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Abstract One challenge in the teaching of immunology is the complexity of the subject. Immunology presents a long list of unique cells, signaling molecules, receptor-ligand interactions, regulatory mechanisms, developmental pathways, and outcomes that can feel burdensome to instructors and unapproachable to students. The beauty of this subject, however, is that these unique features interact in networks that parallel those in other biological fields. Visualizing the interactions between tissues, cells, and molecules of the immune system and their outcomes can promote immunological literacy and a broad understanding of biological systems. Cell Collective (cellcollective.org) is an open-access, approachable software system that allows students and researchers alike to build models and perform simulations of biological processes. Students can use this interactive platform to probe cell-cell interactions, signaling pathways, metabolic networks, etc. while building systems thinking and computational skills, which are critical for success in STEM fields. After building models, real-time simulations can be run to visualize and understand the dynamics of the biological system under conditions of environmental pressure, disease, mutation, etc. Instructors can assess student knowledge by building assessments into modules in a formative or summative manner. Because it is free, user-friendly, and offers a host of pre-built training, educational and experimental modules, Cell Collective is ideally suited for use in all types of educational settings. Supported by a grant from the NSF (RCN-UBE) 2120806
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Visualizing Interaction Networks and Evidence in Biomedical Corpora
The abundance of scientific articles published and indexed in publicly accessible repositories has spurred the research and development of automated information extraction systems. The output of such systems can be used to assemble large networks capturing the understanding of mechanistic pathways and their interactions as represented in the underlying body of research. We describe a system designed to help researchers search, visualize and interact with biological networks derived via information extraction tools. As input, the system takes a dataset of biological and biochemical interactions automatically generated by an information extraction system and provides an interface designed to search, visualize and interact with the data. The usage paradigm consists of identifying a starting point for a search, then using the data’s network structure by incrementally exploring the immediate neighborhood of the elements displayed by the system.
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- Award ID(s):
- 2212130
- PAR ID:
- 10420445
- Date Published:
- Journal Name:
- 16th IEEE Pacific Visualization Symposium (PACIFICVIS)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/PacificVis56936.2023.00012
