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| Name | Multiscale exploration of single cell data with geometric harmonic analysis | Guy Wolf |
| Video Uploader | Video From Intelligent Medical Systems |
| Upload Date | This Video Uploaded At 29-02-2024 08:55:34 |
| Video Discription | Abstract High-throughput data collection technologies are becoming increasingly common in many fields, especially in biomedical applications involving single cell data (e.g., scRNA-seq and CyTOF). These introduce a rising need for exploratory analysis to reveal and understand hidden structure in the collected (high-dimensional) Big Data. A crucial aspect in such analysis is the separation of intrinsic data geometry from data distribution, as (a) the latter is typically biased by collection artifacts and data availability, and (b) rare subpopulations and sparse transitions between meta-stable states are often of great interest in biomedical data analysis. In this talk, I will show several tools that leverage manifold learning, graph signal processing, and harmonic analysis for biomedical (in particular, genomic/proteomic) data exploration, with emphasis on visualization, data generation/augmentation, and nonlinear feature extraction. A common thread in the presented tools is the construction of a data-driven diffusion geometry that both captures intrinsic structure in data and provides a generalization of Fourier harmonics on it. These, in turn, are used to process data features along the data geometry for interpretability, denoising, and generative purposes. Finally, I will demonstrate the application of the resulting tools in biomedical applications, such as early embryoid body development and COVID 19 mortality. Further information on https://www.dkfz.de/en/datascience/seminar.html |
| Category | Science & Technology |
| Tags | Science & Technology Download MP4 | Science & Technology Download MP3 | Science & Technology Download MP4 360p | Science & Technology Download MP4 480p | Science & Technology Download MP4 720p | Science & Technology Download MP4 1080p |
