NLM DIR Seminar Schedule

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UPCOMING SEMINARS

RECENT SEMINARS


The NLM DIR holds a public weekly seminar series for NLM trainees, staff scientists, and investigators to share details on current and exciting research projects at NLM. Seminars take place on Tuesdays at 11:00 AM, EST and some Thursdays at 3:00 PM, EST. Seminars are held in the B2 Library of Building 38A on the main NIH campus in Bethesda, MD.

To schedule a seminar, click the “Schedule Seminar” button to the right, select an appropriate date on the calendar to sign up, and then complete the form. You will need an NIH PIV card to access the “Schedule Seminar” page.

Please include seminars by invited visiting scientists in the NLM DIR seminar series. These need not be on a Tuesday or Thursday.

If you would like to schedule a seminar by a visiting scientist, click the “Schedule Seminar” and complete the form. Contact NLMDIRSeminarScheduling@mail.nih.gov with questions. Please follow this link to subscribe/unsubscribe to/from the NLM DIR seminar mailing list.

Titles and Abstracts for Upcoming Seminars


(based on the current date)

Jaya Srivastava
April 8, 2025 at 11 a.m.

TBD

Pascal Mutz
April 15, 2025 at 11 a.m.

TBD

Valentina Boeva, Department of Computer Science, ETH Zurich
April 18, 2025 at 11 a.m.

Decoding tumor heterogeneity: computational methods for scRNA-seq and spatial omics

Abstract. Characterizing and understanding drivers of tumor transcriptional and epigenetic heterogeneity is key to advancing personalized medicine and developing effective therapies. In this presentation, I will discuss our recent work on designing a computational methodology to extract gene signatures for distinct transcriptional states of cancer cells from single-cell RNA sequencing data (scRNA-seq) and show examples of linking intratumor transcriptional heterogeneity to tumor microenvironment and clinical variables. In this context, I will talk about the best-performing existing approaches for the integration of scRNA-seq data from malignant cells across cancer patients and also present our recently developed scRNA-seq-based CancerFoundation model, which, in addition to being capable of data integration across patients, can be used for predicting drug responses. I will conclude with our latest efforts in spatial transcriptomics and demonstrate how supervised machine-learning approaches that use spatial information can further resolve the complexity of cancer and provide explainable clinical biomarkers.

Bio. Prof. Dr. Valentina Boeva is a Tenure Track Assistant Professor at the Department of Computer Science, ETH Zurich, where she leads the Computational Cancer Genomics Group. Her research focuses on developing computational methods for multi-omics data integration to understand the epigenetic and transcriptional plasticity of cancer cells. Before joining ETH Zurich in 2019, Prof. Boeva led the Computational Epigenetics of Cancer laboratory at Inserm's Cochin Institute in Paris. She holds a Ph.D. in Bioengineering and Bioinformatics from Lomonosov Moscow State University. Throughout her career, Prof. Boeva has made contributions to the field of computational cancer genomics with developing methods for the analysis of DNA sequencing data, bulk and single-cell transcriptomics and epigenomics data, and, recently, spatial transcriptomics and proteomics.

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