جست‌وجوی استاد و پژوهشگر

• Microbiology
• Antimicrobial Resistance (AMR)
• Bacteriophage Therapy
• +۳ مورد دیگر

Dr. Carola Venturini is a Lecturer at the Sydney School of Veterinary Science, University of Sydney. Her research focuses on microbiology, antimicrobial resistance (AMR), and bacteriophage therapy with a One Health perspective. She holds a BSc (Hons) from the University of Trieste and a PhD in Molecular Biology from the University of Wollongong. Her work investigates mobile genetic elements in bacterial pathogens and explores bacteriophage applications in animal and human health. Education: BSc (Hons) in Natural Sciences, University of Trieste PhD in Molecular Biology, University of Wollongong Research interests include: Evolution of drug-resistant pathogens Horizontal gene transfer mechanisms Bacteriophage-based interventions Microbiome ecology and antibiotic impacts Recent work highlights bacteriophage translocation in human colonoids, Vibrio harveyi pathogenesis in fish, and MDR Klebsiella pneumoniae clonal spread. Her studies bridge animal, human, and environmental health sectors. Grants include projects on phage formulations for animal infections, AMR surveillance in India, and collaborations with institutions in Germany, UK, USA, and Italy. Labs/Teams: Collaborates with the Westmead Institute for Medical Research and maintains international partnerships through the Sydney Southeast Asia Centre and Charles Perkins Centre.

Robert Nobleمشاهده پروفایل

مدرس ارشد

• Cancer
• Evolutionary Biology
• Mathematical Biology
• +۷ مورد دیگر

Dr. Robert Noble is a Senior Lecturer in Mathematics at City St George's, University of London, specializing in the evolution and ecology of cancer . His research integrates mathematical modeling with computational biology to address four key themes: systematic understanding of somatic evolution, patient-specific tumor forecasting, treatment strategies leveraging evolutionary dynamics, and disentangling ecological contributions to cancer risk. Education: DPhil in Zoology (University of Oxford, 2014) Previous Appointments: Postdoctoral roles at ETH Zurich (2017-2020) and University of Zurich (2018-2020) His methodological toolkit spans agent-based models , stochastic processes , and Bayesian data analysis , with software contributions like the ggmuller and demon packages. Recent work focuses on universal tree balance indices for biological data comparison and adaptive therapy frameworks for clinical translation. Collaborations with experimental biologists and clinicians inform his research, which has produced key insights into spatial tumor evolution , drug resistance dynamics , and clonal diversity-survival relationships . He maintains active peer-review roles for journals like PLOS Computational Biology and Nature Ecology & Evolution.

Daniel Weissmanمشاهده پروفایل

استادیار

• Population Biology
• Ecology
• Evolution
• +۵ مورد دیگر

Daniel Weissman is an Assistant Professor at Emory University with a primary appointment in the Department of Physics and an associated faculty position in Biology. He is affiliated with the Program in Population Biology, Ecology, and Evolution and leads the Weissman Lab focused on theoretical approaches to evolutionary biology. Ph.D., Stanford University, 2010 BA, Harvard University, 2005 Weissman's research bridges theoretical physics and evolutionary biology, developing mathematical models to predict evolutionary outcomes. His work spans population genetics, spatial structure in populations, pathogen evolution, and genomic data inference. A central goal is to develop frameworks that translate genetic sequencing data into evolutionary predictions, with applications from antibiotic resistance to viral evolution. His research particularly investigates how functional and statistical interactions among genes affect evolution, the role of spatial structure in adaptation, and inferring microbial population dynamics. Analysis of Weissman's publication record from 2017-2024 reveals a progression from fundamental theoretical questions about adaptation and spatial structure toward more applied questions in infectious disease dynamics. His work consistently explores how spatial structure, recombination, and population heterogeneity influence evolutionary processes, with increasing attention to SARS-CoV-2 and bacterial pathogens like Staphylococcus aureus and Plasmodium falciparum. A notable theme is the investigation of how synchronized dispersal and sexual reproduction affect adaptation rates in structured populations. Weissman leads the Weissman Lab, located in the Math & Science Center N244 at Emory University. The lab focuses on building and analyzing models of biological populations to predict their future evolution, with particular emphasis on developing theoretical frameworks that can translate genomic data into evolutionary predictions. His research has received funding from the National Science Foundation, Simons Foundation, and Alfred P. Sloan Foundation.

Zamin Iqbalمشاهده پروفایل

استاد

• Genomics
• Microbial Genomics
• Plasmid Research
• +۵ مورد دیگر

Zamin Iqbal is a Professor of Algorithmic and Microbial Genomics at the Department of Life Sciences, Milner Centre for Evolution, University of Bath. His office is located in MILNER CENTRE 1.25, and he is currently accepting doctoral students for supervision. His research expertise spans multiple areas of microbial genomics, with particular focus on plasmid biology, antibiotic resistance mechanisms, and computational approaches to genomic analysis. His work contributes to understanding bacterial evolution, pathogenesis, and transmission dynamics of clinically important pathogens like Klebsiella pneumoniae and Mycobacterium tuberculosis . Professor Iqbal's recent publications demonstrate a strong trend toward developing computational methods for microbial genome analysis, with emphasis on plasmid epidemiology, phylogenetic compression algorithms, and metagenomic analysis. His work bridges the gap between theoretical computer science and practical microbiological applications, particularly in tracking antibiotic resistance transmission. His research contributes to multiple UN Sustainable Development Goals related to health and well-being. The fingerprint analysis of his work shows strong concentrations in plasmid research (100%), genomics (60%), Mycobacterium tuberculosis (45%), whole genome sequencing (43%), and related fields including metagenomics, serotyping, and antibiotic resistance mechanisms. Professor Iqbal maintains active collaborations across multiple international institutions, as evidenced by his co-authorship on studies involving researchers from numerous countries. His work has garnered attention across academic social media platforms, with multiple posts on X (formerly Twitter) and Bluesky, and has been referenced in Wikipedia pages related to his research areas.

Artem Kaznatcheevمشاهده پروفایل

استادیار

• Evolutionary Biology
• Theoretical Computer Science
• Computational Complexity
• +۵ مورد دیگر

Artem Kaznatcheev is an Assistant Professor at Utrecht University in the Department of Mathematics and Department of Information and Computing Sciences within the Science faculty. His research bridges theoretical computer science and evolutionary biology to analyze biological and social systems through an algorithmic lens. Current role since January 2023 Recruiting PhD students and postdocs Previously: James S. McDonnell postdoctoral fellow at University of Pennsylvania His work focuses on: Computational complexity of evolution Evolutionary game theory Algorithmic biology Mathematical modeling of cancer dynamics Cultural evolution of science Selected article trends show: Interdisciplinary integration of computer science and cancer biology Key themes: fitness landscapes, evolutionary games, treatment optimization 2021-2020 publications dominate Mathematical formalisms applied to biological and social phenomena Scientific contributions include: James S. McDonnell Foundation Independent Postdoctoral Fellowship 2019 Genetics paper on computational complexity as evolutionary constraint 2017 Nature Ecology & Evolution study on fibroblast-drug interactions in cancer Collaborative environments: Worked with Theory, Evolution and Games Group Previous affiliations: Oxford University, University of Pennsylvania, Moffitt Cancer Center, McGill University Developed teaching roles at Oriel College (Oxford)

• Immunogenomics
• Antibody Engineering
• Computational Biology
• +۴ مورد دیگر

Yana Safonova is an Assistant Professor in Computer Science and Engineering at the Huck Institutes of the Life Sciences , Pennsylvania State University. Her research bridges computational biology with immunogenomics. Immunoglobulin Gene Analysis Genome Assembly Methodology Antibody Diversity Bioinformatics Tool Development Her research focuses on immunoglobulin genetics , vertebrate genome assembly , and computational immunology . Recent work includes developing tools for IGH locus reconstruction and analyzing germline gene diversity in model organisms. Key publication trends reveal expertise in antibody engineering , genomic immunology , and bioinformatics pipeline development for immunosequencing and genome analysis .

Daniel Jeffaresمشاهده پروفایل

مدرس ارشد

• Leishmania Genomics
• Population Genetics
• Quantitative Genetics
• +۳ مورد دیگر

Dr. Daniel Jeffares is a Senior Lecturer in the Department of Biology at the University of York. His research focuses on Leishmania genomics, population genetics, and quantitative genetics, with an emphasis on understanding evolutionary processes and molecular biology in parasitic organisms. His work contributes to global health initiatives, including collaborations through the UK-Brazil Joint Centre Partnership in Leishmaniasis (JCPiLeish) and the PREV_PKDL project analyzing visceral leishmaniasis in East Africa. He leads the Jeffares Lab, which utilizes advanced genomic techniques to study parasite evolution and pathogenesis. Research Interests: Leishmania population genomics and drug resistance Genomic analysis of co-infections and pathogen diversity Evolutionary adaptations in trypanosomatids and extremophiles Applications of genomic methods in disease research Awards : Recipient of the Visiting Professorship (2022), recognizing his contributions to collaborative research and capacity-building in genomic methodologies. Grants & Collaborations: Principal Investigator on projects funded by MRC, Wellcome Trust, and NERC Leadership in multidisciplinary initiatives addressing visceral leishmaniasis in Sudan, Ethiopia, Uganda, and Kenya Active partnerships with institutions in Brazil and global health networks Labs/Teams: The Jeffares Lab at the University of York, part of the Biology Department’s research cluster focusing on microbial genomics and evolutionary processes.

Nicolas Rodrigueمشاهده پروفایل

دانشیار

• Molecular Evolution
• Bayesian Statistics
• Computational Biology
• +۳ مورد دیگر

Nicolas Rodrigue is an Associate Professor in the Department of Biology at Carleton University, with a cross appointment in Biology. He holds degrees from Bishop's University (BA), McGill University (BSc), École de technologie supérieure (MSc), and Université de Montréal (PhD). His research focuses on Bayesian modeling of molecular evolution, particularly protein-coding genes and evolutionary forces like mutation, selection, and drift. He also explores Markov chain Monte Carlo methods, protein structure modeling, and next-generation sequencing for viral/microbial evolution studies. Education: BA, Bishop's University BSc, McGill University MSc, École de technologie supérieure PhD, Université de Montréal Research Interests: Bayesian phylogenetic models Mutation-selection dynamics Protein sequence and structural evolution High-performance statistical computing Microbial genomics and clinical evolution Recent publications highlight advancements in phylogenetic modeling, adaptive evolution detection, and computational methods for analyzing molecular data. His work integrates statistical frameworks with evolutionary biology to address complex questions about genomic adaptation and sequence evolution. Awards: None explicitly listed. Advising/Grants: No student advising or grant details provided in the text. Lab/Teams: No specific lab or team affiliations mentioned.

• Biomedical Informatics
• Cancer Genomics
• Computational Biology
• +۳ مورد دیگر

Dr. Yi Qiao is a researcher in the Department of Biomedical Informatics at the University of Utah School of Medicine. His work focuses on integrating computational methods with genomic data to study cancer evolution, tumor subclonal dynamics, and precision oncology. Key contributions include developing tools like SubcloneSeeker, quickBAM, and Gene.iobio for analyzing genomic variants and clinical data. Education : PhD in Biomedical Informatics from Boston College BS from Zhejiang University Research Interests : Dr. Qiao's research bridges computational biology and clinical oncology. He develops innovative methods to dissect tumor heterogeneity using single-cell and bulk sequencing, with applications in drug response prediction and therapy selection. His work emphasizes understanding how subclonal populations evolve in cancers like leukemia and lung cancer, and how this informs targeted treatments. Key Projects : Framework for combining bulk DNA and single-cell RNA sequencing to study tumor expression (Genome Res, 2024) quickBAM API for high-throughput sequence analysis (Bioinformatics, 2023) ScreenDL deep learning model for drug response prediction (2024) Grants & Collaborations : His research is supported by collaborations with oncology teams and computational biology groups, focusing on translational applications of genomic data. Tools like Taxonomer and bam.iobio have advanced clinical diagnostics through real-time genomic analysis. Labs & Teams : He leads the Computational Oncology Lab, specializing in developing AI-driven tools for precision medicine. Active in cross-disciplinary teams at the University of Utah Health's cancer research initiatives.

Thomas Lengauerمشاهده پروفایل

استاد

• Computational Biology
• Bioinformatics
• Applied Algorithmics
• +۱۰ مورد دیگر

Prof. Dr. Thomas Lengauer is a leading figure in computational biology and applied algorithmics at the Max Planck Institute for Informatics, part of the Max Planck Society in Saarbrücken, Germany. He heads the Department of Computational Biology and Applied Algorithmics, where he drives research at the intersection of computer science, genomics, and medicine. His work integrates algorithm development with biological applications, particularly in viral genomics, epigenetics, and personalized treatment prediction. Research Interests: His research focuses on computational methods for analyzing complex biological data. Key areas include HIV and hepatitis virus evolution, antiretroviral therapy outcome prediction, DNA methylation and epigenomic analysis, machine learning applications in medicine, and the integration of big data in biological research. He has made significant contributions to understanding viral drug resistance and host-pathogen interactions through computational modeling. The recent publications (2019–2025) reflect a strong trend toward integrating temporal genomic data, machine learning, and public health surveillance. His work spans from fundamental algorithm development (e.g., RnBeads, MeDeCom) to applied clinical research (e.g., dolutegravir resistance, SARS-CoV-2 interventions). Key domains include epigenomics , virology , machine learning in healthcare , and biological database systems , increasingly incorporating AI-driven approaches. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: While no formal list of students is provided, Prof. Lengauer leads a large collaborative research group, evidenced by frequent co-authorship with researchers such as Walter, Bock, Müller, Kaiser, and Pirkl. He participates in major consortia (e.g., DEEP Consortium, Respiratory Virus Network), suggesting leadership in funded collaborative projects. His work is likely supported by Max Planck Society core funding and competitive third-party grants, though specific grants are not listed. Labs and Teams: He leads the Computational Biology and Applied Algorithmics group at the Max Planck Institute for Informatics. The team develops computational tools for epigenomic data analysis (e.g., RnBeads, DecompPipeline), viral resistance prediction, and public health modeling. The group collaborates extensively with clinical and biological researchers across Europe, functioning as a hub for interdisciplinary bioinformatics research.

• Genomics
• Bioinformatics
• Molecular Biology
• +۷ مورد دیگر

Martin Smith is an Assistant Professor at the Université de Montréal in the Department of Biochemistry and Molecular Medicine . His research focuses on harmonizing genomic technologies and artificial intelligence for precision medicine and functional genome annotation , particularly using single-molecule sequencing and computational biology approaches. PhD in Genomics from University of Queensland (2012) Postdoctoral work at Garvan Institute of Medical Research Director of Genomic Technologies Program at Kinghorn Centre for Clinical Genomics (2017) His research initiatives include transcriptomic profiling using real-time nanopore sequencing , with projects funded by the NSERC , FRQS , Génome Québec , and the Cole Foundation . He supervises M.Sc. student Kristina Atanasova and collaborates with interdisciplinary teams in pediatric acute leukemia and COVID-19 research. Research Highlights : Clonal and transcriptional landscape of lymphocytes Real-time classification of leukemias Evolutionary RNA structure analysis AI-enhanced immunopeptidomics High-resolution RNA sequencing methods Scientific Awards : CSIRO Pre-Incubator Performance Award Palmer Foundation Innovation Award Megabase DNA Sequencing Prize Robert Cedergren Bioinformatics Poster Prize Martin Smith is recognized for developing bioinformatics tools like DotAligner and SLOW5 , and will direct the Ramaciotti Centre for Genomics at UNSW Sydney starting 2024. His work bridges biotechnology and high-performance computing to advance precision medicine applications for conditions including Leishmania and acute leukemia .

Evan Biederstedtمشاهده پروفایل

پژوهشگر

• Computational Biology
• Cancer Genomics
• Bioinformatics
• +۳ مورد دیگر

Evan Biederstedt is an Associate in Biomedical Informatics at Harvard Medical School, affiliated with the Gehlenborg Lab. He holds a Master of Science (MSc) and specializes in computational biology with a focus on cancer genomics. His work includes developing the Cell Annotation Platform (CAP) to enhance cellular state interpretation through metadata and molecular signature analysis. Biederstedt’s research spans single-cell analysis, spatial transcriptomics, and genomic tools for structural variant discovery. His contributions include scaling cross-tissue annotation models and haplotype-aware somatic variation analysis. Key areas of focus include bioinformatics tool development, cancer genomics, and genomic data integration. He has collaborated on projects like the Virus Discovery Codeathon and international hackathons for genomic analysis. Biederstedt’s GitHub profile showcases his open-source contributions. His publications highlight advancements in tensor decomposition for patient cohort analysis, spatial transcriptomics, and pangenome strategies. Biederstedt’s work bridges computational methods with biomedical applications, emphasizing scalable solutions for complex genomic data challenges.

Matthias Stöckمشاهده پروفایل

پژوهشگر

• Evolutionary Genetics
• Sex Determination in Vertebrates
• Aquatic Ecology
• +۳ مورد دیگر

Matthias Stöck is a researcher at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB) in Berlin, Germany. He leads research on genetic and evolutionary processes in fish and other vertebrates , focusing on sex determination mechanisms, hybrid speciation, and environmental impacts on aquatic organisms. His work bridges molecular genetics and ecosystem-level dynamics. Research Themes: Evolution of sex chromosomes across vertebrates Environmental endocrine disruption effects Comparative genomics of fish and amphibians Biodiversity conservation in freshwater systems Key Article Trends: His recent publications analyze genomic responses to environmental stressors (e.g., synthetic androgens and estrogens), evolutionary patterns in hybrid and polyploid species, and conservation strategies for standing water ecosystems. Methodological contributions include the RADSex pipeline for sex determination studies. Projects: He leads the ODER~SO investigation into the 2022 Oder River environmental disaster and coordinates research on "Breaking the rules: modifications of sexual reproductive pathways in vertebrates" (2023-2026).

Dayton Wildeمشاهده پروفایل

استاد

• Molecular Genetics
• Ornamental Plant Breeding
• CRISPR Technology
• +۳ مورد دیگر

Dr. Dayton Wilde is a Professor in the Department of Horticulture at the University of Georgia , affiliated with the College of Agricultural & Environmental Sciences and the Institute of Plant Breeding, Genetics and Genomics . His research focuses on molecular genetics applied to ornamental plants, with expertise in gene editing, mutagenesis, and biotechnological approaches to improve floral traits. Key research areas include: Molecular Genetics of Ornamental Plants CRISPR Technology for Disease Resistance Genetic Transformation of Woody Species Bioinformatics in Plant Architecture Analysis Cryopreservation for Genetic Conservation Somatic Embryogenesis in Horticultural Crops Recent publications highlight advancements in gene editing systems for Gerbera, mutagenesis for disease resistance, and somatic embryogenesis for ornamental tree propagation. His work bridges molecular biology with practical horticultural applications.

Korbinian Schneebergerمشاهده پروفایل

استاد

• Computational Genetics
• Genome Plasticity
• Plant Genomics
• +۶ مورد دیگر

Prof. Korbinian Schneeberger is a full Professor of Computational Genetics and Genome Plasticity at the Ludwig Maximilian University of Munich , embedded within the Graduate School of Life Science Munich (LSM) . He leads a multidisciplinary team of bioinformaticians, biologists, and biotechnologists, all driven by a shared curiosity in genomic technologies and plant genome evolution. Contact: k.schneeberger@lmu.de . Research Focus: Genome plasticity and mutational dynamics across plant species Development and refinement of next-generation sequencing and assembly pipelines Comparative genomics, pan-genome construction, and structural variation Epigenetic regulation and transposon biology in plant genomes Meiotic recombination and crossover patterning in holocentric plants Application of single-cell and single-nucleus technologies to dissect gamete-level variation His laboratory develops widely-used bioinformatics tools—including SHOREmap , findGSE , SyRI , and plotsr —that enable the community to assemble, compare, and interpret plant genomes at unprecedented resolution. Recent work advances understanding of centromere evolution, adaptation to extreme soils, layer-specific somatic mutation patterns in fruit trees, and large-scale Arabidopsis population genomics. Scientific Output & Impact: Since 2015, Prof. Schneeberger has published more than 60 peer-reviewed articles, many appearing in top-tier journals such as Nature Genetics , Nature Plants , and Genome Biology . His 2025 studies already tackle the mutational landscape of Arabidopsis centromeres, scalable eQTL mapping in gametes, and the phased pan-genome of tetraploid potato, underscoring a trajectory at the forefront of plant genomic science. Funding & Collaborations: Research in the Schneeberger Lab is supported by multiple national and international grants, providing resources for high-throughput sequencing, computational infrastructure, and interdisciplinary training. The group actively collaborates with leading plant research centers worldwide, sharing data and tools to accelerate discoveries in crop improvement and evolutionary biology. Team & Environment: The lab operates as a vibrant, international environment with state-of-the-art wet-lab and computational facilities. Trainees and staff benefit from the rich ecosystem of LSM, including structured doctoral programs, career mentoring, and access to cutting-edge core facilities.