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Francesco IorioView profile

Researcher

• Computational Biology
• Pharmacogenomics
• Cancer Biology
• +3 more

Francesco Iorio is a Research Group Leader in Computational Biology at Human Technopole (Milan, Italy), leading research in computational cancer pharmacogenomics and therapeutic target discovery. He holds a PhD from the University of Salerno and TIGEM (Naples), focusing on computational methods for drug discovery. Previously, he was a Senior Bioinformatician at EBI, leading CRISPR-Cas9 screen analyses across cancer cell lines to identify synthetic lethalities and therapeutic targets. He led the Cancer Dependency Map Analytics team at Wellcome Sanger Institute, developing algorithms for integrating large-scale cancer datasets. Since 2019, he serves as a Scientific Advisor to the Cancer Research Horizon–AstraZeneca Functional Genomics Centre. His research integrates computational methods with experimental data to uncover cancer dependencies, drug mechanisms, and biomarkers. Key contributions include tools like CRISPRcleanR for bias correction in CRISPR screens, and CELLector for selecting cancer cell line models. His work spans pharmacogenomics, functional genomics, and CRISPR technologies, with a focus on translating findings into clinical applications. Publications highlight advancements in CRISPR screen analysis, cancer dependency mapping, and drug repositioning. Current projects aim to advance precision medicine through computational frameworks for understanding tumor heterogeneity and therapeutic vulnerabilities.

Erin HeinzenView profile

Associate Professor

• Epilepsy Genetics
• Neurodevelopmental Disorders
• Genomics
• +3 more

Erin Heinzen is an Associate Professor at the UNC Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, with a joint appointment in the UNC Department of Genetics. She holds a Pharm.D. and Ph.D. from the University of North Carolina at Chapel Hill, followed by postdoctoral training at Duke University. Her research focuses on the genetic and genomic basis of epilepsy disorders, particularly somatic mutations and transcriptomic regulation in neurological diseases. Education: Pharm.D., University of North Carolina at Chapel Hill (2001) Ph.D., Pharmaceutical Sciences, University of North Carolina Chapel Hill (2004) Research Interests: Dr. Heinzen’s lab investigates somatic mutations in epilepsy and brain malformations, using induced pluripotent stem cells and advanced sequencing technologies. Key projects include studying SLC35A2 variants in intractable epilepsy and analyzing transcriptomic changes in brain tissue. Her work has identified 15 epilepsy genes, including the gene for Alternating Hemiplegia of Childhood. Grants & Awards: NIH-funded research, including $7M in collaborative grants to study genetic variants in epilepsy. Active in consortia like Epi4K and ILAE. Labs & Teams: The Heinzen Lab collaborates with neurology, neuropathology, and neurosurgery groups globally, advancing neurogenetics and treatment approaches for intractable seizures.

Yehuda Ben-ShaharView profile

Professor

• Behavioral Genetics
• Neurogenetics
• Insect Behavior
• +4 more

Yehuda Ben-Shahar is a Professor of Biology at Washington University in St. Louis, where he has served since 2008. His research integrates behavioral, genetic, genomic, and molecular approaches to investigate the genetic architectures underlying animal behavior, primarily using Drosophila melanogaster and honey bees as model systems. He maintains laboratory facilities at the Bayer Laboratory (Room 406) and conducts field research at the Tyson Research Center. Ben-Shahar earned his PhD from the University of Illinois at Urbana-Champaign. His research focuses on how specific genes in neuronal circuits govern behaviors like feeding and mating decisions, with significant contributions to understanding honey bee social behavior evolution. Recent work centers on the gut microbiome's role in nestmate recognition and developing genetic tools for non-model insects. His publication record reveals consistent innovation in behavioral genetics, with recent emphasis shifting toward microbial influences on social behavior and neural circuit analysis. Early work established foundational insights into gene-behavior relationships, while current research explores chemosensory mechanisms across insect and mammalian systems. Scientific recognition includes: Multiple Faculty of 1000 'Must read' designations (2002, 2007, 2009) Cover features in Science (2009) and Journal of Experimental Biology (2002) 'Mutant of the Month' in Nature Genetics (2006) Extensive media coverage including NPR, CBC Radio, and major newspapers Ben-Shahar mentors graduate students including Cassie Vernier (whose 2020 Science Advances paper defined gut microbiome roles in hive membership) and has supervised numerous undergraduates. His lab operates through collaborative grants supporting research at the intersection of genetics, neuroscience, and social behavior. The Ben-Shahar Lab maintains active research teams at the Bayer Laboratory for molecular work and the Tyson Research Center for honey bee studies, with recent projects involving cyborg locust development and odor-guided navigation research.

Matt WrightView profile

Lecturer

• Computer Music
• Acoustics
• Music Technology
• +7 more

Matt Wright is a Lecturer at Stanford University's Center for Computer Research in Music and Acoustics (CCRMA), specializing in media systems design and computer music research. He previously served as Musical Systems Designer at UC Berkeley's CNMAT (1993-2008) and Research Director at UCSB's CREATE center for eight years. His work focuses on real-time music synthesis, sound standards (SDIF/OSC), and computational ethnomusicology. He holds a PhD from Stanford CCRMA on musical rhythm perception, and contributed to the AlloSphere immersive audiovisual instrument. Education: PhD in Computer-Based Music Theory from Stanford University (completed at CCRMA). Earlier studies include training in traditional lutes and Afro-Brazilian percussion. Research interests bridge technology and music: developing tools for musical gesture analysis, sound synthesis, and cross-cultural music analysis. His recent work also involves genomic data platforms (ClinGen) for clinical variant curation, reflecting a dual focus on computational music and bioinformatics. Publications emphasize both music technology (e.g., EEG studies of piano duets) and genomics (e.g., ClinGen variant curation tools). He has advised students in electronic arts and contributed to genetic disease research through collaborative frameworks like ClinVar. Labs/Teams: Lead the CREATE Ensemble (technology-driven live performance) and contributed to the AlloSphere research instrument at UCSB's CREATE center.

LIU BoxiangView profile

Assistant Professor

• Genomics
• Bioinformatics
• Machine Learning
• +3 more

Asst Prof LIU Boxiang holds the position of Assistant Professor and NUS Presidential Young Professorship at the Department of Pharmacy and Pharmaceutical Sciences, National University of Singapore (NUS), within the Faculty of Science. His research focuses on integrating multi-omics approaches with computational methods to study complex diseases such as coronary artery disease and age-related macular degeneration. He specializes in developing statistical and machine learning tools for genomic analysis, including eQTL mapping and deep learning architectures for gene expression regulation. Education: BA in Biophysics (Illinois Wesleyan University), MS and PhD in Bioinformatics (Stanford University). He contributed to the GTEx consortium and is part of the Asian Immune Diversity Atlas (AIDA) initiative. His lab develops methods like ANTseq for ancestry determination and scPrediXcan for cell-type-specific transcriptome studies. Research Interests: Functional genomics, eQTL analysis, deep learning in biomedicine, and computational tools for omics data integration. His work bridges disciplines such as natural language processing and computer vision with biological questions. Scientific Awards: NUS Presidential Young Professorship (2021). His lab's innovations include ParaMed, a biomedical translation dataset, and LinearDesign for optimized mRNA stability. Advising and Grants: Leads the Liu Lab (boxiangliulab.com), focusing on single-cell genomics, mitochondrial dynamics, and computational biomedicine. Collaborates on projects like the RESET cohort study for cardiovascular disease prevention.

Yongjin ParkView profile

Assistant Professor

• Single-cell Analysis
• Immunology
• Epigenomics
• +3 more

Yongjin Park Yongjin Park is an Assistant Professor in the Department of Statistics at the University of British Columbia (UBC) . He is affiliated with the Causal Path Lab , focusing on computational biology and genomics. His research integrates statistical methods with large-scale genomic data to understand complex diseases like multiple sclerosis (MS) and Alzheimer’s, particularly through single-cell analysis and epigenomic studies. Affiliations: Faculty of Science, UBC; BC Cancer Research Research Interests: Single-cell RNA sequencing, immune cell dynamics, epigenomics, and regulatory genomics in disease contexts. Key projects include analyzing T-cell subtypes in MS patients and developing scalable computational tools for genomic data (e.g., CoCoA-diff, pseudobulk projection methods). His lab emphasizes translating genomic insights into clinical applications. Awards & Honors Data Science Award Dr. John and Barbara Petkau Scholarship Killam Graduate Teaching Assistant Award Margaret Wylie Memorial Scholarship in Statistics Lab & Collaborations The Causal Path Lab collaborates on projects involving Alzheimer’s disease progression, placental methylation, and cancer genomics. Recent work includes single-nucleus transcriptomic analysis of brain vasculature and epigenetic drivers of disease.

Tom RobinsonView profile

Lecturer

• Synthetic Biology
• Lipid Membranes
• Microfluidics
• +4 more

Dr Tom Robinson serves as a Lecturer in Chemical Engineering within the School of Engineering at the University of Edinburgh, specializing in the Bioengineering Research Institute. His interdisciplinary work bridges synthetic biology, membrane biophysics, and microfluidics to engineer biomimetic systems. His core research focuses on: Bottom-up Synthetic Biology : Constructing artificial eukaryotic cells with multi-compartment structures using droplet microfluidics and giant lipid vesicles (GUVs) to enable enzymatic cascades for biofuel production and drug delivery applications. Lipid Membrane Engineering : Developing model membrane systems (GUVs and nano-vesicles) to isolate and study membrane properties like permeability, fusion dynamics, and ligand interactions without cellular interference. Advanced Microfluidics : Designing novel microfluidic platforms for single-cell analysis (cancer cells, magnetotactic bacteria), high-throughput vesicle production, and precision manipulation of biomimetic structures. Analysis of Dr Robinson's 55+ publications reveals dominant trends in biomimetic membrane systems (42%), synthetic cell engineering (31%), and microfluidic device innovation (27%). His work increasingly integrates multi-omics approaches with physical manipulation techniques, particularly evident in recent studies on magnetotactic bacteria navigation and phase-separated synthetic cells. The research demonstrates strong translational potential in drug delivery and environmental microbiology. The Robinson Lab employs cutting-edge microscopy including FLIM, confocal, multiphoton, and high-speed imaging to characterize membrane dynamics and cellular interactions. Current projects focus on ESCRT-III protein-mediated vesicle remodeling, magnetic field effects on bacterial motion, and polymerizable emulsion systems for optical applications. The lab maintains active collaborations across bioengineering, microbiology, and materials science disciplines, with significant contributions to the MaxSynBio consortium for bottom-up cell synthesis.

Lucia BandieraView profile

Research Fellow

• Systems Biology
• Synthetic Biology
• Bioengineering
• +3 more

Dr. Lucia Bandiera is a Chancellor’s Fellow in Engineering Biology at the University of Edinburgh’s School of Engineering. Her research focuses on cybergenetic platforms to model and control biological systems, with applications in precision medicine and synthetic biology. She holds a PhD in Bioengineering from the University of Bologna (2013–2016) and has held postdoctoral positions at the University of Edinburgh’s Centre for Synthetic and Systems Biology. Key roles include Deputy Head of Graduate School (Postgraduate Experience) and Deputy Biological Safety Officer. Her academic qualifications include a BSc and MSc in Biomedical Engineering from the University of Bologna (2007–2012). She is an Associate Fellow of the Higher Education Academy (AFHEA, 2020) and has received prestigious funding such as the EPSRC Postdoctoral Fellowship (2017) and a tenure-track fellowship (2021). Her teaching includes courses on Lab-on-Chip Technologies and Engineering Principles. Research interests include mathematical modeling, optimal experimental design, and microfluidics. She leads projects like CONDSYC (EPSRC-funded), focusing on synthetic biology systems design. Her work spans biomolecular systems, cyber-physical platforms, and applications in liver disease and pandemic mitigation. Notable achievements include organizing the Institute for Bioengineering’s seminar series and contributing to datasets like Face coverings and respiratory tract droplet dispersion . Her lab develops tools for quantitative analysis of biological networks and precision medicine.

Ellis PatrickView profile

Associate Professor

• Bioinformatics
• Biomedical Data Science
• Statistical Bioinformatics
• +6 more

Associate Professor Ellis Patrick is an applied statistician and bioinformatician affiliated with the University of Sydney's School of Mathematics and Statistics, the Westmead Institute for Medical Research, and the Sydney Precision Data Science Centre. His research focuses on developing bioinformatics tools to analyze high-dimensional biomedical data, with applications in disease treatment, precision medicine, and understanding molecular drivers of conditions like Alzheimer’s, MS, and cancer. He holds a PhD from the University of Sydney and postdoctoral experience at Harvard Medical School and The Broad Institute. Education: PhD in statistical bioinformatics from the University of Sydney. Postdoctoral training included joint appointments at Brigham and Women’s Hospital, Harvard Medical School, and The Broad Institute of MIT and Harvard. Research Interests: Specializes in statistical bioinformatics, spatial omics, and high-dimensional data analysis, with emphasis on translational research in infectious diseases, organ transplantation, cardiovascular disorders, neurodegeneration, and oncology. His work combines computational methods with clinical data to uncover disease mechanisms and improve therapeutic strategies. Grants & Collaborations: Recent grants include PrecisionGO (MRFF-funded), White matter lesion transcriptomics (National MS Society), and studies on coronary artery disease and graft failure prediction. Collaborates widely with medical researchers, leveraging interdisciplinary teams to tackle complex health challenges. Labs & Teams: Leads the Bioinformatics Cluster at the Sydney Precision Data Science Centre, integrating computational and experimental approaches to advance precision health initiatives.

Roderic D PageView profile

Professor

• Taxonomy
• Biodiversity Informatics
• Phylogenetics
• +3 more

Professor Roderic D Page is a faculty member at the University of Glasgow, holding the position of Professor of Taxonomy (Evolution & Diversity) within the School of Biodiversity, One Health & Veterinary Medicine. His primary affiliation is with the Institute of Biodiversity, Animal Health & Comparative Medicine. He is based in Glasgow, Scotland, and can be contacted via email at Roderic.Page@glasgow.ac.uk or through his ORCID profile (0000-0002-7101-9767). Professor Page's research focuses on biodiversity informatics, taxonomy, and phylogenetics. He is a leading advocate for open science, particularly in improving access to taxonomic literature and integrating biodiversity data through knowledge graphs. His work includes projects such as BioStor (digitizing historical biodiversity literature), the Biodiversity Heritage Library (BHL), and initiatives to link persistent identifiers (e.g., LSIDs, DOIs, ORCIDs) across taxonomic databases. Key themes in his research include: Enhancing interoperability between biodiversity datasets Developing tools for phylogenetic visualization and analysis Addressing challenges in DNA barcoding and taxonomic classification Promoting open access to biodiversity data and legacy literature His recent work explores machine learning applications in taxonomy, the limitations of current data-sharing practices in phylogenetics, and the role of knowledge graphs in synthesizing biodiversity knowledge. He frequently critiques siloed approaches to data management and advocates for global collaboration in biodiversity informatics. Grants and funding for his research include support from initiatives related to the Biodiversity Heritage Library, the LOTUS project (open natural products research), and the Global Biodiversity Information Facility (GBIF). His contributions have advanced both computational methods and policy frameworks for biodiversity data integration. Professor Page is associated with the BioNames and BHL projects, and his lab focuses on bridging gaps between taxonomic databases, genomic data, and geospatial information. He actively participates in international efforts to standardize biodiversity data and improve accessibility for researchers worldwide.

Alexander R. PaciorkowskiView profile

Clinical Professor

• Neurogenetics
• Pediatric Neurology
• Congenital Disorders
• +3 more

Alexander R. Paciorkowski, M.D., is a Clinical Professor in the Department of Neurology at the University of Rochester School of Medicine and Dentistry. He specializes in Child Neurology and Neurogenetics, serving as part of the Neurogenetics Consultation Service, Hereditary Ataxia Program, and Neurofibromatosis Program. His clinical and research interests focus on neurogenetic disorders, pediatric epilepsy, congenital anomalies (e.g., Zika-related brain abnormalities), and improving access to neurology care in underserved regions. Education: MD from University of Connecticut School of Medicine (2000) Training: Pediatrics Residency (2000–2003) Medical Genetics Residency (2005–2007) Pediatric Neurology Fellowship (2007–2010) His research explores the economic impact of neurologic disabilities on families, bioinformatics tools for genetic data analysis, and genotype-phenotype correlations in rare disorders. He has contributed to over 78 peer-reviewed articles and co-authored chapters in Swaiman's Pediatric Neurology (2017), focusing on developmental encephalopathies and neurogenetics. Dr. Paciorkowski has received awards including the Derek Denny-Brown Young Neurological Scholar Award (2016) and the Kayden R. Vinson Distinguished Scholar Award (2014). His work extends to global health initiatives, with projects in Latin America and sub-Saharan Africa.

Deborah Dunn-WaltersView profile

Professor

• Immunology
• B Cell Biology
• Immunosenescence
• +4 more

Deborah Dunn-Walters is a Professor of Immunology and Associate Dean for Research and Innovation at the University of Surrey. She leads the Department of Biochemistry and Physiology within the School of Biosciences, Faculty of Health and Medical Sciences. Her research focuses on B cell development, immunosenescence, and antibody repertoire dynamics, with particular emphasis on responses to SARS-CoV-2 and other respiratory infections. Dunn-Walters pioneered tools like BRepertoire and sciCSR for analyzing immune repertoires using single-cell and computational methods. She chairs international B cell conferences and collaborates globally. Education includes a BSc (Hons I) and PhD, details unspecified. Her work integrates systems immunology approaches to understand age-related changes in humoral immunity, aiming to improve vaccine efficacy and combat pandemic threats. Awards include Fellowship of the Academy of Medical Sciences (2025). Research interests span regulatory B cells, metabolic regulation (e.g., thioredoxin’s role), tumor-infiltrating B lymphocytes, and antibody diversity in health/disease. She leads a lab developing novel methods for immune repertoire analysis, including web tools like VCAb for antibody structure exploration. Grants and advising are central to her role as Associate Dean, though specific grants aren’t listed. She oversees research innovation strategies and supports interdisciplinary collaborations. Her lab’s work has implications for cancer immunology, autoimmune disease, and infectious disease management.

Xiaofeng ZhuView profile

Professor

• Genetic Epidemiology
• Statistical Genetics
• Genetic Association Analysis
• +5 more

Xiaofeng Zhu, PhD is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine. He also serves as faculty at the Cleveland Institute for Computational Biology. His research focuses on developing statistical methods and computational tools for analyzing genetic and genomic data, particularly in the context of association analysis, admixture mapping, and rare variant identification. He leads the Continental Origins and Genetic Epidemiology Network (COGENT) consortium and has identified multiple genetic loci associated with blood pressure, sleep disorders, and Alzheimer's disease. Education: Ph.D. in Biostatistics, Epidemiology and Biostatistics, Case Western Reserve University (1998) M.S. in Statistics, University of Cincinnati (1994) M.S. and B.Sc. in Mathematics, Peking University (1989, 1986) Research Interests: Dr. Zhu's work emphasizes statistical genetics, including the development of methods to control population stratification, admixture mapping in admixed populations, and cross-phenotype association analyses. His lab integrates deep learning and bioinformatics to study complex traits such as cardiovascular disease, obesity, and sleep disorders. Recent efforts include analyzing whole-genome sequencing data to uncover rare variants influencing phenotypic variation. Publications Trends: His recent work spans Mendelian randomization methods (e.g., MRBEE), gene-sleep interaction studies, and multi-ancestry genomic analyses. Key themes include causal inference, pleiotropy analysis, and leveraging diverse genetic datasets to improve polygenic risk scores. Awards & Memberships: Fellow of the Royal Statistical Society Member, American Society of Human Genetics Member, International Genetic Epidemiology Society Advising & Grants: He has mentored 3 Master’s students, 9/10 PhD graduates, and 11/12 postdoctoral researchers. Notable mentees hold positions at Harvard, Mayo Clinic, and NIH. Active grants include studies on sleep health metrics, lipid loci discovery, and cardiovascular disease genetics. Labs & Teams: Leads COGENT consortium and collaborates with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. His lab develops software tools for ancestry inference, rare variant analysis, and epigenetic association studies.

Paula BrancoView profile

Assistant Professor

• Machine Learning
• Data Mining
• Data Science
• +8 more

Paula Branco is an Assistant Professor at the School of Electrical Engineering and Computer Science, University of Ottawa (since 2020). Previously, she was a PostDoctoral Fellow at Dalhousie University's Faculty of Computer Science (2019). She holds a PhD in Computer Science from the University of Porto, alongside a MSc in Data Mining and a Mathematics degree. She is an external researcher at INESC TEC's LIAAD laboratory. Her research focuses on Machine Learning, particularly utility-based learning and imbalanced domains, with applications in cybersecurity, healthcare, and environmental monitoring. Key areas include anomaly detection, fraud detection, rare event prediction, and spatio-temporal data analysis. Recent work emphasizes resampling techniques for imbalanced regression (e.g., SMOGN, ImbalancedLearningRegression Python package), evaluation metrics for imbalanced domains, and cybersecurity applications like intrusion detection and malware analysis. She has supervised seven graduate students and contributed to open-source projects like UBL (R package) and ImbalanceMetrics. Her teaching includes courses on databases and AI for cybersecurity. She actively publishes in top venues and collaborates on tools like SMOGN-LIDTA17 and NeighborhoodBiasResamplingRegression.

Rolf DanielView profile

Professor

• Metagenomics
• Metatranscriptomics
• Microbial Genomics
• +4 more

Prof. Dr. Rolf Daniel is Full Professor of Genomic and Applied Microbiology at the University of Göttingen, heading both the Department of Genomic and Applied Microbiology and the Göttingen Genomics Laboratory since 2012. He serves as Speaker of the North German Center of Microbial Genomics (NZMG) and previously directed the Institute of Microbiology and Genetics (2012-2016). His research pioneers cultivation-independent metagenomics and metatranscriptomics of environmental microbial communities from soil, sediments, ice, and biofilms. The lab employs dual function-based/sequence-based approaches to discover novel enzymes (proteases, cellulases, lipases) and genes, while conducting whole-genome sequencing of archaea/bacteria with industrial or pathogenic relevance. They also develop specialized bioinformatic tools for genomic data analysis and visualization. Recent publications reveal strong interdisciplinary trends: environmental microbiome responses to land-use changes (2018), viral genome evolution studies, and novel enzyme characterization from metagenomic libraries, spanning environmental science, medical microbiology, and industrial biotechnology. Scientific recognition includes: Norddeutscher Wissenschaftspreis (Northern German Science Award, 2013) No explicit details on student advising or grant funding were documented in source materials. Prof. Daniel directs the Göttingen Genomics Laboratory and the North German Center of Microbial Genomics (NZMG), driving collaborative research in microbial genomics across regional institutions through the GGNB graduate programs in Microbiology, Molecular Biology, and Genome Science.