordمشاهده پروفایل

دانشیار

• Soft Materials
• Flexible Electronics
• Sustainable Polymers
• +۱ مورد دیگر

Kaitlyn Crawford is an Associate Professor of Materials Science and Engineering at the University of Central Florida, with a secondary appointment in Chemistry. She directs the Functional Materials and Sensors Lab, focusing on sustainable soft materials for flexible electronics and biomedical applications. Her research integrates polymer science and engineering to develop wearable sensors for health monitoring, biodegradable materials to reduce e-waste, and natural polymer composites. Current projects include a $1.5M DHS-funded wearable for firefighter heat-stress monitoring and NASA-funded space applications. Her recent publications emphasize sustainable polymers, bionic devices, and AI-driven diagnostics. Awards include the 2024 ACS PMSE Early Investigator Award and a Jewish National Fund fellowship. She leads multiple graduate students in biomedical and materials research. Awards: 2024 ACS PMSE Early Investigator Award Faculty Fellowship Program in Israel, Jewish National Fund Faculty Excellence Honoree, Women’s History Month (UCF)