جست‌وجوی استاد و پژوهشگر

Nobuhiko Tokurikiمشاهده پروفایل

استاد

• Protein Evolution
• Molecular Biology
• Biochemistry
• +۴ مورد دیگر

Nobuhiko Tokuriki is a Professor in the Department of Biochemistry & Molecular Biology at the University of British Columbia's Faculty of Medicine. His research focuses on molecular mechanisms of protein evolution, exploring how mutations drive structural, biophysical, and functional changes in proteins over evolutionary timescales. Osaka University, PhD (2004) Weizmann Institute of Science, Postdoctoral Fellow (2004) University of Cambridge, Postdoctoral Fellow (2009) His interdisciplinary approach combines experimental evolution, protein engineering, structural biology, and bioinformatics to reconstruct evolutionary trajectories of biological molecules. Key questions include mutation order in functional transitions, evolvability determinants, and ongoing evolution of modern enzymes (e.g., drug resistance, xenobiotic degradation). Recent work emphasizes conformational dynamics, epistatic networks, and environmental interactions in shaping fitness landscapes. Publications highlight trends in β-lactamase evolution, promiscuous enzyme characterization, and computational-experimental synergy for exploring sequence-function relationships. The lab trains students in biochemical and biophysical techniques, with alumni placed in academic, industrial, and consulting roles. Current lab members include PhD candidates like John Chen (studying antibiotic resistance via deep mutational scanning) and technicians like Renmei Tang. The group collaborates on projects involving protein stability, metabolic engineering, and microbial community dynamics.

• Computational Biology
• Genetics
• Bioinformatics
• +۵ مورد دیگر

Harold Pimentel is an Assistant Professor in the Department of Computational Medicine at the University of California Los Angeles (UCLA) . His research spans computational biology, genomics, and bioinformatics, with a focus on RNA-seq quantification, CRISPR analysis, and deep mutational scanning frameworks. Key research contributions include the development of tools like kallisto and Rosace for transcript-level RNA-seq analysis, and studies on evolutionary DNA methylation conservation and cancer neoepitopes. His work integrates statistical modeling, algorithm design, and genomic data interpretation. Articles from 2025–2011 reflect trends in CRISPR, single-cell RNA-seq, gene regulation, and epigenomics, with keywords spanning Genetics , Computational Biology , and Machine Learning . Collaborative networks include institutions like UCSF and UCI, with co-authors such as James Fraser , Hiten Madhani , and Willow Coyote-Maestas .

Ryan Baldridgeمشاهده پروفایل

استادیار

• Protein Quality Control
• Membrane Biology
• ERAD (Endoplasmic Reticulum Associated Degradation)
• +۴ مورد دیگر

Ryan Baldridge is an Assistant Professor of Biological Chemistry at the University of Michigan Medical School. He leads the Baldridge Lab, which focuses on protein quality control mechanisms at cellular membranes. His research spans multiple programs including the Chemical Biology Program, Cellular and Molecular Biology Program, and the Protein Folding Diseases Initiative at the University of Michigan. Dr. Baldridge's research focuses on the fundamental mechanisms of integral membrane protein quality control systems, particularly endoplasmic reticulum associated degradation (ERAD). His lab studies how these systems recognize misfolded proteins and targets them for degradation, using Saccharomyces cerevisiae as a primary model system with complementary work in mammalian tissue culture. Current research directions include understanding substrate selection mechanisms in ERAD, investigating protein quality control at organelle membranes beyond the ER, and developing strategies for targeted protein degradation from cellular organelles. Analysis of Dr. Baldridge's publication record reveals a strong focus on membrane protein quality control systems, particularly ERAD. His work spans from fundamental mechanistic studies of ubiquitin ligases to applications in targeted protein degradation. Key themes include ubiquitin signaling, membrane protein biochemistry, and the relationship between lipid composition and protein quality control pathways. His research has important implications for understanding diseases related to protein misfolding including neurodegenerative disorders and cancer. Dr. Baldridge has received notable research support including a grant from the W. M. Keck Foundation to develop novel targeted protein degradation strategies for inhibiting viral biogenesis and infection. Dr. Baldridge has successfully mentored multiple graduate students to completion, including Dr. Devon Dennison (2023) and Dr. Brian Peterson (2023), who completed PhDs with theses focused on Golgi-localized Tul1 selective degradation and Hrd1 function respectively. His lab actively accepts new students and maintains collaborative relationships with several research groups including Kaushik Ragunathan's Lab at Brandeis University, and multiple labs at the University of Michigan Medical School. The Baldridge Lab operates as part of the University of Michigan's robust research ecosystem, with connections to the Department of Biological Chemistry, Program in Chemical Biology, Cellular and Molecular Biology Program, and the Protein Folding Diseases Initiative. The lab utilizes advanced techniques including single-molecule imaging, deep mutational scanning, and liposome reconstitution to study membrane protein quality control mechanisms.

Ulrich Stelzlمشاهده پروفایل

استاد

• Molecular Interaction Networks
• Functional Genomics
• Protein-Protein Interaction
• +۵ مورد دیگر

Ulrich Stelzl is a full Professor at the University of Graz , leading the Otto Warburg Laboratory for Molecular Interaction Networks . His research bridges genomics and proteomics to study how genetic variation and post-translational modifications influence protein interactions in diseases like cancer. He also serves as a faculty member at BioTechMed-Graz and heads the Department of Pharmaceutical Chemistry. Education: Technical University of Vienna (Technical Chemistry/Biochemistry), ETH Zurich, Max Planck Institute Berlin (PhD) His work combines high-throughput functional genomics , computational biology, and biochemical methods to map molecular networks. Key areas include deep mutagenesis for nucleotide-to-protein knowledge gaps, network biology for disease mechanisms, and phosphorylation/methylation effects on cellular phenotypes. Recent publications highlight his focus on yeast-based kinase arrays , ATGL lipid regulation , and polyamine metabolism in aging. His lab's 2024 studies on spermidine and autophagy represent major contributions to longevity research. Scientific Awards Erwin Schrödinger Award (2008) Stelzl advises PhD student Sarah Masser and collaborates with international teams. His lab explores subcellular protein dynamics through the DYNIMO project, integrating computational and experimental approaches.

Timothy Palzkillمشاهده پروفایل

استاد

• Antibiotic Resistance
• Molecular Basis of Antibiotic Resistance
• Small Molecule Inhibitors
• +۷ مورد دیگر

Dr. Timothy Palzkill is a Professor in the Department of Pharmacology and Chemical Biology at Baylor College of Medicine's School of Medicine. He leads the Palzkill Lab, which is housed in the Margaret M. & Albert B. Alkek Building at One Baylor Plaza. His research spans multiple departments including Biochemistry and Molecular Biology and Molecular Virology and Microbiology, reflecting the interdisciplinary nature of his work on antibiotic resistance and viral pathogenesis. The Palzkill Lab focuses on four primary research areas: (1) Understanding the molecular basis of antibiotic resistance, particularly focusing on β-lactamases that hydrolyze β-lactam antibiotics; (2) Developing small molecule inhibitors of antibiotic resistance enzymes using DNA-encoded chemical libraries and structure-based design; (3) Investigating MCR-1 mediated colistin resistance and developing inhibitors to restore colistin efficacy; and (4) Mapping norovirus epitopes through genomic phage display libraries to guide vaccine and diagnostic development. The lab employs diverse methodologies including phage display, next-generation DNA sequencing, molecular libraries, chemical synthesis, protein purification, enzyme kinetics, and X-ray crystallography. Analysis of Dr. Palzkill's recent publications reveals a strong emphasis on β-lactamase enzymes, particularly KPC and CTX-M variants, with significant work on understanding resistance mechanisms and developing inhibitors. His research increasingly incorporates DNA-encoded chemical libraries for drug discovery, with applications extending to antiviral development including work on SARS-CoV-2 protease inhibitors. The lab's norovirus research has made important contributions to understanding the human immune response to viral infections. Dr. Palzkill has mentored numerous graduate students who have gone on to successful careers in academia, industry, and clinical settings. Recent PhD graduates include Allison Judge (Postdoctoral Research Fellow at MD Anderson Cancer Center), Lynn Su (Scientist III at Solugen), and David Boragine (Application Engineer Specialist at 3M). His lab maintains an active research program with frequent publications and presentations at scientific conferences, as evidenced by recent student achievements in science communication competitions. The Palzkill Lab operates as a dynamic research environment utilizing cutting-edge technologies for studying protein structure-function relationships and developing therapeutic interventions. Current projects include developing inhibitors for carbapenemases like NDM, OXA-48, and KPC, investigating the structural basis of MCR-1 catalysis, and mapping norovirus epitopes to understand the humoral immune response during human infections. The lab's collaborative approach is evident in partnerships with the Center for Drug Discovery at Baylor and other research groups focused on antimicrobial resistance and viral pathogenesis.

Trevor Bedfordمشاهده پروفایل

استاد

• Computational Molecular Evolution
• Phylogenetics
• Infectious Disease Epidemiology
• +۵ مورد دیگر

Trevor Bedford, PhD , is a Professor at the Fred Hutchinson Cancer Research Center (Fred Hutch) across multiple divisions including Vaccine and Infectious Disease, Public Health Sciences, and Human Biology. He is also an Affiliate Professor at the University of Washington in the Department of Genome Sciences and Department of Epidemiology, and a Howard Hughes Medical Institute Investigator. His work bridges computational biology, genomics, and public health to combat infectious disease outbreaks. Education: PhD in Biology, Harvard University (2008) BA in Biological Sciences, University of Chicago (2002) Dr. Bedford specializes in computational molecular evolution , phylogenetics , and infectious disease epidemiology , with a focus on antigenic evolution and Bayesian statistics . His research develops tools to translate viral genomic data into actionable public health strategies, exemplified by the Nextstrain platform for real-time surveillance. Recent projects include analyzing SARS-CoV-2 campus transmission, refining influenza vaccine selection, and mapping mpox dynamics through genomic data. His scientific contributions have been recognized by his appointment as a Howard Hughes Medical Institute Investigator . He mentors students such as Sidney Bell (PhD candidate) and Allison Black (postdoc), fostering innovation in genomic epidemiology. At Fred Hutch, he leads the Bedford Lab , which integrates open science with computational methods to tackle global health threats.

Sven Diederichsمشاهده پروفایل

استاد

• Functional Genomics
• Cancer Mutations
• FGFR Family Signaling
• +۳ مورد دیگر

Prof. Dr. Sven Diederichs is a Tenured Full Professor (W3) and Division Head of the Division of Cancer Research at the Department of Thoracic Surgery , University Hospital Freiburg. He coordinates the DKTK Program 'Exploitation of Oncogenic Mechanisms' and leads the Center for Translational Cell Research (ZTZ). His work bridges high-throughput functional genomics with precision oncology. Education: PhD (Dr. rer. nat.) in Hematology/Oncology, University of Münster; Biochemistry, University of Witten/Herdecke and Eberhard-Karls-Universität Tübingen Postdoctoral Training: Harvard Medical School/Massachusetts General Hospital Cancer Center His research focuses on functional characterization of cancer-derived mutations , particularly in the FGFR family, to inform targeted therapies. He developed saturation mutational scanning libraries to map drug resistance/sensitivity across 30,000 mutations and explores non-canonical mutations like nonstop extensions and synonymous variants. Recent work highlights include comprehensive studies on RNA-dependent proteins (R-DeeP), lincNMR's role in nucleotide metabolism, and systematic analysis of mutation-driven tumorigenesis. These efforts aim to establish clinical decision support systems for precision oncology. Scientific Awards : FEBS Anniversary Prize (2016) Liver Cancer Research Award (2014) Dr. Hella Bühler Prize (2013) Binder Innovation Prize (2012)

Andrew Sungمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Cybersecurity
• +۷ مورد دیگر

Andrew Sung is a Professor at the University of Southern Mississippi (USM) in Hattiesburg, affiliated with the Chain Technology Center (TEC). His distinguished academic career spans over four decades, focusing on the critical intersection of machine learning and cybersecurity, with significant contributions to multimedia forensics and digital security. His educational background includes: PhD from Stony Brook University (1984) MS from University of Texas System Office (1980) BS from National Taiwan Normal University (1976) Professor Sung's research centers on applying machine learning to security challenges, with groundbreaking work in deepfake detection, malware analysis, and steganalysis. His publications demonstrate expertise in developing privacy-preserving techniques like machine unlearning, creating robust deepfake detection frameworks, and innovating Android security solutions. He has pioneered methods in moving target defense for software-defined networking and advanced forensic techniques for identifying digital forgeries in images and audio, addressing evolving threats in AI-generated content and network infrastructure. Analysis of his 15 most recent publications (2019-2024) reveals a dominant research trajectory toward combating AI-generated threats. His work increasingly focuses on deepfake detection through ensemble learning and dataset distillation, machine unlearning for privacy compliance, and sophisticated malware analysis techniques. This trend highlights his strategic pivot toward securing digital ecosystems against next-generation AI threats while maintaining strong foundations in traditional cybersecurity domains like network defense and steganalysis. No scientific awards were mentioned in available sources. Information regarding students advised or research grants was not provided in the available documentation. Professor Sung conducts his research at the Chain Technology Center (TEC) at USM, where he leads investigations into cutting-edge security challenges at the forefront of artificial intelligence and digital forensics.

Neil Kingمشاهده پروفایل

دانشیار

• Computational Protein Design
• Self-Assembling Protein Nanomaterials
• Vaccine Development
• +۴ مورد دیگر

Neil King, PhD , is an Associate Professor in the Department of Biochemistry at the University of Washington School of Medicine and Deputy Director of the Institute for Protein Design . His research focuses on computational protein design for creating self-assembling protein nanomaterials with applications in vaccine development , targeted drug delivery , and hybrid biomaterials . Education: PhD in Biochemistry (UCLA, Todd Yeates Lab) BS in Biomedical Engineering (Northwestern University) His research interests span: Developing atomic-level accurate nanomaterials using computational tools Next-generation structure-based vaccines for influenza and coronaviruses Membrane-interacting hybrid materials inspired by viral mechanisms Extending design capabilities to machine learning-driven platforms The article trends demonstrate a progression from foundational computational methods (Bale et al., 2016; Sheffler et al., 2023) to AI-enhanced vaccine platforms (2025 preprints) and hybrid biomaterials (Herpoldt et al., 2024; Butterfield et al., 2017). Key subfields include self-assembly algorithms , antigen presentation , membrane fusion systems , machine learning integration , malaria vaccine platforms , and deep mutational scanning . Neil leads a translational research group that combines de novo protein design with preclinical evaluation , supported by grants from the Open Philanthropy Project . His lab has mentored students like Priya (Distinguished Researcher award), Cameron Criswell (PhD graduate), and Cara Chao (PhD graduate).

• Computer Science
• Genetics
• Evolutionary Biology
• +۳ مورد دیگر

Tony Capra is an Assistant Professor of Computer Science at the Vanderbilt University School of Engineering , where he investigates intersections of computational methods and biomedical research. His work leverages advanced informatics to explore genetic and evolutionary questions with direct clinical relevance. Education: Ph.D. and M.A. in Computer Science from Princeton University; B.A. in Computer Science and Mathematics from Columbia University Dr. Capra's research program focuses on developing computational frameworks to address challenges in human genetics, evolutionary biology, and biomedical applications. His laboratory specializes in: Biomedical machine learning Evolutionary genomics Structural variant interpretation Electronic health record analysis Comparative 3D genome modeling Population-scale data integration His recent publications demonstrate increasing emphasis on cross-species evolutionary comparisons, structural biology applications, and clinical translation of genomic insights. Key methodologies involve machine learning at biobank scales and functional annotation of noncoding variation. Current affiliations include the Department of Computer Science and Biomedical Engineering at Vanderbilt, with research teams working at the interface of computational biology and clinical data science. Collaborative efforts span human genetics, primate genomics, and precision medicine initiatives.

• Alzheimer's disease
• tauopathies
• neurodegeneration
• +۶ مورد دیگر

Derek Hayden Oakley, M.D., Ph.D. , is Assistant Professor of Pathology at Massachusetts General Hospital and Harvard Medical School . Based in the Department of Pathology, his laboratory integrates human iPSC-based neuronal models, quantitative 3-D neuropathology, and machine-learning approaches to dissect mechanisms underlying Alzheimer’s disease and related tauopathies. Education & Training M.D. (Doctor of Medicine) Ph.D. (Doctor of Philosophy) Research Interests Dr Oakley’s work focuses on the molecular and cellular basis of neurodegeneration, particularly the pathobiology of tau protein and amyloid-β in Alzheimer’s disease. By leveraging patient-derived induced pluripotent stem cell (iPSC) neurons, he investigates post-translational modifications of tau and their influence on neuronal toxicity and propagation. His group also pioneers the application of machine-learning algorithms to high-resolution dissection photographs and surface scans, enabling objective, quantitative 3-D neuropathological analyses of human brain tissue. A complementary line of research examines the intersection of innate immune signaling—such as STING activation—with neurodegeneration in ALS and frontotemporal dementia. Overall, his studies bridge fundamental mechanistic work with translational biomarker discovery, aiming to accelerate clinical trial readiness in tauopathies and synucleinopathies. Publication Trends Between 2020 and 2025, Dr Oakley co-authored 48 peer-reviewed papers that collectively map the molecular landscape of tau, amyloid, and innate immunity in neurodegeneration. High-impact contributions include Nature (somatic mutations in Alzheimer neurons), Acta Neuropathologica (cryptic splicing signatures of TDP-43 dysfunction), and Science Translational Medicine (cholesterol homeostasis in the living human brain). These works underscore a trajectory from mechanistic discovery towards biomarker and therapeutic target validation. Scientific Awards & Recognition Specific honors are not detailed in the provided text. Research Funding & Collaborative Networks Dr Oakley is embedded in extensive collaborative networks (>100 co-authors) anchored by Massachusetts General Hospital and the Harvard NeuroDiscovery Center. He co-leads projects with Drs Bradley Hyman and Matthew Frosch, and participates in multi-institutional consortia such as the Pick’s Disease International Consortium. His work is supported by federal and foundation grants, though exact funding details are not listed. Laboratory & Affiliations Laboratory location: Massachusetts General Hospital, Pathology, WRN 245 55 Fruit Street, Boston, MA 02114, USA Phone: +1 617-726-1077

• Medical Image Analysis
• Computer-Aided Diagnosis
• Artificial Intelligence
• +۷ مورد دیگر

Samuel Armato is a Professor in the Department of Radiology-Basic Sciences at the University of Chicago. His research focuses on medical image analysis , computer-aided diagnosis , and artificial intelligence in medical imaging, particularly in computed tomography (CT) scans for lung cancer and mesothelioma . Armato has extensive experience in multi-institutional imaging projects , serving as the local principal investigator for the Lung Image Database Consortium and as Faculty Director of the University of Chicago’s Human Imaging Research Office . Education: Ph.D. in Medical Physics (1997), University of Chicago; B.A. in Physics (1987), University of Chicago His work spans radiomics , image quality assessment , and tumor response evaluation , with a strong emphasis on CT imaging for thoracic diseases. Recent publications highlight applications of deep learning to COVID-19 classification and radiomics-based differentiation of BAP1 mutations in mesothelioma. Armato also contributes to standardization of imaging criteria and quality assurance in clinical trials. Scientific Awards: iMig Advancement Award (2021) SPIE Fellow (2018) Academy of Radiology Research Distinguished Investigator (2016) AAPM Fellow (2014) Kurt Rossmann Teaching Award (2012, 2002) Raine Visiting Professor (2009) Armato has led NIH-funded projects such as Acuo PACS system , Computerized Analysis of Mesothelioma , and Standard Database for CT Lung Images . He collaborates on multidisciplinary teams and contributes to clinical trial imaging protocols and radiation therapy optimization .

Martin Heldمشاهده پروفایل

مدرس

• Biocatalysis
• Synthetic Biology
• Sustainable Chemical Manufacturing
• +۳ مورد دیگر

Martin Held is a Lecturer at the Department of Biosystems Science and Engineering, ETH Zürich. He holds a PhD in Biotechnology from ETH Zürich (2000) and has industrial experience through a biotech startup focused on biocatalyst manufacturing. Affiliation: Department of Biosystems Science and Engineering, ETH Zürich Research: Development of biocatalytic processes and synthetic biology tools for sustainable chemical production His research integrates interdisciplinary approaches across biocatalysis, synthetic biology, and chemical engineering to create eco-friendly industrial solutions. Recent work includes microbial indigo synthesis and defossilisation strategies for chemical manufacturing. 2025 Trends: Bio-based textile dyes, carbon feedstock alternatives 2023-2022 Work: Protein secretion optimization, antimicrobial engineering Contact: martin.held@bsse.ethz.ch

• Neuroimaging
• Alzheimer's Disease
• Neuroradiology
• +۹ مورد دیگر

Nasim Sheikh-Bahaei is an Assistant Professor of Clinical Radiology and Neurology at the Keck School of Medicine of the University of Southern California , where she serves as Medical Director of Radiology at Keck Hospital and Section Chief of Neuroradiology . Her work focuses on neuroimaging biomarkers for neurodegenerative diseases and dementias, particularly using advanced MRI and PET techniques to study amyloid, tau, and microvascular changes. Education: M.D. from Tehran University of Medical Sciences Ph.D. in Alzheimer’s disease imaging from University of Cambridge Research Interests: She integrates multimodal neuroimaging to investigate: Synaptic function in Alzheimer’s and its link to amyloid/tau MRS-measured neurotransmitter interactions with PET/tractography Microvascular alterations (cerebral microbleeds, perivascular spaces) in AD, migraine, and normal pressure hydrocephalus Development of automated software for perivascular space quantification Optimization of PET tracers and quantitative analysis systems 7T MRI studies on migraine microvascular/perfusion changes Publication Trends: Recent work emphasizes deep learning for MRI harmonization , perivascular space analysis as a vascular biomarker, synaptic/metabolic imaging , and CAA/pathology associations . Techniques span T1-weighted artifacts , 3D TSE-based flow suppression , and texture analysis for early dementia detection . Leadership & Collaborations: As a Co-Investigator in USC’s ADRC imaging core and member of Laboratory of Neuroimaging (LONI) , she leads projects on glymphatic system dysfunction in CSF flow disorders. Her research is funded by the National Institute for Health Research (NIHR) and institutional grants.

Kai Shimagakiمشاهده پروفایل

پژوهشگر

• HIV research
• virology
• immunology
• +۴ مورد دیگر

Kai Shimagaki is a Postdoctoral Associate at the University of Pittsburgh. His research focuses on HIV-1 evolution, coevolutionary processes between viruses and antibodies, and quantitative analysis of genetic interactions. He holds a Ph.D. from Sorbonne University (formerly Pierre et Marie Curie University), where his work centered on protein structure prediction and pathogen-immune system interactions. Education: Ph.D. in Computational Biology, Sorbonne University Research Interests: Quantitative analysis of viral evolution and immune system dynamics Computational modeling of fitness landscapes and epistasis Development of algorithms for deep mutational scanning and protein sequence analysis His work bridges virology, immunology, and computational methods to understand HIV adaptation mechanisms. Publications Overview: Recent work emphasizes HIV evolution modeling, epistasis detection, and computational tools for genetic fitness prediction. Key methods include Bézier interpolation, Boltzmann machine models, and higher-order covariance analysis. Scientific Awards: None listed. Advising & Funding: Supported by the Honjo International Scholarship Foundation during his Ph.D. No current advising roles noted. Labs/Teams: Affiliation details not specified in text.