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SVmine improves structural variation detection by integrative mining of predictions from multiple algorithms., , , и . Bioinform., 33 (21): 3348-3354 (2017)Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation., , , , , , , , , и . ACM Trans. Knowl. Discov. Data, 18 (1): 14:1-14:26 (января 2024)Network Clustering Analysis Using Mixture Exponential-Family Random Graph Models and Its Application in Genetic Interaction Data., , , , и . IEEE ACM Trans. Comput. Biol. Bioinform., 16 (5): 1743-1752 (2019)An integrated approach to the prediction of domain-domain interactions., , , и . BMC Bioinform., (2006)scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery., , и . Briefings Bioinform., (марта 2023)scRMD: imputation for single cell RNA-seq data via robust matrix decomposition., , , , , и . Bioinform., 36 (10): 3156-3161 (2020)A Lasso regression model for the construction of microRNA-target regulatory networks., , , , и . Bioinform., 27 (17): 2406-2413 (2011)CIMON: Towards High-quality Hash Codes., , , , , , , и . CoRR, (2020)Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation., , , , , , и . CoRR, (2021)Direct interaction network inference for compositional data via codaloss., , , и . J. Bioinform. Comput. Biol., 18 (6): 2050037:1-2050037:26 (2020)