Titlebook: Bioinformatics Research and Applications; 20th International S Wei Peng,Zhipeng Cai,Pavel Skums Conference proceedings 2024 The Editor(s) (

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,Improved Inapproximability Gap and?Approximation Algorithm for?Scaffold Filling to?Maximize Increassed of contigs which are matched to fix positions on the reference genome, as well as some unmatched fragments, the purpose is to insert the unmatched fragments between the contigs in the scaffold, such that the resulting genome is similar to the reference genome. Let . be a one-to-one matching betw

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,SEMQuant: Extending Sipros-Ensemble with?Match-Between-Runs for?Comprehensive Quantitative Metaprots this understanding by measuring relative protein abundance and revealing dynamic changes under different conditions. However, the challenge of missing peptide quantification persists in metaproteomics analysis, particularly in data-dependent acquisition mode, where high-intensity precursors for MS

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PrSMBooster: Improving the Accuracy of Top-Down Proteoform Characterization Using Deep Learning Resoteoforms. Consequently, the accuracy of identification results is crucial. Proteins with multiple primary structure alterations generate various proteoforms, leading to a combinatorial explosion due to their vast numbers. Furthermore, there is no gold set as a reference. So, enhancing the accuracy

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,FCMEDriver: Identifying Cancer Driver Gene by?Combining Mutual Exclusivity of?Embedded Features andtion approaches mainly exploit mutual exclusivity of mutated driver genes and integrate multi-omics data with gene function networks. Some of them identify driver genes based on the gene features learned by network embedding algorithms. However, these methods are limited to using the mutual exclusiv

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Der Thermodynamische Gleichgewichtszustandstic algorithm to predict the missing amino acids in the gaps. The experimental results on both real and simulation data show that our proposed algorithms show promising results of 100% and close to 100% accuracy.