Find Academic Supervisors

• Epigenetics
• Retroelements
• Transposable elements
• +5 more

Didier Trono is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Laboratory of Virology and Genetics (LVG) within the School of Life Sciences. Formerly, from 2004 to 2012, he served as the founding dean of EPFL's Faculty of Life Sciences, orchestrating its development and growth during this formative period. Trono received his medical education at the University of Geneva, followed by clinical training in pathology, internal medicine, and infectious diseases in Geneva and at Massachusetts General Hospital in Boston. His scientific career began at the Whitehead Institute of MIT, and in 1990 he was recruited by the Salk Institute of San Diego to launch an AIDS research center. After seven years in the United States, he returned to Europe and eventually joined EPFL. Dr. Trono's research has evolved significantly over his career. Initially focusing on virus-host interactions, he studied pathogens like HIV and Hepatitis B virus, creating HIV-derived genetic transfer tools that are now successfully used in gene therapy. For approximately the last fifteen years, his research has centered on epigenetics, particularly exploring the impact of retroelements and their control mechanisms on development and physiology of higher organisms, including humans. His laboratory investigates how transposable elements and KRAB zinc finger proteins regulate gene expression, with important implications for understanding cancer biology and developing new diagnostic and therapeutic approaches. Analysis of his recent publications (2022-2024) reveals a strong focus on transposable elements, KRAB zinc finger proteins, and their roles in gene regulation and cancer. His work combines molecular biology, genomics, and bioinformatics approaches to understand how these ancient viral remnants have been co-opted by the host genome to regulate development and cellular functions. The research spans basic molecular mechanisms to potential clinical applications in cancer diagnosis and therapy, with some recent work also addressing SARS-CoV-2 and immune responses. Throughout his career, Professor Trono has mentored numerous PhD students, including Bojkowska Karolina, Brandão Sanches Vong Martins Filipe Amândio, Bulliard Yannick, Coluccio Andrea, Corsinotti Andrea, Coudray Alexandre, De Tribolet-Hardy Jonas Caspar, and Dorschel Iris Arianna. His laboratory has received significant funding to support research at the intersection of virology, genetics, and epigenetics, contributing to EPFL's reputation as a leading institution in life sciences research. The Trono Laboratory continues to be at the forefront of research on retroelements and their regulatory mechanisms, maintaining a vibrant research environment that bridges fundamental biological questions with potential medical applications, particularly in cancer research and precision medicine.

• RNA Biology
• Myeloid Malignancies
• Hematology
• +4 more

Dr. Giulia Biancon is an Assistant Professor Adjunct in the Department of Medical Oncology and Hematology at Yale School of Medicine. She holds a PhD from the University of Milan (2019) and is a member of the Halene Lab, focusing on RNA biology and hematologic malignancies. Her research combines high-throughput methodologies to study RNA mechanisms in diseases like myeloid leukemias and splicing factor mutations. Education: PhD in Molecular Biology from the University of Milan (2019). Research Interests: RNA splicing, stress granules in cancer, epitranscriptomics, clonal hematopoiesis, and the interplay between genetic mutations and cellular pathways in blood cancers. Awards: 2024 Eclipse Award, 2022 ASH Abstract Achievement Award, and 2022 RNA Society Best Poster Award. Her work has been published in journals like Cell Reports , Blood , and Molecular Cell . Labs/Teams: Principal member of the Halene Lab and coordinator at the Yale Center for RNA Science and Medicine. Collaborates with institutions like the SeroNet network for immunology studies.

Ahmet AcarView profile

Associate Professor

• Cancer Biology
• Precision Medicine
• Drug Resistance Mechanisms
• +3 more

Dr. Ahmet Acar is an Associate Professor at the Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey. He leads the Cancer Precision Medicine and Drug Resistance Laboratory, focusing on understanding mechanisms of drug resistance in cancer. His research integrates experimental models, next-generation sequencing, and deep learning to address clinical challenges in cancer therapy. Dr. Acar holds a B.Sc. from METU's Biological Sciences department and a Ph.D. from the Cancer Research UK Manchester Institute. He completed postdoctoral training at the Institute of Cancer Research, London, and the University of Manchester. Research Interests: Drug resistance mechanisms, precision oncology, tumor microenvironment modeling, patient-derived organoids, computational pathology, and evolutionary cancer biology. His lab develops 2D/3D co-culture systems, PDO biobanks, and AI-driven histopathology tools to improve treatment strategies. Recent Work Trends: Recent publications emphasize tumor evolution modeling, matrix mechanics in drug resistance, and AI applications in histopathology. Collaborations with hospitals in Turkey and Europe support PDO biobank initiatives. His team explores evolutionary steering strategies to exploit collateral drug sensitivities. Labs/Teams: Precision Medicine and Drug Resistance Lab at METU focuses on interdisciplinary approaches combining wet-lab experiments with computational methods. Current projects include ex vivo tumor modeling and AI-driven diagnostic tools for oncology.

• Bioinformatics
• Genomics
• Cancer Genomics
• +7 more

Dr. Andre Kahles is a Lecturer in the Department of Computer Science at ETH Zürich, specializing in biomedical informatics. His research focuses on computational methods for analyzing large-scale genomic and transcriptomic data, with applications in cancer genomics, metagenomics, and precision medicine. He has contributed to the development of tools such as SplAdder for alternative splicing analysis, MetaGraph for petascale genomic data exploration, and SECEDO for subclone detection in cancer genomes. His work bridges algorithmic innovation with biological insights, addressing challenges in single-cell analysis, genome graph alignment, and multi-omics integration. Key research themes include: Developing scalable algorithms for processing nanopore sequencing and metagenomic data Characterizing somatic mutations and non-coding drivers in cancer genomes Advancing genome graph-based alignment and annotation methods Integrating multi-omics data for clinical decision-making and tumor profiling His publications span topics like RNA-seq analysis, chromothripsis in cancers, and global urban microbiome tracking through the MetaSUB consortium. Kahles has collaborated on landmark projects including the Pan-Cancer Analysis of Whole Genomes (PCAWG) and the Tumor Profiler Study.

• Mathematical Biology
• Cancer Evolution
• Computational Biology
• +4 more

Dr. Calum Gabbutt is a Chapman-Schmidt AI in Science Postdoctoral Research Fellow at Imperial College London's Department of Mathematics (Faculty of Natural Sciences) and a Postdoctoral Training Fellow at the Institute of Cancer Research (ICR), London. He holds a PhD in Mathematical Biology from Queen Mary University of London (2017–2021) and an MPhys from the University of Oxford (2013–2017). His research focuses on mathematical and computational methods to understand clonal dynamics and cancer evolution, particularly leveraging genomic and lineage tracing data. He develops Bayesian inference models to analyze evolutionary processes in cancer, aiming to improve clinical outcomes through precision medicine. Key areas include genetic barcoding, methylation-based molecular clocks, and phylogenetic reconstruction of tumor evolution. Recent work spans large-scale genomic analyses of cancer evolution, computational tools like PISCA-box for somatic chromosomal alterations, and studies on phenotypic plasticity in metastasis and therapy resistance. His research integrates AI-driven approaches to decode cancer heterogeneity and temporal dynamics in human tissues. Collaborations span institutions like the ICR and Queen Mary University of London, emphasizing interdisciplinary methods at the intersection of mathematics, computational biology, and oncology.

Simon CrouchView profile

Research Fellow

• Statistical Modeling
• Epidemiology
• Cancer Research
• +6 more

Simon Crouch is a Senior Research Fellow in Biostatistics at the University of York's Health Sciences department. With a strong mathematical background from Cambridge and Warwick, he leads the analytics team within the Epidemiology and Cancer Statistics Group and works closely with the Haematological Malignancy Research Network (HMRN) and Cardiovascular Health team. His work focuses on statistical modeling of complex epidemiological data related to hematological malignancies. University of Cambridge: MA, MMath in Mathematics University of Warwick: PhD in Mathematics University of Lancaster: MSc in Medical Statistics Dr. Crouch specializes in the statistical modeling of complex epidemiological data, with particular focus on hematological malignancies. His research encompasses predictive modeling, event history analysis, and machine learning applications in cancer epidemiology. He has made significant contributions to understanding myelodysplastic syndromes, lymphoma classification, and survival analysis in blood cancers through population-based studies. His work often involves collaboration with international registries including the European Myelodysplastic Syndromes Registry (EUMDS) and the Haematological Malignancy Research Network. Analysis of his recent publications reveals a strong focus on myelodysplastic syndromes (MDS), with particular attention to risk stratification, survival analysis, and treatment outcomes. His work increasingly incorporates genomic and molecular data to refine disease classification and prediction models. The trend shows progression from purely statistical methodology development toward integrated translational research that combines clinical, genomic, and epidemiological data to improve patient outcomes. Extensive publication record with 113 research outputs including 66 articles, 21 patents, and numerous meeting abstracts Active participation in major international research consortia including MDS-RIGHT and ImmunAID Significant contributions to the development of statistical methodologies for cancer epidemiology Dr. Crouch actively supervises PhD students in mathematical and statistical modeling applied to cancer epidemiology, with particular interest in time-to-event models, complex longitudinal models, and simulation techniques. His research has been supported through multiple projects, including the European Myelodysplastic Syndromes Registry and the MDS-RIGHT project focused on facilitating informed decision-making in hemato-oncology. He contributes to the Advanced Health and Social Statistics module for postgraduate students at the University of York.

Andrew BassettView profile

Researcher

• Genome Engineering
• Neurodegenerative Diseases
• Stem Cell Research
• +5 more

Dr. Andrew Bassett serves as Head of the Cellular and Gene Editing Research group at the Wellcome Sanger Institute, where he develops cutting-edge genome engineering techniques using human pluripotent stem cells to investigate neurodegenerative diseases including Alzheimer's and Parkinson's. His work focuses on scaling genetic screening approaches and improving CRISPR specificity for modeling complex disease mechanisms. His academic training includes: PhD at the MRC Laboratory of Molecular Biology (MRC-LMB) with Andrew Travers on chromatin remodelling in heterochromatin formation Postdoctoral research with David Baulcombe at the University of Cambridge studying small RNA roles in chromatin modification Additional postdoctoral work with Chris Ponting at the MRC Functional Genomics Unit (MRC-FGU) in Oxford, where he pioneered CRISPR applications in Drosophila Bassett's research program centers on developing advanced genome engineering methodologies for precise modulation of gene expression networks during development and neurodegeneration. His group specializes in creating complex editing events (SNPs, paired knockouts, enhancer perturbations) within iPSC-derived models, with particular emphasis on epigenetic regulation and transcriptional control. Current projects integrate single-cell 'omics and phenotypic assays to decode genetic causes of neurodegenerative disorders through the OpenTargets consortium. Analysis of his 15 most recent publications reveals dominant trends in CRISPR technology development (35%), neurodegenerative disease modeling (30%), and single-cell functional genomics (25%). His work consistently bridges methodological innovation with disease mechanism studies, increasingly incorporating multi-omics approaches and expanding into cancer immunology and infectious disease applications since 2022. As group leader, Bassett mentors postdoctoral researchers and PhD students while securing major funding for genome engineering initiatives. His team operates within the Sanger Institute's Cellular Operations division and maintains critical partnerships with the OpenTargets consortium for therapeutic target validation. The laboratory specializes in high-throughput screening platforms using iPSC-derived neural and microglial models, with recent methodological advances including scSNV-seq and ONE-STEP tagging systems that significantly enhance precision genome editing capabilities.

Lin YangView profile

Assistant Professor

• Reinforcement Learning Theory
• Learning for Control
• Non-convex Optimization
• +1 more

Lin Yang is an Assistant Professor in the Electrical and Computer Engineering Department at the University of California, Los Angeles (UCLA). His research focuses on reinforcement learning theory and applications, learning for control, non-convex optimization, and streaming algorithms. Education: PhD in Computer Science and PhD in Physics & Astronomy - Johns Hopkins University (simultaneously) Bachelor's degree in Math and Physics - Tsinghua University Research Interests: His work spans reinforcement learning theory and its applications, particularly in learning for control systems. He also investigates non-convex optimization techniques and streaming algorithms for efficient data processing. Scientific Awards: Dean Robert H. Roy Fellowship - Johns Hopkins University Previous Positions: Before joining UCLA, he was a postdoc at Princeton University working with Professor Mengdi Wang.

Martin PeiferView profile

Professor

• Computational Cancer Genomics
• Tumor Evolution
• Genome Instability
• +5 more

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

Nadya DimitrovaView profile

Assistant Professor

• Long Non-Coding RNAs
• Cancer Biology
• Molecular Biology
• +3 more

Nadya Dimitrova is an Assistant Professor in the Department of Molecular, Cellular, and Developmental Biology at Yale University, affiliated with the Yale School of Medicine. She holds secondary appointments in Genetics and is a member of multiple interdisciplinary centers, including the Center for RNA Science and Medicine. Her research focuses on long non-coding RNAs (lncRNAs) and their roles in cancer biology, particularly in tumor suppression and oncogenesis. Dimitrova earned her Sc.B. in Biochemistry from Brown University (2002), a Ph.D. from The Rockefeller University (2009), and completed postdoctoral training at MIT's Koch Institute. Notable awards include the HHMI Predoctoral Fellowship, Damon Runyon Postdoctoral Fellowship, and the 2023 Yale Cancer Center Class of '61 Award. Her lab explores lncRNA mechanisms using genomic and genetic tools, aiming to uncover their roles in cancer pathways. Recent work highlights lncRNAs' roles in metastasis, cardiac hypertrophy, and p53 signaling. Collaborations with researchers like Antariksh Tyagi and Clara Liao drive translational insights into RNA-based therapies. Education: Sc.B., Brown University (2002); Ph.D., The Rockefeller University (2009). Research interests include lncRNA regulation, cancer transcriptomics, and RNA-driven disease mechanisms. Her lab integrates systems biology approaches to dissect lncRNA functions in health and disease.

Yoon Seok KimView profile

Research Fellow

• Optogenetics
• Structural Biology
• Neuroscience
• +3 more

Dr. Yoon Seok Kim is a Postdoctoral Fellow at Stanford University’s Department of Bioengineering, focusing on structural and mechanistic studies of light-gated ion channels. He earned his Ph.D. in Bioengineering at Stanford, mentored by Drs. Karl Deisseroth and Brian Kobilka, with research centered on ion channel selectivity and optogenetic applications. Education: Ph.D. in Bioengineering, Stanford University Dr. Kim’s research spans Optogenetics , Structural Biology , and Neuroscience , particularly the molecular mechanisms of ion channels in neural and glioma contexts. His work includes structural analysis of potassium-selective channelrhodopsins and synaptic mechanisms in neurodegenerative diseases. Recent publications highlight interdisciplinary trends, merging Neuroscience , Molecular Biology , and Bioengineering , with subfields like diffuse midline gliomas , dopamine neuron resilience , and machine learning in protein engineering . His studies often integrate advanced imaging and optogenetic tools.

Cristian TomasettiView profile

Professor

• Cancer Etiology
• Mathematical Oncology
• Cancer Evolution
• +5 more

Cristian Tomasetti serves as Professor and Director of the Early Detection and Prevention Division at City of Hope's Beckman Research Institute, where he leads the Division of Mathematics for Cancer Evolution and Early Detection within the Department of Computational and Quantitative Medicine. His work bridges mathematical modeling with cancer biology to develop novel approaches for cancer detection and prevention. Dr. Tomasetti's research focuses on the mathematical foundations of cancer etiology, evolution, and early detection. His laboratory has pioneered algorithms for early cancer detection using cell-free DNA sequencing and protein data, developing some of the first multi-analyte blood tests capable of identifying cancer at its earliest stages. His work on cancer evolution has produced the most comprehensive mathematical models of tumorigenesis currently available, providing critical insights into mutation rates, driver gene requirements, and fitness advantages in cancer development. His influential research on the relationship between stem cell divisions and cancer risk has reshaped understanding of cancer etiology. The analysis of Dr. Tomasetti's recent publications reveals a consistent focus on liquid biopsy technologies, particularly circulating tumor DNA analysis for early cancer detection and monitoring. His work spans multiple cancer types including colorectal, pancreatic, ovarian, and bladder cancers, with a strong emphasis on translating mathematical models into clinically applicable diagnostic tools. The research demonstrates an evolution from theoretical models of cancer development to practical applications in cancer screening, risk assessment, and treatment monitoring. Dr. Tomasetti has established himself as a leader in the field of mathematical oncology, with his laboratory at the forefront of developing computational approaches to cancer prevention and early detection. His work on cell-free DNA testing has significant potential to transform cancer screening paradigms, moving toward less invasive and more effective methods for detecting cancer before symptoms appear.

Barbara MelloneView profile

Professor

• Centromere Biology
• Chromosome Segregation
• Genetics
• +4 more

Barbara Mellone is a Professor in the Department of Molecular and Cell Biology / Genetics and Genomics at the University of Connecticut. She leads the Mellone Lab, which focuses on understanding how genetic information is accurately passed from one cell generation to the next through the study of centromeres. Her research interests include: Centromere biology and function Chromosome segregation mechanisms Genetic and epigenetic regulation of centromeres Evolution of centromeres across species Using Drosophila melanogaster as a model system for chromosome studies Connections between chromosome segregation errors and human diseases like cancer Professor Mellone's recent publications demonstrate a strong focus on centromere structure and function, particularly examining CENP-A chromatin, centromere assembly factors like CAL1, and the evolutionary aspects of centromere biology. Her work combines genetic, molecular, and evolutionary approaches to unravel the fundamental mechanisms of chromosome inheritance. Her laboratory has made significant contributions to understanding how centromeres are built, maintained, and evolve, with implications for human diseases associated with chromosome segregation errors.

• Human Evolutionary Genetics
• Computational Biology
• Genotype/Phenotype Architecture
• +3 more

Timothy D. O'Connor is an Associate Professor in the Department of Medicine at the University of Maryland School of Medicine, serving as Co-Director for the Program in Health Equity and Population Health (HEPH). His research focuses on the evolutionary and population genetic influences on disease and phenotypic diversity, integrating evolutionary theory with large genomic datasets. He leads the O’Connor Evolutionary Genomics Group, emphasizing collaboration and multi-omics approaches. Education: B.S. Bioinformatics, Brigham Young University (2001-2007) Ph.D. Evolutionary Genetics, University of Cambridge (2007-2011), supported by the Gates Cambridge Scholarship Senior Research Fellow, University of Washington (2010-2013) Research Interests: Dr. O’Connor’s work spans human evolutionary genetics, computational biology, and genetic epidemiology. His lab develops novel algorithms to analyze large genomic datasets, with a focus on New World populations, including studies of Peruvian genomic dynamics, malaria parasite migration, and the evolutionary origins of phenotypic diversity. He emphasizes interdisciplinary collaboration and the application of evolutionary principles to modern biomedical challenges. Grants & Awards: NIH/NIAID R01 (2020-2025): $499,998 for malaria genomic migration studies in Cambodia/Thailand NIH/NIGMS R35 (2019-2024): $299,713 for evolutionary multi-omics research 2021 Faculty Mentoring Award 2019 Teacher of the Year Award Labs & Collaborations: His lab is part of the TOPMed Program, co-leading the Population Genetics Working Group. He also collaborates on projects like the Peruvian Genome Project and the Gynecological Cancer Center of Excellence. His work bridges academia and clinical practice, addressing disparities in genomic medicine through initiatives like the PENGUIN model for patient engagement.

Henry H.Q. HengView profile

Professor

• Genomics
• Evolutionary Biology
• Cancer Research
• +3 more

Dr. Henry H.Q. Heng is a tenured Professor of Molecular Medicine and Genetics and Pathology at Wayne State University , affiliated with the Karmanos Cancer Institute . His research spans genomics, evolutionary biology, and cancer systems theory. Education: PhD from University of Toronto (1994) Key research areas: Genomics, Evolutionary Biology, Cancer Research, Precision Medicine Dr. Heng's groundbreaking Genome Architecture Theory challenges traditional neo-Darwinism by emphasizing genomic topology and system inheritance over gene-level mechanisms. His team introduced the two-phased cancer evolution model (punctuated macroevolution followed by microevolution), explaining rapid cancer adaptation through genome chaos and non-clonal chromosome aberrations. Recent publications focus on karyotype coding , therapy-induced genome chaos, and the limitations of precision medicine approaches that ignore genomic heterogeneity. His work reveals how stress-induced genomic instability drives cancer evolution and drug resistance. 2020 PROSE Award Finalist for 'Genome Chaos: Rethinking Genetics, Evolution, and Molecular Medicine' Dr. Heng's lab develops innovative genomic techniques like high-resolution Fiber-FISH and investigates Gulf War Illness through genomic instability lens. He actively debates foundational issues in cancer research through books like 'Debating Cancer: The Paradox in Cancer Research' (2015) and 'Genome Chaos' (2019).