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Long-range Genomics Benchmark Technology and More

Author(s)
Polen, McKinley
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Advisor
Kellis, Manolis
Terms of use
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/
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Abstract
The transformer architecture has emerged as a popular choice in various domains, owing to its ability to capture long-range dependencies and parallel processing capabilities. In the context of genomics, where dependencies often span over 100,000 base pairs, the quadratic computational complexity of the attention mechanism, a core feature of the transformer architecture, poses a significant bottleneck. With the goal of creating a genomics foundation model (FM), this paper aims to address challenges associated long range dependencies in genomics. Our survey encompasses modifications to the attention mechanism, the creation of a genomics long range benchmark (GLRB), and the evaluation of various transformer and other non-transformer architectures. These efforts collectively develop the groundwork supporting the development of a robust genomics foundation model, opening new possibilities for genomics research and applications.
Date issued
2024-05
URI
https://hdl.handle.net/1721.1/156968
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology

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