Bertram Müller-Myhsok is a Research Professor and Research Group Leader at the Max Planck Institute of Psychiatry in Munich, Germany. His research focuses on statistical genetics and transcriptomic data analysis in psychiatric disorders, particularly major depression, PTSD, schizophrenia, and their treatment responses. He integrates machine learning with genetic and clinical data to develop predictive models and stratified treatment approaches. Professional activities include leadership roles in the International Max Planck Research School for Translational Psychiatry and collaborations with institutions like the Institut du Cerveau (Paris) and Bernhard Nocht Institute (Hamburg). His work spans genetic epidemiology, psychiatric genomics, and precision medicine, with over 400 publications in high-impact journals. Key research areas include identifying genetic risk factors for mental disorders, developing polygenic scores, and leveraging omics data to uncover disease mechanisms. He leads projects like Psych-STRATA, a Horizon Europe-funded initiative advancing personalized psychiatry through pharmacogenomics.
Yang Luo is a Kennedy Trust Senior Research Fellow in Data Science at the University of Oxford's Kennedy Institute of Rheumatology. His research bridges statistical genomics and computational immunology to unravel genetic contributions to immune-mediated traits, with a focus on the major histocompatibility complex (MHC) region. His work leverages large biobank datasets (UK Biobank, Biobank Japan), gene expression resources (GTEx), and proteomic data to decode molecular mechanisms linking genetic variation to disease risk. Specific interests include tuberculosis genetics, multi-ancestry polygenic risk scores, and single-cell eQTL modeling. Recent publications highlight expertise in HLA association studies, evolutionary immunogenetics, and disease-specific cell state dynamics. Key contributions include constructing a global HLA haplotype panel and developing novel statistical methods for admixed population genetics. Scientific Awards: Kennedy Trust Senior Research Fellow in Data Science His lab integrates computational and experimental approaches to translate genetic findings into clinical applications for immune disorders.
Jeremy Wang, PhD is an Assistant Professor in the Department of Genetics at the UNC School of Medicine . His research focuses on applying high-performance computational methods and machine learning to analyze high-throughput sequence data using long-read technologies (e.g., Oxford Nanopore) to advance precision personalized medicine . Key disease areas include Inflammatory Bowel Diseases (IBD) Respiratory Infectious Diseases His lab specializes in microbiome analysis , host-pathogen interactions , and computational genomics , working with collaborators in clinical, translational, and computational domains. His publications demonstrate expertise in long-read sequencing applications for Pediatric cancer classification SARS-CoV-2 genomic epidemiology Microbiome spatiotemporal dynamics Murine disease models Drosophilid genome assemblies Metagenomic bias analysis Collaborations span UNC and global institutions, with current work extending to clinical laboratory partnerships for pathogen sequencing and oral microbiome sampling methodology.
Dr. Christina Leslie is a Research Professor and Member of the Computational & Systems Biology Program at Memorial Sloan Kettering Cancer Center (MSK). She leads an active research laboratory focused on developing computational approaches to understand complex biological systems. Dr. Leslie earned her PhD from the University of California, Berkeley and has established herself as a leading computational biologist in cancer research and immunology. Computational & Systems Biology Program, Memorial Sloan Kettering Cancer Center Gerstner Sloan Kettering Graduate School of Biomedical Sciences Dr. Leslie's research focuses on developing novel computational methods to study cellular biological systems from a global and data-driven perspective. Her lab exploits diverse high-throughput functional and genomic data to understand molecular networks underlying fundamental cellular processes, including transcription regulation, pre-mRNA processing, signaling, and post-transcriptional gene silencing. Her algorithmic methods draw heavily on machine learning to build accurate predictive models from noisy and high-dimensional biological data. Key areas of interest include modeling cell-type specific transcriptional programs and dissecting co- and post-transcriptional regulation, particularly microRNA-mediated gene regulation. Analysis of Dr. Leslie's publication record over the last five years reveals a strong focus on computational approaches to cancer genomics, immunology, and epigenetics. Her work bridges multiple disciplines, with a particular emphasis on developing machine learning methods to interpret complex biological data. The publications demonstrate increasing sophistication in integrating multiple data types (genomic, transcriptomic, epigenomic) to understand cancer biology and immune responses. Recent work shows a growing emphasis on single-cell technologies and spatial analysis of tumor microenvironments. Introduction of string kernel methodology for SVM classification of biological sequences Development of algorithms for predictive modeling of gene regulation First systems-level analyses of competition between microRNAs and between target transcripts Dr. Leslie actively mentors numerous graduate students and research associates, with current lab members including Vianne Gao, Alireza Karbalaghareh, Erik Ladewig, and several others. Her lab has received significant research funding to support their work on computational approaches to cancer biology and immunology. The Leslie Lab maintains close collaborations with multiple experimental groups at MSK, facilitating the translation of computational insights into biological understanding. The Leslie Lab operates within the Computational & Systems Biology Program at MSK, with strong ties to both the research and clinical missions of the institution. The lab maintains state-of-the-art computational infrastructure for analyzing large-scale genomic and proteomic datasets and collaborates extensively with wet-lab researchers to validate computational predictions experimentally.
Ben Cosgrove is an Associate Professor in the Meinig School of Biomedical Engineering at Cornell University, serving as Director of Graduate Studies. His research focuses on systems bioengineering approaches to understand muscle stem cell dysfunction in aging and disease. He leads the Cosgrove Lab, a multidisciplinary group integrating biomedical engineering, stem cell biology, and systems biology to study microenvironmental signaling in muscle regeneration. His work includes developing biomimetic microenvironments for stem cell manufacturing and improving regenerative medicine therapies. Dr. Cosgrove holds a B.Eng. from the University of Minnesota (2003) and a Ph.D. in Bioengineering from MIT (2009). Postdoctoral training at Stanford University (with Dr. Helen Blau) followed. His research is supported by NIH grants (including R01, R21), the Glenn Medical Research Foundation, and others. He has been recognized with awards such as the BMES Graduate Research Award (2008), Rising Star Award (2015), and Swanson Teaching Excellence Award (2019). Research interests span bioengineering, biomechanics, computational science, and systems biology. His lab's innovations include spatial transcriptomic mapping and high-yield stem cell expansion platforms. Current projects aim to decode stem cell-niche interactions to treat muscle degeneration and aging. Grants: NIH K99/R00, R01, R21; Glenn Medical Research Foundation Labs/Teams: Cosgrove Lab (Cornell University) Future Work: Expanding applications of spatial transcriptomics and engineering regenerative therapies for muscle diseases
Tiffany M Jamann is an Associate Professor in Crop Sciences at the University of Illinois, where she holds the Monsanto Fellowship in Plant Breeding. Her research program focuses on understanding and improving disease resistance mechanisms in maize through integrated genetic, genomic, and phenotypic approaches. Dr. Jamann's work spans multiple disease systems with particular emphasis on foliar diseases such as Northern Leaf Blight and ear diseases like Gibberella ear rot. Her research interests include: Quantitative trait locus (QTL) mapping for disease resistance in maize Development of near-isogenic line populations for gene discovery Comparative studies of resistance mechanisms across different pathosystems Investigation of pattern-triggered immunity in maize Standardization of pathogen inoculation and disease rating methodologies Analysis of Dr. Jamann's recent publications (2023-2025) reveals a strategic integration of traditional plant breeding with cutting-edge genomic approaches. Her work demonstrates increasing use of comparative genomics and transcriptomics to identify host-specificity genes in pathogens while maintaining strong focus on practical breeding applications. A notable trend is her development of standardized methodologies for pathogen inoculation across multiple disease systems, enabling more reliable resistance evaluation. Monsanto Fellow in Plant Breeding Multiple publications featured in news outlets and academic discussions Active research with significant social media engagement (46 X users mentioning her work) Dr. Jamann's research program likely involves extensive collaboration with other plant pathologists and breeders, as evidenced by her numerous co-authored publications. Her work on multi-environment trials suggests substantial field research across different geographical locations. The development of specialized maize germplasm, including near-isogenic lines, indicates long-term investment in genetic resources for disease resistance research. Her laboratory maintains sophisticated capabilities for pathogen characterization, high-throughput phenotyping using fluorescence microscopy, and genetic mapping approaches. The emphasis on both fundamental plant-pathogen interactions and applied crop improvement demonstrates a research program that bridges basic science with practical agricultural outcomes.
Luca Sebastiani is a Full Professor in Horticultural Sciences (AGR/03) at Scuola Superiore Sant'Anna in Pisa, Italy, since 2014. He currently coordinates the PhD Course in AgroBioSciences and has previously served as Director of the Institute of Life Sciences (2016-2021). His academic career includes roles as Associate Professor (2002-2014) and Assistant Professor (1998-2002) at the same institution. PhD in Plant Biology from Scuola Superiore Sant'Anna (1996) MSc in Agricultural Sciences from University of Pisa (cum laude, 1991) Postdoctoral research in agricultural biotechnology (1996-1998) Research Interests: Focus on plant-environment interactions, particularly abiotic and biotic stress responses in crops. Key areas include: Physiological and molecular responses to climate change stressors Nutraceutical enhancement of food crops Plant germplasm conservation using molecular markers Agriculture 4.0 integrating AI, IoT, and robotics Phytoremediation using poplar and Brassica species Scientific Contributions: His work bridges molecular mechanisms (aquaporin function, heavy metal transport) with ecosystem-level applications (precision irrigation, contaminant phytoremediation). Recent publications emphasize genome sequencing, stress tolerance modeling, and nutraceutical food development. ISHS Medal for SapFlow Workshop organization (2011) Giovanni Spitali Foundation Award for PhD dissertation (1998) Collaborations: Extensive international collaborations with institutions like Beijing Forestry University, Comenius University, and Purdue University. Currently supervises projects in plant phenotyping, omics technologies, and sustainable crop management.
Hong Han is an Assistant Professor in the Department of Biochemistry & Biomedical Sciences within McMaster University's Faculty of Health Sciences and a member of the Centre for Discovery in Cancer Research (CDCR). She holds a Canada Research Chair and leads the Han Lab, which focuses on cancer biology, RNA regulation, and innovative high-throughput technologies for therapeutic discovery. Dr. Han earned her Ph.D. from the University of Toronto (2010-2016) and has established herself as a leading researcher in glioblastoma and alternative splicing regulation. Her interdisciplinary research integrates cancer biology, RNA science, and multilayer gene regulation to uncover mechanisms underlying cancer progression and treatment resistance. Her laboratory pioneers integrated technological platforms for large-scale genetic/drug screening and ultra-high-throughput single-cell profiling. The research focuses on three main areas: alternative splicing regulation in cancer (particularly glioblastoma and prostate cancer), multilayer mechanisms of glioblastoma heterogeneity and microenvironment evolution, and multiplexed screening approaches for therapeutic discovery in treatment-resistant cancers. Analysis of Dr. Han's recent publications reveals a strong emphasis on single-cell technologies to characterize glioblastoma heterogeneity, minimal residual disease states, and tumor-immune interactions. Her work increasingly bridges basic RNA biology with translational applications, particularly in developing novel therapeutic strategies targeting splicing networks and immune evasion mechanisms. Canada Research Chair Dr. Han teaches Advanced Techniques in the Biomedical Sciences (BIOCHEM 734). Her research program is supported by multiple funding sources, as evidenced by her extensive publication record in high-impact journals including Nature, Cell, Molecular Cell, and Nature Communications. She employs a comprehensive approach combining in vitro, in vivo, and patient cohort studies with cutting-edge genomic technologies. The Han Lab has developed innovative multiplexed screening platforms that enable simultaneous interrogation of thousands of conditions, ranging from CAR-T cells to small molecule therapeutics. This approach accelerates the discovery of novel cancer targets and therapeutic strategies for treatment-resistant cancers.
Kristina Schoonjans is an Associate Professor at EPFL’s School of Life Sciences, where she leads the Laboratory of Metabolic Signaling (UPSCHOONJANS). Her research focuses on the molecular mechanisms of bile acid signaling, nutrient sensing, and intermediary metabolism, particularly in the context of metabolic disorders such as obesity, fatty liver disease, and cancer. She investigates how the liver-gut-brain axis integrates metabolic signals through nuclear receptors and mitochondrial dynamics. Her research interests include: Bile acid signaling and its role as a hormonal regulator Nutrient and metabolite sensing in energy homeostasis Intermediary metabolism and metabolic disorders Role of nuclear receptors (e.g., TGR5, LRH-1) in liver, gut, and adipose tissue Mitochondrial dynamics and fission in metabolic regulation Organoid models for studying liver and intestinal metabolism Systems genetics using BXD mouse populations The most recent articles highlight a strong focus on bile acid signaling, particularly through TGR5 and LRH-1, in regulating metabolic health. Themes include the conversion of white fat to beige fat (beiging), hepatic tumorigenesis, mitochondrial fission, and the use of organoid and genetically engineered mouse models. There is a consistent emphasis on translational applications for obesity, fatty liver disease, and cancer. Scientific honors include: Windaus Prize from the Dr. Falk Foundation (2010, shared with Johan Auwerx) for the discovery of the signaling/endocrine function of bile acids Prof. Schoonjans actively supervises PhD students and has advised numerous doctoral candidates who have since completed their theses. Her lab is supported by multiple grants from Swiss and international funding agencies, including the Swiss National Science Foundation, EPFL, CONACYT, and the Foundation for Health and Education. She teaches in several doctoral programs at EPFL, including Life Sciences Engineering, and contributes to education through the SSV and EDBB/EDCB/EDMS-ENS programs. The Schoonjans Lab brings together scientists, doctoral assistants, and technicians working on projects related to metabolic signaling. The team uses advanced techniques such as genetically modified mouse models, organoid cultures, and multi-omics (metabolomics, proteomics, transcriptomics) to study the liver-gut and brain-liver axes. The lab has a strong track record of high-impact publications and collaborations with institutions worldwide.
Katherine J. Franz is a Professor of Chemistry at Duke University, affiliated with the Trinity College of Arts & Sciences and the Duke Cancer Institute. She holds a Ph.D. from MIT (2000) and a B.A. from Wellesley College (1995). Her research focuses on bioinorganic chemistry, particularly metal ion coordination in biological systems, with applications in antimicrobial therapies, cancer metallomics, and neurodegenerative diseases. Key projects include developing prochelators targeting fungal and bacterial pathogens, studying copper's role in antifungal drug efficacy, and designing light-activated metal complexes for controlled drug release. Dr. Franz has received numerous awards including the Camille Dreyfus Teacher-Scholar Award (2009), Sloan Research Fellowship (2008), and the NSF CAREER Award (2005). She leads a lab with 6 current students/mentees and has secured grants from NIH, NSF, and the US-Israel Binational Science Foundation. Her lab's work spans from fundamental metalloprotein studies to translational drug development, emphasizing interdisciplinary approaches in chemistry and biology. Education: Ph.D. in Chemistry, MIT, 2000 B.A. in Chemistry, Wellesley College, 1995 Research Interests: Metal homeostasis in pathogens, copper's role in antifungal resistance, prodrug design for targeted therapy, and mechanistic studies of metalloproteins. Grants: Tri-Institutional Molecular Mycology Training Program (NIH, 2024–2029) Duke PREP Biomedical Sciences Program (NIGMS, 2022–2027) Copper-Mucin Interaction Study (BSF, 2022–2026) Her lab's publications (n=15+ since 2020) highlight breakthroughs in prodrug selectivity, copper-induced protein toxicity, and histatin antifungal mechanisms. The Franz Lab actively collaborates with clinicians and computational scientists to advance therapeutic strategies addressing unmet medical needs in infectious diseases and cancer.
Professor Mirko Trajkovski leads the Laboratory of Metabolic Diseases at the Faculty of Medicine, University of Geneva. He completed his PhD at the International Max Planck School in Dresden (2005), followed by postdoctoral research at ETH Zurich, before establishing his lab at University College London (2012) and moving to Geneva (2013). His work focuses on adipose tissue plasticity , gut microbiota , and their roles in obesity , diabetes , and insulin resistance . Swiss National Science Foundation Professor (2014) ERC Starting Grant (2014) & Consolidator Grant (2019) Dr Walter Seipp Prize & Carl Gustav Carus Prize (2005) His lab investigates fat browning mechanisms , microbiota-host communication , and multi-tissue metabolic regulation using in vivo , in vitro , and human cohort approaches. Recent publications emphasize microbiome-based therapies , temperature effects on metabolism , and gut-bone-adipose crosstalk . Current advisees include PhD student Silas Kieser, with past members like Jing Xue, Salvatore Fabbiano, and Claire Chevalier contributing to immuno-metabolism and microbial engineering projects.
Caryl E. Sortwell is a Professor of Translational Neuroscience and Edwin A. Brophy Endowed Chair in Central Nervous System Disorders at Michigan State University's College of Human Medicine. She leads the Sortwell Lab within the Neuroscience Program and Grand Rapids Research Center, focusing on Parkinson's disease (PD) therapeutics. Education : B.S. in Psychology/Pre-medicine (University of Illinois, 1987), Ph.D. in Anatomy and Cell Biology/Neurobiology (University of Illinois at Chicago, 1994) Positions : Assistant/Associate Professor at Rush University Medical Center (1997-2005), Associate Professor at University of Cincinnati (2005-2009), Professor at MSU College of Human Medicine (2009-present) Her research investigates alpha-synuclein pathology in PD using preformed fibril models to study neurodegeneration, neuroinflammation, and therapeutic interventions. She explores neurotrophic factors like BDNF, gene therapies targeting CaV1.3 channels, and deep brain stimulation mechanisms. Her work emphasizes precision medicine approaches to optimize treatment outcomes. Scientific contributions include methodological advancements in neurochemical sensing with diamond electrodes and viral vector delivery systems. Key collaborations include research with Dr. Joe Patterson on alpha-synuclein genetic consequences. Technical Expertise : Immunohistochemistry, stereotactic surgery, in vivo neurotoxicant models, protein analysis (Western blot/ELISA), droplet digital PCR, and neuroinflammatory profiling
Gabriela V. Cohen Freue is an Associate Professor in the Department of Statistics at the University of British Columbia (UBC), Vancouver Campus, and holds a Canada Research Chair (CRC Tier 2). She leads an interdisciplinary research program focusing on developing robust statistical methodologies for analyzing high-dimensional data in genomics and proteomics, with applications in medical sciences. Her work addresses challenges such as outliers, collinearity, and measurement errors, with applications in biomarker discovery for diseases like multiple sclerosis, cardiovascular disorders, and asthma. Her academic journey includes collaborations across disciplines, including with the BC Cancer Agency, PROOF Centre of Excellence, and iCAPTURE. She has pioneered methods like the Penalized Elastic Net S-Estimator (PENSE) and contributed to proteomic data analysis tools such as the Protein Group Code Algorithm (PGCA). She also co-developed the MDQC quality control method for microarrays. Research interests include robust regression, biomarker development, and statistical methods for big data. Her team includes postdocs, PhD, and MSc students, with a focus on training in both statistical rigor and interdisciplinary collaboration. Notable grants include a CANSSI Collaborative Research Team Project (CRT) award for robust causal inference and prediction modeling. Teaching responsibilities span statistical consulting, high-dimensional biological data analysis, and generalized linear models. She emphasizes active learning and real-world problem-solving in her courses. Her lab’s work is supported by grants from the Data Science Institute (DSI) and collaborations with institutions like the PROOF Centre. Alumni of her group hold positions in academia (e.g., George Mason University) and industry (e.g., Merck, BC Cancer Research Centre).
Gustavo M. Silva is the Jack H. Neely Associate Professor of Biology at Duke University's Trinity College of Arts & Sciences, a position he has held since 2025. Previously, he served as Associate Professor of Biology (2024-present) and Assistant Professor of Cell Biology (2022-present) at Duke. His research is conducted through the Silva Lab (sites.duke.edu/silvalab), which focuses on molecular mechanisms of cellular stress response. Education: Ph.D. from University of Sao Paulo (Brazil), 2010 B.Sc. from University of Sao Paulo (Brazil), 2004 Dr. Silva's research centers on understanding how gene expression is regulated at transcriptional and translational levels during cellular stress. His lab specifically investigates how the ubiquitin system controls protein synthesis and degradation dynamics under stress conditions, which are critical for cellular physiology. His work has significant implications for understanding disease mechanisms where protein homeostasis is disrupted. The research combines biochemical, genetic, and proteomic approaches to dissect these complex regulatory networks. His publication record demonstrates a clear evolution from fundamental studies on redox regulation and proteasome function to more complex investigations of ubiquitin signaling in translation control and stress response. Recent work increasingly focuses on K63-linked ubiquitination's role in ribosome function and translation regulation, with growing emphasis on the clinical implications of these mechanisms in disease contexts including cancer. Scientific Awards & Recognition: Paul T. Englund Emerging Scholar Award (Johns Hopkins School of Medicine, 2024) Dean's Award for Excellence in Mentoring (Duke Graduate School, 2023) Science Diversity Leadership Award (Chan Zuckerberg Initiative, 2022) Best Professor Award (Vanderbilt Basic Sciences Juneteenth Committee, 2022) 100 inspiring Black scientists in America (CellPress, 2020) Dr. Silva actively mentors students at multiple levels, as evidenced by his Dean's Award for Excellence in Mentoring. His research is supported by substantial funding including NIH grants such as the Tri-Institutional Molecular Mycology and Pathogenesis Training Program (2024-2029) and 'Stalling cancer at the ribosome' from the V Foundation for Cancer Research (2025-2028). He also serves as Principal Investigator on multiple R01 grants focused on ubiquitin's role in translation control and stress response. The Silva Lab maintains strong collaborative relationships with institutions including the Chan Zuckerberg Initiative and ETH Zurich, and participates in several interdisciplinary training programs at Duke that support underrepresented students in biomedical sciences.
Istvan Albert is a Research Professor of Bioinformatics at Pennsylvania State University , affiliated with the Department of Biochemistry and Molecular Biology . He leads the Bioinformatics Consulting Center and teaches BMMB 852: Applied Bioinformatics . Research Interests: Specializing in bioinformatics, large-scale biological data analysis, microarray and sequence analysis, scientific programming, algorithm development, and database-driven web development. His work spans gene ontology visualization , RNA-Seq analysis , and coronavirus research . Software Development: Created GeneScape for gene function visualization and bio for bioinformatics workflows. Maintains the Biostar Handbook series and the Biostars Q&A Forum , a leading bioinformatics resource.
