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| author: "Anastasia Bratulin" | ||
| date: 2026-07-16 | ||
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| title: "Reflections from ISMB 2026 in Washington, D.C." | ||
| url: /2026/07/16/2026-07-16-anastasia-bratulin-ismb-2026 | ||
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| # Reflections from ISMB 2026 in Washington, D.C. | ||
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| **_The_** [**_Open Bioinformatics Foundation (OBF) Event Fellowship program_**](/travel-awards) **_aims to promote diverse participation at events promoting open-source bioinformatics software development and open science practices in the biological research community. Anastasia Bratulin,_** _**a PhD candidate at**_ _**the Ohio State University**_, **_was awarded an OBF Event Fellowship to attend_** _**the**_ **_[ISMB 2026](https://www.iscb.org/ismb2026/home)_**. | ||
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| This July, I had the pleasure of attending the International Conference on Intelligent Systems for Molecular Biology (ISMB) 2026 in Washington, D.C., thanks to the event fellowship from Open Bioinformatics Foundation (OBF). As a well known conference in the field of computational biology and bioinformatics, ISMB brings together researchers from around the world to share advances in genomics, artificial intelligence, and biomedical data science. It was an exciting week filled with talks on how we can standardize data, use AI in our work, and share our findings in a way that is accessible. For a graduate student working in bioinformatics, BOSC (Bioinformatics Open Source Conference) was a great place to learn about the latest developments in biomedical databases, knowledge graphs, and data integration methods. The conference also provided an incredible opportunity to network with experts while seeing firsthand how the field continues to evolve. | ||
| I presented my own research, "Curating Gene Symbol Relationships for the Resolution of Gene Symbol Ambiguity" as a five minute talk in the joint BOSC/BOKR session and during the poster sessions. Gene symbol ambiguity is a challenge, when manually parsing literature and for the development and maintenance of biological datasets. My research focuses on annotating gene symbol aliases to improve genomic data quality, interoperability, and downstream analyses. Presenting this work sparked valuable discussions and it was encouraging to have conversations with others with the same problems as mine and hearing how my work is helpful to them. | ||
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| Throughout BOSC, speakers emphasized the importance of FAIR data, interoperability, genomic standards, scalable data integration, and reproducible computational biology. As biological datasets continue to grow, ensuring that data can be interpreted and reused across platforms has become as important as generating the data itself. It was encouraging to see so many researchers developing open standards and infrastructure that make collaborative science possible. | ||
| Three BOSC talks stood out to me because of how helpful they were to my own research. | ||
| The first was "KG-Registry: The Open Registry of Knowledge Graphs and Their Provenance," presented by J. Harry Caufield. Knowledge graphs are important for integrating diverse biomedical datasets, but finding appropriate knowledge graphs and understanding where their information comes from can be difficult. The KG-Registry addresses this challenge by creating an open registry that improves both discoverability and provenance. Documenting data sources and relationships is essential for building trust in integrated biomedical knowledge. | ||
| Another highlight was "Scalable Representation of Categorical Genomic Variation Using Cat-VRS," presented by Daniel Puthawala from Nationwide Children's Hospital. Cat-VRS extends existing genomic variation standards to better represent categorical and complex genomic variation in a consistent way. As someone whose own research focuses on standardizing ambiguous biological terminology, I found this presentation particularly relevant. Whether working with gene symbols or genomic variants, standardized representations reduce ambiguity, improve communication between databases (and people!), and enable more reliable computational analyses. | ||
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| The third talk I noted was "Canopy: An Open-Source Platform for FAIR Research Data Hubs," presented by Marcos Martínez-Romero from Stanford University. The presentation described Canopy, the open-source platform designed to help institutions build FAIR-compliant research data hubs. I enjoyed learning how Canopy simplifies the management and sharing of research data while encouraging collaboration across organizations. This kind of open infrastructure lowers barriers for researchers to help ensure that valuable datasets remain accessible and reusable long after individual projects are completed. | ||
| Overall, I learned about how the open-source computational biology community consistently evaluates and develops standards, creates tools to increase interoperability, and promotes open science. Additionally, how high-quality data annotation is a foundational step for artificial intelligence, which was also discussed from multiple perspectives. I'm grateful for the opportunity to present my work and attend ISMB 2026. I'm excited to continue developing methods that improve genomic data annotation and interoperability, and I look forward to seeing how these ideas continue to shape computational biology in the years ahead. | ||
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| ## Acknowledgements | ||
| Thank you to the [Wagner lab](https://www.nationwidechildrens.org/specialties/institute-for-genomic-medicine/research-labs/wagner-lab/wagner-lab-staff) at Nationwide Children's Hospital and the [Biomedical Sciences Graduate Program](https://medicine.osu.edu/education/phd/biomedical-sciences) at the Ohio State University for the support, as well as the [OBF](https://www.open-bio.org/)! | ||
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