جست‌وجوی استاد و پژوهشگر

Peggi Melissa Angelمشاهده پروفایل

استاد

• Breast Cancer Research
• Extracellular Matrix Remodeling
• Proteomics
• +۴ مورد دیگر

Peggi Melissa Angel is a Professor in the Department of Pharmacology & Immunology at the College of Medicine, Medical University of South Carolina (MUSC). Her research focuses on extracellular matrix dynamics in cancer and chronic diseases, with emphasis on ancestry-related disparities in breast cancer progression and novel mass spectrometry imaging techniques. Her academic training includes: BS in Chemistry (ACS certified), 1999 PhD from University of Georgia (2007) on "Quantitative Proteomics in Developmental Biology" Postdoctoral Fellowship at Emory University (2007-2008) studying "Fetal Alcohol Syndrome & Alcohol-induced Mitochondrial Post-translational Modifications in Liver Disease" Postdoctoral Fellowship at Vanderbilt University Medical Center (2008-2011) on "Systems-based Consortium for Organ Design and Engineering: Heart Valves" Dr. Angel's laboratory pioneers spatial proteomics and glycomics workflows, integrating 2D collagen mapping with microscopy to decode the "collagen switch" in triple-negative breast cancer. Her team develops high-throughput N-glycan assays using imaging mass spectrometry for applications in cancer and cardiovascular diseases, while investigating extracellular matrix remodeling in liver fibrosis, lung adenocarcinoma, and cardiovascular pathology. Current projects focus on quantitative measurement of collagen post-translational modifications and site-specific mutations in disease contexts. Analysis of her 15 most recent publications reveals dominant trends in spatial omics for cancer microenvironment characterization, with strong emphasis on breast cancer disparities (particularly Black vs. White patient cohorts), pancreatic and prostate cancer heterogeneity, and early detection of liver disease progression. Her work consistently bridges proteomics, glycomics, and ancestry-related molecular patterns using advanced MALDI-MSI platforms. Dr. Angel leads an active research laboratory at MUSC developing cutting-edge methodologies for extracellular matrix and glycan analysis. Her team specializes in multimodal mass spectrometry imaging, machine learning-enhanced data analysis, and the creation of spatial atlases for human tissue microenvironments. Current initiatives include the development of automated histology-MSI co-registration systems and high-throughput platforms for single-cell glycomic profiling.

Koei Chinمشاهده پروفایل

پژوهشگر

• Cancer Biology
• Genomics
• Oncology
• +۳ مورد دیگر

Dr. Koei Chin is a researcher focused on understanding the mechanisms of genomic instability in cancer initiation and progression, particularly in breast and pancreatic cancers. His work emphasizes identifying molecular targets for early detection and developing therapeutic strategies. He collaborates extensively with institutions on high-impact studies, leveraging multiplex imaging and multiomics approaches to dissect tumor heterogeneity and microenvironment interactions. His research integrates advanced imaging techniques (e.g., spatial profiling, cyclic immunostaining) to uncover prognostic biomarkers and therapeutic vulnerabilities. Key themes include immune-stromal interactions in breast cancer, replication stress in pancreatic cancer recurrence, and resistance mechanisms in HER2+ tumors. He actively develops standardized frameworks for reproducible data analysis in tissue imaging. Dr. Chin’s contributions span experimental models, preclinical drug testing (e.g., Juglone-based therapies), and translational studies linking genomic alterations to clinical outcomes. His interdisciplinary approach bridges basic science and clinical applications, aiming to improve precision oncology.

Pratip Ranaمشاهده پروفایل

استادیار

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

Pratip Rana is an Assistant Professor at Old Dominion University, specializing in interdisciplinary research at the intersection of machine learning, bioinformatics, and healthcare. His work focuses on developing advanced computational methods for medical diagnosis, cancer subtyping, and multiomics data analysis. He has contributed to projects involving LiDAR data generation, drug-target affinity prediction, and physics-informed neural networks for fluid flow modeling. Research interests include applying AI to healthcare challenges (e.g., TBI prediction, radiotherapy structure identification), modeling protein aggregation in neurodegenerative diseases (e.g., Alzheimer’s), and designing nanomaterials for gas sensing applications. His recent publications emphasize multimodal deep learning, feature selection for cancer classification, and synergy between machine learning and constraint-based biological models. His articles highlight contributions to medical AI, computational biology, and materials science. No scientific awards are listed, though his work reflects strong interdisciplinary innovation. Advising and grant details are not explicitly provided in the text.

Heejung Kimمشاهده پروفایل

استادیار

• Adaptive Radiotherapy
• Artificial Intelligence in Healthcare
• Medical Physics
• +۳ مورد دیگر

Heejung Kim, Ph.D., is an Assistant Professor in the Department of Radiation Oncology at UT Southwestern Medical Center, specializing in the Division of Medical Physics & Engineering. She holds a B.S. in Electrophysics from Kwangwoon University, and M.S. and Ph.D. degrees in Biomedical Engineering from Seoul National University. Dr. Kim’s research focuses on adaptive radiotherapy, artificial intelligence applications in healthcare, and medical physics innovations. Prior to her academic role, she served as a medical physicist at Samsung Medical Center in Seoul, Korea, and holds a Texas Medical Physicist License with board certification in therapeutic medical physics from the American Board of Radiology. Her research interests span radiation dosimetry, image-guided radiation therapy, and proton therapy optimization. Notable contributions include studies on Monte Carlo dose calculations, synthetic CT generation using deep learning, and toxicity predictors in stereotactic ablative radiotherapy. Dr. Kim actively contributes to professional associations and has published extensively in journals like Medical Physics and Cancers. Her work integrates clinical radiation oncology with advanced technologies, emphasizing patient-specific solutions and precision medicine approaches. Despite no explicitly listed awards, her board certifications highlight professional excellence. Advising is inferred through her academic role, though specific student names are unrecorded here.

Sarah Amalia Teichmannمشاهده پروفایل

استاد

• Genomics
• Biophysics
• Immunology
• +۳ مورد دیگر

Professor Sarah Amalia Teichmann FRS FMedSci is a leading computational and experimental biologist at the University of Cambridge, where she holds a Professorship in Stem Cell Medicine and serves as Director of Research at the Cavendish Laboratory. She leads visiting research groups at the European Bioinformatics Institute (EMBL-EBI) and Wellcome Sanger Institute, with additional affiliations at Churchill College and the Cambridge Stem Cell Institute. Her research bridges protein complex evolution and single-cell immunology, developing graph theory methods for protein assembly classification and pioneering single-cell transcriptomics to study immune system dynamics. Recent work focuses on spatial transcriptomics, multi-omics disease modeling, and T cell receptor-antigen-HLA code deciphering. Scientific awards include the EMBO Gold Medal, Colworth Medal, Lister Prize, and the FEBS EMBO Women in Science Award. She has mentored numerous PhD students and postdoctoral researchers, many of whom became independent investigators. Her lab collaborates on projects like the Human Cell Atlas and develops tools such as CellPhoneDB. EMBO Gold Medal (2015) Colworth Medal (2010) Lister Prize (2011) Francis Crick Medal (2012) FEBS EMBO Women in Science Award (2023)

Qiuyu Lianمشاهده پروفایل

پژوهشگر ارشد

• Single-cell Sequencing
• Spatial Transcriptomics
• Cancer Biology
• +۳ مورد دیگر

Qiuyu Lian is a Research Fellow at the University of Cambridge, affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP) under the Faculty of Mathematics. Their research focuses on biological physics and mechanics, with a strong emphasis on single-cell sequencing technologies, spatial transcriptomics, and cancer biology. Key areas of interest include understanding molecular mechanisms driving cancer progression, developing computational tools for genomic data analysis, and exploring interactions between microbiota and stem cell development. Research interests prominently feature systems biology approaches to study cancer heterogeneity, gene regulation networks, and therapeutic resistance mechanisms. Their work bridges computational methods (e.g., neural network modeling, bioinformatics pipelines) with experimental biology, particularly in hepatocellular carcinoma and lung adenocarcinoma. Recent projects include the HCCDB database for cancer expression analysis and advancements in spatial transcriptomics to map tumor microenvironments. Publications highlight contributions to single-cell sequencing methodologies (e.g., AAB-seq, GMM-Demux), spatial transcriptomics integration with histopathological imaging (TIST), and molecular characterization of cancer subtypes. These studies underscore a multidisciplinary approach combining engineering, mathematics, and biology to address complex biological systems. No scientific awards are explicitly mentioned in the provided texts, though their extensive publication record suggests recognition within the field. Advising and grant activities are not detailed here, but their research collaborations likely involve advanced computational and experimental facilities at DAMTP. Lian’s work is part of broader initiatives in biological physics, aiming to translate molecular insights into clinical applications for cancer therapy and diagnostics.

Michael Dohopolskiمشاهده پروفایل

استادیار

• Radiation Oncology
• Artificial Intelligence in Medical Imaging
• Adaptive Radiotherapy
• +۵ مورد دیگر

Michael Dohopolski, M.D., is an Assistant Professor in Radiation Oncology at the University of Texas Southwestern Medical Center. He holds a bachelor’s degree from the University of Notre Dame and an M.D. from the University of Pittsburgh School of Medicine. His clinical training includes an internship in preliminary medicine at Banner University Medical Center Phoenix and a residency in Radiation Oncology at UT Southwestern, where he now focuses on central nervous system diseases. Dr. Dohopolski’s research emphasizes AI-driven advancements in radiation therapy, including adaptive radiotherapy, auto-segmentation, and personalized treatment protocols like PULSAR. His work spans clinical outcomes analysis, dosimetry optimization, and radiomics-based prediction models for cancers of the head and neck, prostate, and brain metastases. He has contributed to over 47 peer-reviewed publications and received awards such as the RSNA Roentgen Resident/Fellow Research Award. His honors highlight his innovative approach to integrating machine learning with clinical practice. Ongoing projects explore AI uncertainty quantification, multiomics outcome prediction, and enhancing patient-reported quality-of-life metrics through optimized radiotherapy protocols.

• Alzheimer's Disease Research
• Neurogenetics
• Functional Genomics
• +۳ مورد دیگر

Amanda Myers, PhD, is a Professor of Cell Biology at the University of Miami, Miller School of Medicine, with co-appointments in the Division of Neuroscience, the Department of Human Genetics and Genomics, and the Center on Aging. As a founding member of the Academy of Medical Educators and Associate Editor for PLoS Genetics, she leads the Laboratory of Functional Neurogenomics and maintains continuous funding from the National Institute on Aging. Her educational background includes: BA in Psychology and Biological Basis of Behavior, University of Pennsylvania (1993) PhD in Neuroscience, Washington University in St. Louis (2002) Dr. Myers' research centers on multi-omics analysis of 3,000+ human brain tissue samples (60% with Alzheimer's pathology) to identify molecular disease mechanisms. Key interests include: DNA, RNA, and protein alterations in Alzheimer's brain tissue iPSC modeling of cognitive decline pathways Heat-shock protein dynamics and protein trafficking defects Genomic control of expression and novel target identification Her 2021-2023 publications reveal genetic risk factors across diverse populations, blood-based biomarkers for early detection, and susceptibility genes for Alzheimer's and related dementias, emphasizing translational applications through multi-omic integration. Her accolades include: ADRC Director's Education Award John Merlie Fellowship O'Leary Prize Finalist for Neuroscience Research National Academy of Sciences Resident Research Associateship Distinguished Mentor Award Nomination NIH Early Career Reviewer Program Dr. Myers mentors students across academic levels and serves as a scientific reviewer for NIH study sections, international agencies including the French National Research Agency and Qatar National Research Fund, and multiple journals. Current research is funded by NIA, with past support from NIMH and NINDS. She directs the Laboratory of Functional Neurogenomics, which integrates genomic, transcriptomic, and proteomic data within collaborative networks at the Miller School of Medicine to advance Alzheimer's therapeutics.

Yoshiaki Tanakaمشاهده پروفایل

دانشیار

• Genomics
• Bioinformatics
• Brain Tumor Mechanisms
• +۴ مورد دیگر

Yoshiaki Tanaka is an Associate Professor at the University of Montreal's Faculty of Medicine, Department of Medicine. He leads the Functional Genomics and Bioinformatics Research Unit at the Maisonneuve-Rosemont Hospital Research Center (CRHMR). His research focuses on understanding tumor progression, metastasis, and drug resistance using 3D in vitro brain organoids and large-scale genomic data analysis techniques like single-cell RNA-seq, ATAC-seq, and ChIP-seq. Dr. Tanaka’s team integrates computational methods with cellular models to develop novel therapeutic strategies for brain tumors and neurological diseases. Education: BSc in Pharmaceutical Sciences (2006, Tokyo University of Science), PhD in Life Sciences (2011, University of Tokyo under Dr. Kenta Nakai), Postdoctoral training (2011–2020) at Yale University under Dr. In-Hyun Park, specializing in stem cell pluripotency and tissue development. Research Interests: Molecular mechanisms of brain tumors, organoid-based disease modeling, AI-driven genomic data analysis, chromatin dynamics, and neurodevelopmental disorders. His lab develops 3D brain organoids to study glioblastoma microenvironment interactions and leverages machine learning for single-cell data interpretation. Grants and Awards: 2020 Quebec Research Fund - Health Junior 1 Fellowship. Active projects include NSERC-funded studies on BRD4’s role in brain development, FRQS-supported AI-driven tumor subtype analysis, and IRSC-backed investigations into glioblastoma microenvironment interactions using organoids. Labs/Teams: Directs the Functional Genomics and Bioinformatics Unit at CRHMR. Collaborates with institutions like the CIUSSS de l'Est-de-l'Île-de-Montréal. Current trainees include Nicolas Paradis-Isler, Samantha Yuen, and Saber Saharkhiz.

• Neurodevelopmental Disorders
• Epigenetics
• Molecular Biology
• +۳ مورد دیگر

Dr. Rudrarup Bhattacharjee is a Postdoctoral Researcher at the School of Biomedicine, Faculty of Health and Medical Sciences, University of Adelaide. His research focuses on neurodevelopmental disorders, epigenetic mechanisms, and mRNA export factors like THOC2. He is affiliated with the Polo Group at the Adelaide Centre for Epigenetics and eligible to co-supervise Masters and PhD students in projects related to neurodevelopmental disorders and epigenetics. His research combines molecular biology, genomics, and proteomics to investigate mechanisms underlying neurological conditions. Recent projects include studying THOC2-associated disorders and exploring epigenetic therapies for Rubinstein-Taybi Syndrome. He has contributed to grants such as the MRFF Stem Cells Therapies Mission (2024-2025) and the Therapeutic Innovation Australia (TIA) Pipeline Accelerator (2024-2025). Teaching: Demonstrator/Tutor for Physiology 2B (2023), Guest Lecturer on Precision Medicine (2024). Supervision: Co-supervising Honours student Angela Kloutsiniotis on meningioma epigenetics. Labs/Teams: Active member of the Polo Group and Adelaide Centre for Epigenetics. His work bridges basic research and translational medicine, emphasizing multiomic approaches and CRISPR/Cas9 applications.

Evelyn Ramplerمشاهده پروفایل

استادیار

• Analytical Chemistry
• Mass Spectrometry
• Metabolomics
• +۳ مورد دیگر

Evelyn Rampler is an Assistant Professor (Tenure Track) at the University of Vienna's Faculty of Chemistry, Department of Analytical Chemistry. Her research focuses on advancing mass spectrometry-based methodologies for lipidomics and metabolomics, with particular expertise in ganglioside profiling, metabolic pathway analysis, and analytical workflow optimization. She leads projects addressing challenges in quantitative lipidomics, sustainable metabolite extraction, and the application of novel mass spectrometry tools for biomarker discovery. Her academic contributions include pioneering work on TRAM (Triple Acquisition Mass Spectrometry) for integrated metabolomics and lipidomics analysis, FAIMS-enhanced lipidomics workflows, and taxonomically-informed metabolite identification tools like microbeMASST. She has organized international conferences such as APMRS-CEEPC 2024 and actively promotes gender equity in analytical chemistry through advocacy initiatives. Key research areas span metabolic engineering using isotope labeling, sustainable agricultural practices for bioactive compound production, and drug discovery targeting cancer metabolism. Rampler has secured research funding for projects like 'Prone Adiposity,' exploring adipogenic differentiation mechanisms in mesenchymal stem cells through multiomics approaches. Her lab develops innovative LC-MS methodologies to enhance metabolite coverage and analytical throughput while maintaining high resolution and accuracy. Notable collaborations include work with institutions on microbial metabolomics, plant lipidomics, and stem cell glycolipid analysis. Her team's activities emphasize translational applications of analytical chemistry in environmental science, pharmacology, and biomedical research, with over 55 peer-reviewed publications and frequent conference presentations since 2012.

• Neuro-oncology
• Molecular Biology
• Cancer Genetics
• +۴ مورد دیگر

Ulrich Schüller is a Professor of Neuropathology and Medical Specialist in the Faculty of Medicine at the University of Hamburg. He holds dual roles as Senior Physician in the Institute of Neuropathology and Head of Research Group in the Department of Pediatric Hematology and Oncology at the University Medical Center Hamburg-Eppendorf (UKE). His research focuses on molecular profiling of brain tumors, including medulloblastoma, glioblastoma, and pediatric cancers, with expertise in DNA methylation-based classifications and nanopore sequencing technologies. He leads studies on tumor heterogeneity, therapeutic vulnerabilities, and clinical biomarkers. Key affiliations include the UKE’s Center for Molecular Neurobiology Hamburg (ZMNH) and collaborative networks like the European Liquid Biopsy Society (ELBS). He contributes to international trials (e.g., HIT-MED, P-HIT) and has pioneered work on extracellular vesicle-based diagnostics and targeted therapies for pediatric brain tumors. His interdisciplinary approach integrates genomics, proteomics, and clinical data to improve diagnosis and treatment stratification. Research interests span neuro-oncology, epigenetic profiling, and pediatric cancer biology, with publications emphasizing molecular mechanisms of tumor progression and novel therapeutic strategies. Collaborations include academic institutions globally, focusing on translational research to bridge basic science and clinical practice.

Lindsay M. LaFaveمشاهده پروفایل

استادیار

• lung cancer
• lung stem cells
• cancer predisposition
• +۸ مورد دیگر

Lindsay M. LaFave, Ph.D., is an Assistant Professor in the Department of Cell Biology at Albert Einstein College of Medicine, holding the Rubenstein Family Early Career Professorship in Environmental Determinants and Disease. Her research focuses on understanding non-genetic mechanisms driving lung cancer progression, particularly through chromatin biology and epigenomic dynamics. She employs genetically engineered mouse models, organoid platforms, and cutting-edge technologies like single-cell ATAC-seq and spatial genomics to study lung adenocarcinoma (LUAD) evolution. Her work investigates how chromatin state transitions disrupt cellular identity and contribute to metastasis, intratumoral heterogeneity, and pre-metastatic programs. Key methodologies include mouse modeling, alveolar organoids, and multi-omic analyses to dissect gene regulatory networks and tumor microenvironment interactions. Notable contributions include defining chromatin plasticity in LUAD and identifying epigenomic signatures predictive of cancer progression. Awards: No scientific awards explicitly listed in the provided text. Advising & Grants: While no student names are listed, her research is supported by grants focused on epigenetic mechanisms in cancer. She collaborates across disciplines, integrating computational and experimental approaches to advance precision oncology. Labs/Teams: Active in the Department of Cell Biology, leveraging collaborations within the Einstein cancer research community to develop novel tools for studying early and late-stage lung cancer progression.

• Computational Health Sciences
• Precision Medicine
• Data Science
• +۳ مورد دیگر

Atul Butte, MD, PhD, is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and inaugural Director of the Bakar Computational Health Sciences Institute at UCSF. He also serves as Chief Data Scientist for the University of California Health System (UC Health), overseeing 20 health professional schools and 10 hospitals. His research focuses on computational health sciences, precision medicine, and data-driven biomedical innovation. Butte has authored nearly 300 publications, pioneered methods for drug repurposing, and co-founded three biotech companies: Personalis, Carmenta, and NuMedii. Education: Brown University (Computer Science, MD), Harvard Medical School (PhD in Health Sciences and Technology). Research Interests: Leveraging big data for disease stratification, drug discovery, and precision health. Key areas include genomic analysis, electronic health record (EHR) mining, and AI-driven diagnostics. His work emphasizes open science and translational applications, such as identifying novel therapies from existing drugs and molecular data. Articles Overview: Recent work spans computational methods for cancer drug discovery, AI applications in cardiology and emergency medicine, and multi-omics studies on stress resilience. His publications highlight interdisciplinary approaches to solving complex biomedical challenges. Awards: Recognitions include election to the National Academy of Medicine (2015), AAAS Fellow (2023), and Obama Administration's Open Science Champion (2013). Grants & Advising: Continuously NIH-funded for 20 years, with grants in genomic data integration, endometriosis research, and precision medicine initiatives. Advises on clinical informatics and data infrastructure modernization. Labs/Teams: Leads the Bakar Institute and collaborates across UC Health's institutions, fostering cross-disciplinary data science initiatives.

• Genomics
• Genetics
• Human genome research
• +۶ مورد دیگر

Kelly Frazer is a Professor in the Department of Pediatrics at the University of California San Diego (UCSD) School of Medicine. She leads a highly productive research program focused on genomics and genetics, with particular expertise in human genome analysis, stem cell genomics, and translational research. Her work bridges basic science with clinical applications, aiming to understand the genetic basis of human diseases through large-scale genomic approaches. Dr. Frazer's research interests span multiple areas of genomic medicine, with a particular focus on understanding how genetic variations influence disease susceptibility and progression. Her work leverages advanced genomic technologies including genome-wide association studies (GWAS), expression quantitative trait loci (eQTL) mapping, single-cell genomic approaches, and multi-omic integration. She has made significant contributions to understanding the genetic architecture of complex traits related to cardiovascular disease, diabetes, retinal degeneration, and other conditions, often using induced pluripotent stem cell (iPSC) models to investigate disease mechanisms. Analysis of her recent publications reveals a strong trend toward increasingly sophisticated genomic analyses that integrate multiple data types to pinpoint causal variants and understand their functional consequences across different tissues and developmental stages. Her work spans from basic genomic methodology development to direct clinical applications, with particular emphasis on translating genomic findings into biological insights about disease pathogenesis. She frequently employs population-based approaches to understand how genetic variation contributes to phenotypic diversity in human populations. Dr. Frazer maintains an extensive research program with numerous active NIH-funded projects, including the 'Genetic & Social Determinants of Health: Center for Admixture Science and Technology' and 'Unraveling the molecular pathology of retinal degeneration through single cell genomics.' She is a key contributor to several major research consortia including the iPSCORE Consortium and the COVID-19 Host Genetics Initiative, reflecting her collaborative approach to addressing complex biomedical questions.