Find Academic Supervisors

• Computational Biology
• Gene Expression Analysis
• Schizophrenia Research
• +5 more

Tade Souaiaia serves as Assistant Professor of Cell Biology at SUNY Downstate Health Sciences University's School of Graduate Studies. His research integrates computational biology with mental health investigations, focusing on gene expression dynamics in development and psychiatric disorders. He teaches graduate-level statistics and algorithm analysis courses delivered virtually via YouTube. Dr. Souaiaia's primary research centers on computational method development for multi-omics integration (gene expression, isoform-level data, microRNA, ChIP-Seq) to unravel schizophrenia etiology. His secondary research applies kinematic modeling to athletic performance (sprint/long jump), connecting cellular mechanisms with environmental training models. This dual focus bridges molecular neuroscience with practical biomechanics applications. Analysis of his 2020-2025 publications reveals three dominant research trajectories: (1) Psychiatric genetics through multi-ancestry studies of autism/schizophrenia, (2) Polygenic risk score innovation (notably BridgePRS for cross-ancestry portability), and (3) Primate neurogenomics investigating anxious temperament via orbitofrontal cortex and amygdala transcriptomics. His work consistently emphasizes translational applications of computational genomics to mental health. No scientific awards were documented in the provided materials. Dr. Souaiaia teaches Scientific Computing in Python (GRSC 6974) and Graduate Statistics (GRSC 0120), with virtual instruction accessible on YouTube. While specific grant details and student advising records are unreported, his laboratory actively develops computational frameworks for psychiatric genomics. His research program demonstrates strong interdisciplinary collaboration between neuroscience, psychiatry, and bioinformatics teams. He leads a research laboratory specializing in computational analysis of multi-omics datasets, with particular emphasis on primate brain tissue studies. The lab develops novel algorithms for integrating genomic, transcriptomic, and epigenomic data to model mental health disorders, maintaining active partnerships with neuroscience and clinical psychiatry research groups.

Maria BoftsiView profile

Professor

• Virology
• Infectious Diseases
• Molecular Biology
• +3 more

Dr. Maria Boftsi is a molecular biologist specializing in virology and infectious diseases. She holds a B.S. in Biology from Aristotle University (Thessaloniki, Greece) and a Ph.D. in Pathobiology from the University of Missouri-Columbia. Currently a faculty member at Stephens College, she combines teaching with research on viral-host interactions. Educational Background B.S. in Biology, Aristotle University Ph.D. in Pathobiology, University of Missouri-Columbia Research Interests: Dr. Boftsi investigates how viruses like parvoviruses, influenza, and SARS-CoV-2 manipulate host cellular mechanisms, particularly DNA damage responses. Her work employs techniques such as V3C and ChIP-seq. Teaching Experience: She has taught undergraduate courses including Clinical Microbiology , Principles of Cell Biology , and Human Biology at Columbia College, emphasizing accessibility for non-majors.

Peng LiuView profile

Professor

• Statistical Modeling for Microbiome Data
• RNA-sequencing Analysis
• Differential Expression Analysis
• +3 more

Peng Liu is a Professor at Iowa State University, specializing in statistical modeling and computational methods for microbiome and RNA-sequencing data analysis. His work spans plant genomics, stress response studies, and bioinformatics tool development. Developed software tools like C-REx and RiboZIP for genomic data analysis Key research areas: microbiome dynamics, differential translation, plant-pathogen interactions Collaborates with agricultural scientists to address drought tolerance and nutrient stress in crops His recent publications focus on advanced statistical approaches (e.g., hurdle Poisson models, variational inference) applied to multi-omics studies in sorghum and maize systems. He has contributed to understanding gene expression heterosis, ER stress responses, and microbiome impacts on plant resilience through peer-reviewed studies in journals like Bioinformatics, ISME J, and BMC Genomics.

Lionel B. IvashkivView profile

Professor

• Cytokine Biology
• Inflammatory and Autoimmune Diseases
• Macrophage and Stromal Cell Activation
• +4 more

Dr. Lionel B. Ivashkiv is a leading academic and physician-scientist, serving as Professor of Medicine and Immunology at Weill Cornell Medicine and holding dual leadership roles as Chief Scientific Officer at Hospital for Special Surgery (HSS) and Director of the David Z. Rosensweig Genomics Research Center at HSS. His research bridges basic science and translational medicine, focusing on cytokine signaling, epigenetic regulation of inflammation, and therapeutic targets for musculoskeletal disorders. Education : MD from Harvard Medical School, Residency at NYU/Bellevue Hospital, Fellowship at Brigham and Women's Hospital Dr. Ivashkiv's laboratory investigates how cytokines like IFN-γ, IFN-α, IL-10, and TNF regulate innate immune and stromal cell functions (macrophages, osteoclasts, synovial fibroblasts). Key themes include: Jak-STAT signaling crosstalk Epigenomic mechanisms in inflammatory gene expression Macrophage reprogramming (priming/tolerance) Autoimmune disease pathogenesis (rheumatoid arthritis, lupus) Translational genomics (RNA-seq, ChIP-seq, ATAC-seq) Precision medicine approaches for individualized therapies His team employs innovative methods combining bacterial artificial chromosomes (BACs) with CRISPR-Cas9 to study human autoimmunity-associated genes like A20/TNFAIP3 . Recent publications highlight discoveries in: Cytokine-driven inflammation in arthritis and implant failure Lipid metabolism regulation in T cells Novel strategies for preventing peri-implant fibrosis Interferon-γ and PGE2-cAMP axis interactions Epigenetic modulation of immune cell phenotypes Mechanosensing in plasmacytoid dendritic cells Scientific honors include election to the Association of American Physicians and American Society for Clinical Investigation , alongside multiple awards from the Arthritis Foundation and NIH . He leads multidisciplinary teams studying clinical challenges such as: Rheumatoid arthritis flares and therapy resistance Orthopedic implant aseptic loosening Total knee replacement complications Spine degeneration and pain

Yanxiang DengView profile

Assistant Professor

• Spatial Omics
• Single-Cell Analysis
• Microfluidics
• +3 more

Yanxiang Deng is an Assistant Professor in the Department of Pathology and Laboratory Medicine at the Perelman School of Medicine, University of Pennsylvania. His research pioneers spatial omics technologies to decode tissue architecture in development and disease, with seminal contributions including spatial-CUT&Tag and spatial-ATAC-seq for epigenetic mapping. His educational background includes a PhD from Rensselaer Polytechnic Institute (2018) followed by postdoctoral training at Yale University (2018-2022). Key appointments span Cell and Molecular Biology and Genomics and Computational Biology graduate groups. Deng's lab focuses on developing microfluidic platforms for spatial multi-omics, enabling pixel-level profiling of histone modifications, chromatin accessibility, and proteome-transcriptome interactions. His work bridges engineering and biomedicine to address cancer mechanisms and neurodegenerative disorders, with technologies allowing unprecedented resolution of cell-type-specific epigenetic landscapes in intact tissues. Analysis of his 15 most recent publications (2023-2025) reveals accelerating innovation in multimodal spatial mapping, particularly FFPE tissue compatibility, DNA methylation-transcriptome co-profiling, and neuroscience applications. His methods increasingly integrate chromatin features with proteomic data, expanding from foundational 2022 Science and Nature papers to clinical translation in depression and cancer. Major recognitions include: Blavatnik Awards for Young Scientists, Regional Laureate in Life Sciences (2023) Founders Award of Excellence, Rensselaer Polytechnic Institute (2015) National Scholarship (2008) He actively mentors 8 trainees including 6 graduate students and 2 postdocs, with research supported by NIH grants and institutional funding. His lab's deterministic barcoding approach (DBiT-seq), highlighted as Nature Methods' "Method of the Year," underpins multiple high-impact collaborations in immunology and neuroscience. The Deng Lab operates from Stellar Chance Laboratories, employing interdisciplinary teams to develop next-generation tools for spatial multi-omics. Current projects include Spatial-DMT for DNA methylation mapping and spatial-Mux-seq for quadruple-modality profiling, leveraging microfluidics expertise to unlock archival tissue repositories for disease research.

Rafet Al-TobaseiView profile

Associate Professor

• Bioinformatics
• Aquaculture Genetics
• RNA Sequencing
• +5 more

Dr. Rafet Al-Tobasei serves as an Associate Professor in the Department of Computer Science at Middle Tennessee State University (MTSU), where he applies computational methodologies to solve complex biological problems in aquaculture species. His research bridges computer science and genomics to address critical challenges in fisheries science and genetic improvement programs. His academic credentials include: Ph.D. in Computer Science, Middle Tennessee State University (2017) M.A. in Computer Science, Middle Tennessee State University (2011) M.S. in Computer Science, Middle Tennessee State University (2011) B.S. in Computer Science, Tennessee State University (2007) Dr. Al-Tobasei's research program focuses on developing and implementing bioinformatics tools for aquaculture genomics, with particular emphasis on rainbow trout and Nile tilapia. His expertise spans RNA sequencing analysis, Genome-Wide Association Studies (GWAS), Single Nucleotide Polymorphism (SNP) discovery, Long non-coding RNA (lncRNA) characterization, DNA methylation profiling, and Chromatin Immunoprecipitation Sequencing (ChIP-Seq) data interpretation. He investigates molecular mechanisms underlying economically important traits including muscle growth, fillet quality, disease resistance, and stress response. Analysis of his publication record reveals consistent thematic progression in aquaculture genomics: early work established foundational genomic resources for rainbow trout, followed by sophisticated GWAS applications for trait mapping, and recent integration of multi-omics approaches (transcriptomics, epigenomics, and lipidomics). His research increasingly emphasizes practical breeding applications, with significant contributions to genomic selection methodologies using reduced-density SNP panels and advanced statistical models. While specific awards and grants aren't documented in the source material, his extensive publication record in high-impact journals like BMC Genomics and Scientific Reports demonstrates substantial scholarly impact. His collaborative network spans multiple institutions and includes frequent co-authorship with leading aquaculture geneticists, indicating active participation in the research community and likely involvement in mentoring graduate students through research projects.

Wei LiView profile

Professor

• Computational Biology
• Epigenetics
• DNA Methylation
• +2 more

Wei Li is a Professor of Biological Chemistry at UC Irvine. His research bridges computational biology, epigenetics, and cancer genomics, emphasizing DNA methylation analysis and liquid biopsy development. He created the MACS algorithm for ChIP-seq analysis and leads NIH-funded projects on early cancer detection.

Stephen RamseyView profile

Associate Professor

• Computational Systems Biology
• Bioinformatics
• Precision Medicine
• +6 more

Stephen Ramsey, an Associate Professor at Oregon State University, holds dual appointments in the School of Electrical Engineering and Computer Science (College of Engineering) and the Department of Biomedical Sciences (Carlson College of Veterinary Medicine). With a PhD in Physics from the University of Maryland, his postdoctoral training in computational genomics at the University of Washington, and professional experience at the Institute for Systems Biology and Center for Infectious Disease Research, Ramsey bridges computational methods with biomedical applications. Education : Ph.D., Physics, University of Maryland; M.S., Physics, University of Maryland; Sc.B., Mathematical Physics, Brown University Ramsey specializes in computational systems biology , focusing on bioinformatics , biomedical knowledge graphs , and precision medicine . His research integrates machine learning , gene regulatory network modeling , and multi-omics data analysis to address challenges in rare disease diagnostics , drug monitoring , and inflammatory disease mechanisms . Current work includes AI-driven biomedical translation and electrochemical biosensor development for non-invasive diagnostics . Recent publications highlight knowledge graph applications in translational biomedicine , causal network inference in clinical-environmental data integration , and cross-species cancer transcriptomics . His team develops tools like RTX-KG2 and PloverDB to standardize biomedical data sharing and semantic reasoning . Scientific Awards : 2019 Zoetis Award (Carlson College of Veterinary Medicine) 2016 NSF CAREER Award 2016 PhRMA New Investigator Award 2010 NIH K25 Mentored Quantitative Research Award Ramsey advises in computational biology courses (CS 446/546) and contributes to biomedical AI through projects like mediKanren for rare disease diagnostics . His NSF-funded research explores gene expression noise and regulatory network dynamics , while NIH and PhRMA grants support his translational medicine initiatives. He leads the Ramsey Laboratory , which develops graph-based reasoning tools for biomedical data translation and multi-omics integration . The lab's work spans comparative oncology models, electrochemical biosensors , and knowledge graph infrastructure for clinical decision support .

Violaine Saint-AndréView profile

Researcher

• Computational Biology
• Immunology
• Epigenetics
• +3 more

Violaine Saint-André is a Researcher at the Institut Pasteur's Bioinformatics and Biostatistics Hub, where she leads computational biology research focused on immune response determinants through the Milieu Intérieur project. She holds a PhD in Molecular Biology/Genetics from Université Paris VI and an MSc in Bioinformatics from Université Paris VII. Her research investigates transcriptional regulatory networks, epigenetic mechanisms, and multivariate analysis of immune variability. Key interests include: Gene expression regulation and epigenetic memory of environmental exposures Determinants of human immune response heterogeneity Computational methods for multi-omics data integration Impact of smoking on long-term immune adaptation Her publications demonstrate strong focus on immunology and computational biology, with recent work uncovering smoking's persistent epigenetic effects on immunity and cytokine regulation. Research frequently involves high-dimensional data analysis across tuberculosis, COVID-19, and HIV contexts. She contributes significantly to academic training through courses at Institut Pasteur, Centrale-Supelec, and École Centrale de Nantes, covering ChIP-seq analysis, multivariate statistics, and health applications of AI. Actively participates in conference organization and student evaluation committees.

Jussi TaipaleView profile

Professor

• Gene regulation
• Transcription factors
• Systems biology
• +4 more

Jussi Taipale is a Professor of Medical Systems Biology at Karolinska Institutet and holds professorships at University of Helsinki. His research focuses on transcription factor binding mechanisms , cancer genomics , and gene regulatory networks . The interdisciplinary Taipale Lab operates across three international locations: Wellcome Sanger Institute (UK), Karolinska Institutet (Sweden), and University of Helsinki (Finland), with over 20 members including senior scientists, postdoctoral fellows, and graduate students. Ph.D., University of Helsinki (1996) Postdoctoral training: University of Helsinki, Johns Hopkins University Research spans transcription factor cooperativity , epigenetic regulation , chromatin accessibility , and noncoding mutation analysis . Key methodologies include HT-SELEX , CUT&RUN , ATI assays , and CRISPR-based functional genomics . The lab has significantly advanced understanding of Myc-driven oncogenesis , TF-nucleosome interactions , and dinucleotide specificity mechanisms . Notable discoveries include chromatin context-dependent enhancers , water-mediated DNA recognition , and novel composite transcription factor motifs . The group maintains active collaborations across Europe and has trained numerous alumni now leading academic and industry positions worldwide.

Kathleen E. SullivanView profile

Professor

• Epigenetics of inflammation
• Primary immune deficiencies
• Immunology
• +3 more

Kathleen E. Sullivan is a Professor of Pediatrics (Allergy/Immunology) at the Perelman School of Medicine, University of Pennsylvania , affiliated with the Children's Hospital of Philadelphia (CHOP) . Her research focuses on the epigenetics of inflammation and primary immune deficiencies , particularly examining enhancer-promoter interactions in systemic lupus erythematosus (SLE) using techniques like ChIP-seq and RNA expression analysis. Research Trends from her publications highlight: (1) epigenetic mechanisms in autoimmune diseases, (2) genetic basis of immune dysregulation, and (3) clinical-genomic correlations in 22q11.2 deletion syndrome. Her work bridges molecular immunology and pediatric clinical immunology . Contact: sullivank@email.chop.edu | Office: 267-426-2836

Kunal RaiView profile

Associate Professor

• Epigenetics
• Cancer Genomics
• Chromatin Structure
• +8 more

Kunal Rai, Ph.D., is an Associate Professor of Genomic Medicine at The University of Texas MD Anderson Cancer Center and an Adjunct Associate Professor in Bioengineering at Rice University. His work bridges epigenetics, cancer genomics, and translational medicine to advance precision oncology. Primary: Associate Professor, MD Anderson Cancer Center Adjunct: Bioengineering, Rice University Scientific Director, MDACC Epigenomics Therapy Initiative (METI) Dr. Rai’s research focuses on chromatin state changes in cancer progression, epigenetic therapy, and single-cell epigenomics. His lab has pioneered high-resolution epigenetic mapping in melanoma, colon cancer, and rare diseases like DSRCT and MPNST, leveraging machine learning and CRISPR-Cas9 editing to identify therapeutic opportunities. His recent work explores epigenomic stratification for patient-specific therapies, single-cell resolution aberrations, and higher-order chromatin structure disruptions. Articles span journals like Nature Communications , Cell Reports , and PNAS , highlighting cross-disciplinary impacts in cancer biology and epigenetic engineering.

• Cancer and Oncology
• Hematology
• Transcriptional Regulation
• +3 more

Urban Gullberg is a Professor at Lund University , affiliated with the Faculty of Medicine and the Division of Hematology and Clinical Immunology . He leads the research team on Transcriptional mechanisms for the Wilms’ tumor gene 1 (WT1) oncoprotein at the Lund University Cancer Centre (LUCC), focusing on the role of WT1 in leukemia pathogenesis. Research areas: Genome-wide binding of WT1 isoforms/mutants, transcriptional repression of tumor suppressors (e.g., IRF8), and mechanisms of leukemic cell proliferation. Methods: ChIP-Seq, promoter reporter assays, molecular profiling, and computational deconvolution of gene expression. Key findings: WT1 mutations disrupt transcriptional regulation, contributing to leukemia; identification of co-factors like ZNF224 and therapeutic targets. His work aligns with UN Sustainable Development Goals for cancer research. He supervises PhD students and participates in educational activities related to medical cell biology and targeted therapies.

Michael RosbashView profile

Professor

• Circadian Rhythms
• Gene Expression Regulation
• Neuroscience
• +3 more

Michael Rosbash is a Professor of Biology, the Peter Gruber Endowed Chair in Neuroscience, and an Investigator at the Howard Hughes Medical Institute (HHMI) at Brandeis University. His research focuses on circadian rhythms, gene expression regulation, and RNA processing in Drosophila and mammalian systems. Education : B.S. in Chemistry, California Institute of Technology Ph.D. in Biophysics, Massachusetts Institute of Technology Rosbash’s work has elucidated the molecular basis of circadian clocks, including the discovery of transcriptional feedback loops involving PER and CLK proteins. His lab employs advanced techniques like ChIP-seq and TRIBE to study clock gene targets, neuronal circuitry, and post-transcriptional regulation, including miRNA dynamics and splicing mechanisms. Scientific Awards : 2017 Nobel Prize in Physiology or Medicine 2013 Wiley Prize in Biomedical Sciences 2012 Canada Gairdner International Award 2011 Louisa Gross Horwitz Prize 2009 Gruber Neuroscience Prize His research has also expanded to sleep regulation, neuronal activity, and neurodegenerative disease models, with recent projects exploring light adaptation, miRNA turnover, and circadian neuron-specific transcriptomics. The lab continues to bridge molecular mechanisms with physiological outcomes in circadian biology.

Erik van NimwegenView profile

Professor

• Gene Regulatory Networks
• Genome Evolution
• Computational Biology
• +5 more

Prof. Dr. Erik van Nimwegen is a Professor at the Biozentrum of the University of Basel, where he leads a research group focused on computational and systems biology. His laboratory is housed in Room 08.012 at the Biozentrum, with contact information including phone number +41 61 207 15 76 and email erik.vannimwegen@unibas.ch. His administrative support is provided by Rita Ruppen and Jonila Vladi. Van Nimwegen's research centers on understanding the function and evolution of genome-wide regulatory networks. His group investigates how cells control gene expression using both theoretical and experimental methods, with particular interest in deciphering the genome's regulatory code, analyzing gene expression dynamics from single cells to genome-wide regulatory programs, and uncovering quantitative laws of genome evolution. His interdisciplinary approach combines computational predictions with experimental data to model regulatory networks across organisms from E. coli to humans. His work has significant implications for understanding cellular behavior, developing evolutionary theory based on measurable quantities, and potential applications ranging from taming pathogens to engineering human tissue. Analysis of his recent publications reveals a consistent focus on gene regulatory networks, with increasing emphasis on single-cell analysis, computational modeling of biological systems, and the evolutionary aspects of gene regulation. His work spans bacterial systems (particularly E. coli) to higher eukaryotes, with recent publications showing expansion into visualization techniques for single-cell data, cancer research related to RNA processing, and even virology with work on COVID-19 origins. A notable trend is the integration of multiple data types (multiomics) and the development of sophisticated computational tools for analyzing complex biological systems. Van Nimwegen's group has developed numerous software tools and web services for regulatory and comparative genomics, including ISMARA (Integrated System for Motif Activity Response Analysis), CRUNCH (for ChIP-seq data analysis), SwissRegulon database, Phylogibbs, and others. These resources reflect his commitment to creating practical tools that advance the field of computational biology. His laboratory operates as an interdisciplinary team with researchers from diverse backgrounds including theoretical physics, computer science, and molecular biology. The group actively recruits postdocs and engineers, as evidenced by a 2018 posting seeking researchers for computational analysis of bioimages. His work has established important theoretical frameworks for understanding gene regulatory networks and their evolution, with significant contributions to the field of systems biology.