Titlebook: Bioinformatics Research and Applications; 19th International S Xuan Guo,Serghei Mangul,Alexander Zelikovsky Conference proceedings 2023 The

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,Multi-class Cancer Classification of Whole Slide Images Through Transformer and Multiple Instance L) problem while slide-level labels are available. We introduce a approach for WSI classification that leverages the MIL and Transformer, effectively eliminating the requirement for localized annotations. Our method consists of three key components. Firstly, we use ResNet50, which has been pre-traine

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ricME: Long-Read Based Mobile Element Variant Detection Using Sequence Realignment and Identity Calissues such as genetic diseases and species diversity. However, few detection algorithms of mobile element variants have been developed on third-generation sequencing data. We propose an algorithm ricME that combines sequence realignment and identity calculation for detecting mobile element variants

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,Approximating Rearrangement Distances with Replicas and Flexible Intergenic Regions,segment of genes. Most approaches to model these problems consider some simplifications such as ignoring nucleotides outside genes (the so-called intergenic regions), or assuming that just a single copy of each gene exists in the genomes. Recent works made advancements in more general models conside

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