{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/156968"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/156968","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Long-range Genomics Benchmark Technology and More","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. 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