BioVis@ISMB 2025 Program

July 24, 2025

Invited Speakers

The Visual Genome: An attempt to classify multi-omics visualization

Kay Nieselt, University of Tübingen, Germany

Abstract: Over the past decades, advances in biology and medicine—driven by high-throughput and high-resolution experimental methods—have underscored the critical role of visualization in interpreting and communicating complex biological data. The interplay between life sciences and the visualization domain has revealed a deep and natural synergy, where visual analytics has become indispensable for discovery and insight.

In this talk, I will reflect on nearly 30 years of experience in developing visual analytics solutions for large-scale biological data, with a particular focus on multi-omics visualization. I will present a conceptual framework for classifying multi-omics visualizations and illustrate it through selected examples from tools developed by my research group. These range from genome-level visualizations to tools for exploring quantitative omics and epiproteomics data.

I will also introduce TueVis, a web-based resource developed and maintained by my group, offering interactive, user-friendly visualization tools spanning multiple omics layers. Designed for researchers in bioinformatics and the life sciences, TueVis aims to lower the barrier to high-quality data exploration and interpretation. The talk will conclude with a perspective on emerging challenges and opportunities in the evolving field of multi-omics visualization.

Speaker Bio: Kay Nieselt is a Professor of Bioinformatics at the University of Tübingen, where she leads the research group Integrative Transcriptomics. She earned her Ph.D. in Mathematics from the University of Bielefeld, Germany. During her doctoral work on modeling virus evolution, she began developing visual analytics methods for large-scale biological data—an area that would become a central theme of her research.

Her work spans a broad range of bioinformatics domains, including integrative analysis of genomics (with a focus on paleogenomics), transcriptomics, and other omics data types. She is particularly recognized for her contributions to the visualization of large-scale biological datasets and the application and development of machine learning methods for omics data interpretation. In 2012, her group was awarded the Illumina iDEA Challenge Award for the most creative algorithm handling large-scale next-generation sequencing data. Over the years, her team has developed numerous visual analytics tools tailored to multi-omics analysis, with a consistent emphasis on creating innovative yet user-friendly visualizations. These tools support diverse applications such as large-scale gene expression profiling, multiple genome alignments, pan-genome exploration, and integrative multi-omics data analysis.

Kay Nieselt has been actively involved in the BioVis community since its inception in 2011, serving on both the program and steering committees. She chaired the BioVis Special Interest Group (SIG) at ISMB in 2014 and 2015 and subsequently served as the spokesperson for the BioVis COSI.

Visual Data Analysis Research in Biomedical Applications: Navigating the Line Between Scientific Novelty and Practical Impact

Ingrid Hotz, Linköping University, Sweden

Abstract: Visualization has a long-standing tradition in biomedical research, yet its potential as a tool for data exploration and analytical reasoning remains underused. In this talk, I will share results and experiences from recent interdisciplinary collaborations in this area, including projects on molecular dynamics, electronic structure modeling, and hypothesis generation in medicine. In addition to presenting results, I will reflect on the challenges of working across domains, the sometimes slow but often rewarding process of building trust, and the tension between scientific innovation in both fields and real-world applicability. These reflections also raise broader questions about research sustainability: When is a project complete, and when is it time to move on

Speaker bio: Ingrid Hotz is a professor of scientific visualization at Linköping University in Sweden. She received her M.S. degree in theoretical physics from Ludwig Maximilian University in Munich, Germany, and her Ph.D. in computer science from TU Kaiserslautern, Germany. After a postdoctoral position at the Institute for Data Analysis and Visualization (IDAV) at the University of California, she started an Emmy Noether research group at the Zuse Institute in Berlin. She then served for several years as the head of the scientific visualization group at the German Aerospace Center (DLR). The main focus of her research lies in the area of data analysis and scientific visualization, encompassing both fundamental research questions and practical solutions to visualization challenges in applications including physics, chemistry and medical imaging, and mechanical engineering—from small- to large-scale simulations. Her work draws on ideas and methods from various fields within computer science and mathematics, including computer graphics, computer vision, dynamical systems, computational geometry, and combinatorial topology.

Program

TBA