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<b><i>"Multimodal Graph Representation Learning for Single-Cell Cancer Genomics"</i></b></div>
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<b>Xian F. Mallory</b></div>
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Department of Computer Science</div>
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Florida State University (FSU) </div>
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Please feel free to forward/share this invitation with other groups/disciplines that might be interested in this talk/topic.
<b>All are welcome to attend.</b></div>
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NOTE: <b>In-person attendance is requested </b>in our 499 Dirac Science Library (DSL) Seminar Room. Zoom access is intended for external (non-departmental) participants only.</div>
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<b>https://fsu.zoom.us/j/94273595552</b></div>
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Meeting # <b>942 7359 5552</b></div>
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<b>Wednesday, Oct 7, 2026, Schedule:</b></div>
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<div role="presentation">3:00 to 3:30 PM Eastern Time (US and Canada)</div>
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<div role="presentation">☕ Nespresso & Teatime - 417 DSL Commons</div>
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<div role="presentation"><b>3:30 to 4:30 PM Eastern Time (US and Canada)</b></div>
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<div role="presentation"><b>🕟 Colloquium - 499 DSL Seminar Room</b></div>
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<b>Abstract:</b></div>
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Single-cell sequencing makes it possible to characterize tumor heterogeneity at cellular resolution. However, each molecular modality has inherent limitations. Transcriptomic profiles of malignant and normal cells often overlap, copy number alteration (CNA)
signals are low resolution and not comprehensive, and single-nucleotide variations (SNVs) are largely unobserved in low-coverage sequencing. This talk presents a graph-based framework for integrating complementary modalities. Cells are represented as nodes,
one modality defines the node features, and a second modality defines the edge weights. A graph attention autoencoder then learns low-dimensional cell embeddings that jointly reflect both sources of information. Two applications of this framework will be discussed.
SCGclust performs subclone clustering on ultra-shallow single-cell DNA sequencing data by combining read-count-based CNA features with SNV-derived cell similarity. It consistently outperforms methods that rely on a single signal. DeepMalignant identifies malignant
cells in single-cell RNA sequencing data by combining expression signatures with CNA-derived cell similarity. Across 26 samples, four cancer types, and three sequencing platforms, it achieves the most favorable balance of precision and recall, and it generalizes
to spatial transcriptomics. Ablation analyses confirm that both the multimodal edge construction and the attention mechanism contribute to performance. </div>
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Additional colloquium details can be found here:</div>
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<a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2Fcolloquium%2Fcolloquium-with-xian-mallory-2026-10-07&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7Cca4d9b202f254058f77808df246e41fb%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639269728094282124%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=N5wNqOVtRdiTvb4eQh9TDmYiz1iUCd83WdHe%2Bbdagxk%3D&reserved=0" originalsrc="https://www.sc.fsu.edu/news-and-events/colloquium/colloquium-with-xian-mallory-2026-10-07">https://www.sc.fsu.edu/news-and-events/colloquium/colloquium-with-xian-mallory-2026-10-07</a></div>
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🎦 Colloquium recordings will be made available here:</div>
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<a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2Fseminars&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7Cca4d9b202f254058f77808df246e41fb%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639269728094304166%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=aksvvj1bUgz0yB7cIyWlyPv0HJP0t1ndg69lNGL2R%2B4%3D&reserved=0" originalsrc="https://www.sc.fsu.edu/news-and-events/seminars">https://www.sc.fsu.edu/news-and-events/seminars</a></div>
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