جست‌وجوی استاد و پژوهشگر

• Plant-Microbe Symbiosis
• Phosphate Transport
• Plant Defense
• +۳ مورد دیگر

Dr. Maria Harrison is the William H. Crocker Distinguished Professor at Cornell University's School of Integrative Plant Science and Adjunct Professor in Plant Pathology. Her research investigates arbuscular mycorrhizal symbioses, focusing on phosphate transfer mechanisms and plant defense biochemistry. Using model legumes and poplar trees, her lab studies fungal colonization, symbiotic gene regulation, and metabolic pathways for bioactive compounds. She was elected to the Royal Society in 2024, recognizing her contributions to plant-microbe interactions. Her publications reveal insights into lipid provisioning, kinase signaling in symbiosis, and development of plant biosensors. Research integrates molecular genetics, cell biology, and genomics to address nutrient acquisition challenges in agriculture.

Qian Liuمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Applied Statistics
• +۵ مورد دیگر

Dr. Qian Liu is an Assistant Professor in the Department of Applied Computer Science at the University of Winnipeg . She holds a PhD in Individual Interdisciplinary Studies, integrating Computer Science, Statistics, and Medical Genetics. Her research focuses on advanced data science techniques for healthcare and material science, including multi-modal data integration and interpretable AI. Education : 2023: Postdoc, Western University, Canada 2023: PhD, University of Manitoba, Canada 2019: MSc, University of Manitoba, Canada Research Interests : Machine learning, deep learning, bioinformatics, computational biology, medical imaging, and their applications in healthcare and material informatics. Her lab develops tools for genomic integration, radiogenomics, and AI-driven biomarker discovery. Recent Contributions : Her work spans AI in nanomaterial classification, breast cancer biomarker discovery, and emotion recognition. Articles highlight innovations in graph neural networks, diffusion models, and interpretable deep learning. Awards : 2024 University of Manitoba Distinguished Dissertation Award 2019 Best Oral Paper at IEEE Bioinformatics Conference Grants : NSERC 2024 Discovery Grant (Principal Investigator) CIHR 2023 Project Grant (Co-Applicant) Labs/Teams : Active in interdisciplinary collaborations across computer science, statistics, and biomedical domains. Lab members include postdocs, PhD/MS students, and undergraduate researchers.

Jonathan Brittمشاهده پروفایل

دانشیار

• Behavioral Neuroscience
• Addiction
• Drug Addiction
• +۵ مورد دیگر

Jonathan Britt is an Associate Professor in the Department of Psychology at McGill University, affiliated with the Faculty of Science. He leads the Britt Lab, focusing on neural circuitry underlying motivated behaviors, particularly in the context of addiction and neuropsychiatric disorders. His work combines optogenetics, electrophysiology, and behavioral tasks to study the basal ganglia's role in reinforcement learning and compulsive behavior. Research interests include the neural mechanisms of drug addiction, Tourette’s Syndrome, and obsessive-compulsive disorder, with a focus on dopamine pathways and synaptic modifications. Key methodologies involve all-optical approaches and optogenetic interrogation of neural circuits. His recent studies highlight topics like alcohol palatability, serotonergic regulation of attention, and LSD’s effects on social behavior. Articles often explore the nucleus accumbens and hippocampal interactions in reward processing. No scientific awards are explicitly listed, though his contributions to addiction neuroscience are notable. He advises no listed students and has no mentioned grants in the provided text. The Britt Lab serves as a central hub for his research activities.

• Plant Pathology
• Molecular Plant Pathology
• Genomics of Plant Pathogens
• +۷ مورد دیگر

Pietro Spanu is a Professor of Molecular Plant Pathology at the Department of Life Sciences, Imperial College London, within the Faculty of Natural Sciences. His work focuses on understanding plant-pathogen interactions, particularly the genomics and molecular mechanisms of powdery mildews. He leads research into how pathogens manipulate host cellular processes and evade immune responses. Key affiliations include the Agri Futures Lab, Fungal Science Network, and Microbiome Network. His research interests span the genomics of powdery mildews, effector proteins, and host-pathogen communication via extracellular vesicles. He employs cutting-edge techniques like AI-guided discovery and transcriptomics to study pathogen virulence and host defense. Recent work highlights effector interference with endosomal complexes, RNA fragment roles in cross-kingdom signaling, and evolutionary dynamics of plant pathogens. Spanu’s contributions include groundbreaking studies on barley and wheat powdery mildews, revealing mechanisms behind fungal adaptation and virulence. His lab integrates molecular genetics, genomics, and computational biology to address agricultural challenges like crop disease resistance and food security. Collaborations span microbiome networks and interdisciplinary platforms like the Industrial Biotechnology Hub.

Auguste Genovesioمشاهده پروفایل

پژوهشگر

• Computational Bioimaging
• Bioinformatics
• Machine Learning
• +۷ مورد دیگر

Auguste Genovesio is a Research Director (DR INSERM) leading the Computational Bioimaging and Bioinformatics team at the Centre for Computational Biology within the École Normale Supérieure (ENS) in Paris. His work focuses on large-scale cellular morphology analysis, integrating machine learning, microscopy, and computational modeling to study cellular responses to perturbations. His team develops algorithms for analyzing high-dimensional biological data, with applications in drug discovery, functional genomics, and neuroscience. Education and Affiliations: Genovesio’s research is anchored at ENS and collaborates with institutions like Institut Curie, Collège de France, and ESPCI. His lab develops open-source tools such as PySpacell and ALFA , advancing spatial analysis and genomic data processing. Research Interests: His group combines deep learning, bioinformatics, and experimental biology to tackle challenges in cellular dynamics, morphological heterogeneity, and predictive modeling. Recent work includes applying diffusion models to reveal subtle phenotypes and optimizing microscopy image analysis pipelines. Key Projects: Cross-modal knowledge distillation for transcriptomics, latent diffusion models for small datasets, and super-resolution microscopy via StyleGAN regularization. Applications: Collaborations in drug screening, neurobiology (e.g., Drosophila memory studies), and cancer cell analysis. Publications: Over 50 peer-reviewed articles since 2007, including work in Nature Communications , Developmental Cell , and NeurIPS . Recent focus on generative AI for biological image analysis and self-supervised learning biases. Grants & Awards: While specific grants aren’t listed, his lab’s cutting-edge research suggests significant institutional and collaborative support. No explicit awards mentioned in texts. Labs/Teams: Director of the Computational Bioimaging group, part of the Functional Genomics section at ENS. Supervises PhD students and postdocs in AI-driven biology and computational microscopy.

Lu Shin Wongمشاهده پروفایل

مدرس ارشد

• Biocatalysis
• Nanofabrication
• Chemical Biology
• +۳ مورد دیگر

Lu Shin Wong is a Senior Lecturer in Chemical Biology and Biological Chemistry at the University of Manchester's School of Chemistry, affiliated with the Manchester Institute of Biotechnology. He holds a PhD from the University of Southampton and has expertise in biocatalysis and nanofabrication. His research focuses on sustainable chemical processes, enzyme-driven reactions, and nanoscale material fabrication. Wong has held postdoctoral roles at Manchester and Northwestern University, and leads projects in biocatalytic applications, nanotechnology, and bioelectronics. Education: PhD in Organic and Analytical Chemistry (University of Southampton, 2005); BPharm (University of Nottingham, 1997); Postgraduate Diploma in Clinical Pharmacy (University of Bradford, 2001). Research Interests: Biocatalysis (enzyme-mediated organosilicon chemistry, sustainable oxidations); Nanofabrication (scanning probe lithography, polymer pen lithography). His work bridges biotechnology and nanotechnology, emphasizing sustainable synthesis and biomedical applications. Recent projects include the Manchester Bioelectronics Network and CRISPR-Cas technology integration into organic electronics. Key Achievements: Developed methods for protein immobilization using phosphopantetheinyl transferase, pioneered biocatalytic approaches to silicone polymer synthesis, and contributed to understanding stem cell behavior on nanostructured substrates. Active in interdisciplinary collaborations, including bioelectronics and mass spectrometry advancements.

• Molecular Biology
• Genetics
• Aging
• +۴ مورد دیگر

Siu Sylvia Lee is a Professor in the Department of Molecular Biology and Genetics at Cornell University, within the College of Agriculture and Life Sciences. She holds a B.A. in Biochemistry from Rice University (1995) and a Ph.D. from Baylor College of Medicine (1999). Her postdoctoral training at Massachusetts General Hospital and Harvard Medical School included a Damon Runyon Cancer Foundation Fellowship. She joined Cornell in 2003 and became a tenured Associate Professor in 2010, later promoted to full Professor. Her research focuses on epigenetic regulation, aging mechanisms, and longevity in Caenorhabditis elegans , supported by grants from the National Institute of Aging and the Ellison Medical Foundation. Her work integrates chromatin profiling, histone modifications, and mitochondrial signaling to understand aging-related processes. Key areas include sex-specific metabolomics, histone methylation dynamics, and transcription factor networks influencing longevity. Lee teaches advanced courses on cellular/molecular biology and cell proliferation regulation. Education: B.A. Biochemistry, Rice University, 1995 Ph.D., Baylor College of Medicine, 1999 Postdoctoral Fellowship, Massachusetts General Hospital & Harvard Medical School Scientific awards include the Damon Runyon Cancer Foundation Postdoctoral Fellowship. Her research bridges genetics, epigenetics, and developmental biology, with a focus on conserved mechanisms across species. She collaborates on studies involving lipid homeostasis and stress responses in aging. Grants and funding support her exploration of mitochondrial-nuclear communication and chromatin changes in longevity. She advises on molecular genetics graduate programs and contributes to labs investigating aging-related epigenetic changes in C. elegans .

Stewart Massonمشاهده پروفایل

پژوهشگر ارشد

• Metabolic Disease Genetics
• Insulin Resistance
• Cellular Trafficking Mechanisms
• +۳ مورد دیگر

Dr Stewart Masson is a Research Fellow at the Charles Perkins Centre, University of Sydney, within the Faculty of Science. His research focuses on the genetics of metabolic disease and insulin resistance, with a particular interest in the etiology of insulin resistance and intracellular trafficking mechanisms. He holds a PhD from the University of Auckland (2021), where he studied insulin signaling and β-catenin's role in skeletal muscle glucose transport under Prof. Peter Shepherd and Assoc. Prof. Troy Merry. His work now investigates genetic influences on metabolic health and aging in collaboration with Prof. David James' lab. Research Interests: Genetic determinants of metabolic disorders Insulin resistance mechanisms Cellular trafficking in metabolism Genetic diversity in metabolic responses Publications highlight advancements in understanding insulin signaling pathways, lipid metabolism, and the development of tools like Synteny for gene prioritization. His studies leverage mouse models to explore diet-related metabolic changes and identify therapeutic targets. Advising and Grants: While no students are listed, his research has been supported by projects investigating genetic and dietary influences on metabolic health. Collaborative efforts with the James Lab focus on metabolic cybernetics and systems biology approaches. Labs/Teams: Active member of the James Lab at the Charles Perkins Centre, contributing to the Metabolic Cybernetics research group.

Alex Mogilnerمشاهده پروفایل

استاد

• Computational Biology
• Cell Biophysics
• Mathematical Biology
• +۵ مورد دیگر

Alex Mogilner is a Professor of Mathematics and Biology at New York University's Courant Institute and Department of Biology. His research focuses on computational and mathematical modeling of cellular processes, including cell motility, mitosis, actin dynamics, and galvanotaxis. He collaborates closely with experimentalists to bridge theoretical and empirical cell biology. Education: Ph.D., Applied Mathematics, University of British Columbia, Canada (1995) Ph.D., Physics, USSR Academy of Sciences (1990) M.Eng., Engineering Physics, Ural Polytechnic Institute, USSR (1985) Research Interests: Mathematical modeling of molecular machines in cells Mitotic spindle dynamics and chromosome segregation Actin-myosin contraction mechanisms Galvanotaxis and electrotaxis in cell migration Cellular biophysics and mechanochemical processes Selected Publications Highlights: Developed models for mitotic spindle assembly and error correction Investigated mechanisms of cell polarization and turning Studied actin network contraction and cytoskeletal dynamics Explored galvanotactic cell migration in electric fields Labs/Teams: Leads a computational modeling lab at NYU, collaborating with experimental groups globally in cell biology, biophysics, and systems biology.

Conrad Bessantمشاهده پروفایل

استاد

• Bioinformatics
• Computational Biology
• Artificial Intelligence in Biomedicine
• +۵ مورد دیگر

Prof Conrad Bessant is a Professor of Bioinformatics at Queen Mary University of London (QMUL), affiliated with the School of Biological and Behavioural Sciences. He leads the MSc Bioinformatics program and is academic lead of the UKRI AI for Drug Discovery Doctoral Training Programme. His research focuses on automating scientific discovery in biomedicine using AI, machine learning, and network science. Key areas include drug response prediction, kinase networks, and health data analytics from online forums. Research interests span data science, computational biology, and AI applications in healthcare. He has contributed to projects on tumor microenvironment analysis, proteomics, and biomarker discovery in rheumatoid arthritis. His work integrates multi-omics data with machine learning to identify therapeutic targets and predict drug responses. Recent grants include AI-driven omics data integration (BBSRC), biomarker studies in ALS (Barts Charity), and collaborations with pharmaceutical companies like Exscientia and Merck. Publications highlight contributions to automated cell identification, kinase network modeling, and health informatics. He has pioneered tools like MRMaid for proteomics and Galaxy workflows for transcriptomics-informed analyses.

• Circadian Rhythms
• Molecular Genetics
• Neurobiology
• +۱ مورد دیگر

Professor Ezio Rosato is a Professor of Biology at the University of Leicester's School of Biological Sciences. His research focuses on molecular genetics of circadian rhythms, examining biological clocks across diverse organisms from insects to crustaceans. Research investigates genetic and molecular mechanisms underlying circadian timekeeping, seasonal adaptations, and light-responsive behaviors. Current projects explore cryptochrome-mediated magnetosensitivity, circadian neuronal plasticity, and environmental influences on biological timing. Recent publications analyze ultrastructural changes in clock neurons, genetic regulation of seasonal phenotypes, and evolutionary dynamics of circadian systems. His work employs molecular genetics, behavioral analysis, and comparative genomics across model organisms. Professor Rosato collaborates internationally on chronobiological research and contributes to teaching programs in genetics and molecular biology.

David Donald Hansenمشاهده پروفایل

استاد

• Stem Cell Biology
• Developmental Biology
• Germ Line Development
• +۲ مورد دیگر

David Donald Hansen is Professor and Head of Biological Sciences at University of Calgary, leading research on stem cell regulation using C. elegans model systems. His work examines proteasomal control of germline development and balance between proliferation/differentiation decisions. Honored with multiple teaching awards including Killam mentorship and U Make a Difference awards. Research Focus: Genetic controls of germ line development in C. elegans Proteasome regulation of chromodomain proteins RNA-binding proteins in oocyte maturation

Roberto Bertolussoمشاهده پروفایل

مدرس ارشد

• Systems Biology
• Cancer Research
• Computational Biology
• +۳ مورد دیگر

Roberto Bertolusso is a Senior Pfeiffer Lecturer in the Department of Statistics at Rice University. He has held this position since 2013, focusing on teaching probability, statistics, and data science courses. His research integrates computational and systems biology approaches to study cancer mechanisms. Bertolusso earned his Ph.D. and M.S. in Statistics from Rice University and holds a graduate degree in Industrial Engineering from Universidad de Buenos Aires. His academic background includes significant contributions to cancer biostatistics and systems biology, highlighted by his participation in the AACR Methods in Cancer Biostatistics Workshop (2015) and a CPRIT-funded training program (2013–14). His publications span epidemiological modeling, orthopedic outcomes, and computational cancer research, reflecting interdisciplinary expertise. Education: Ph.D. & M.A. in Statistics, Rice University Graduate Level in Industrial Engineering, Universidad de Buenos Aires Teaching Focus: Probability theory, regression analysis, SAS programming, and data science methodologies. Research interests emphasize systems biology applications in cancer, stochastic modeling of biological systems, and computational methods for medical data analysis. His work bridges statistical theory with clinical and biomedical challenges, as seen in studies on viral infection dynamics and tumor growth modeling. Recent publications reflect both his cancer research and collaborative work in orthopedic surgery outcomes, showcasing a commitment to interdisciplinary problem-solving. Awards include recognition for methodological contributions to cancer clinical trial design and biostatistical training initiatives.

• Computational Immunology
• B Cell Receptor (BCR) Repertoire Profiling
• Multi-Omics Analysis
• +۵ مورد دیگر

Dr. Steven Kleinstein is the Anthony N. Brady Professor of Pathology at the Yale School of Medicine, with secondary appointments in Immunobiology and Biomedical Informatics. He is Co-Director of Graduate Studies in Computational Biology and Biomedical Informatics, and leads the Kleinstein Lab. His research focuses on computational immunology, integrating big data analysis with immunology to study immune responses, including B cell receptor (BCR) repertoire profiling via AIRR-seq and multi-omic studies of infection/vaccination responses. Dr. Kleinstein holds a BAS in Computer Science from the University of Pennsylvania (1994) and a PhD in Computer Science from Princeton (2002). He is a member of the Computational Biology and Bioinformatics Program and the Human and Translational Immunology Program. Education: B.A.S. in Computer Science, University of Pennsylvania, 1994 Ph.D. in Computer Science, Princeton University, 2002 Research Interests: His lab develops computational tools (e.g., Immcantation framework) for analyzing BCR repertoires and immune responses to pathogens like SARS-CoV-2, HIV, and influenza. Key projects include understanding germinal center B cell maturation, antibody specificity prediction via language models, and immune correlates of disease severity in hospitalized patients. Collaborations span clinical and basic science groups to apply these methods to autoimmune diseases, allergies, and cancer. Grants & Collaborations: Active in NIH/NIAID initiatives (e.g., HIPC, PRIME) and industry partnerships. Lab members collaborate with institutions globally on projects like the IMPACC study and malaria vaccine research. Labs/Teams: The Kleinstein Lab at Yale is part of the Center for Biomedical Data Science and the Yale Cancer Center, emphasizing computational and experimental immunology integration.

Yufei Huangمشاهده پروفایل

استاد

• Artificial Intelligence
• Cancer Research
• Bioinformatics
• +۳ مورد دیگر

Yufei Huang is a Professor in the Department of Medicine at the University of Pittsburgh and the Leader of AI Research at UPMC Hillman Cancer Center. He holds a PhD and MS in Electrical Engineering from Stony Brook University. His work bridges artificial intelligence, bioinformatics, and cancer research, focusing on applications such as drug response prediction, epigenetic regulation, and viral pathogenesis. Huang is affiliated with both the School of Medicine and the School of Computing and Information, reflecting his interdisciplinary research. His contributions span computational tools for healthcare, including R Shiny apps for drug response analysis and machine learning models for unbiased patient representation. Research interests include AI-driven oncology, molecular mechanisms of cancer progression, and leveraging genomics for precision medicine. He has contributed to studies on lung cancer therapeutics, viral infections (e.g., SARS-CoV-2 and KSHV), and epigenetic modifications like m6A methylation. His lab develops innovative algorithms for single-cell transcriptomics and spatial biology to unravel disease mechanisms. Notable projects include MetGen, a generative model for metastatic cancer prediction, and m6A-express, which deciphers RNA methylation's role in gene expression. His work on CASTOR1 phosphorylation highlights biomarker discovery in lung adenocarcinoma. Huang's interdisciplinary approach integrates machine learning, virology, and computational biology to address critical challenges in healthcare and cancer research.