RECOMB B

12 papers

YearTitle / Authors
2023CDGCN: Conditional de novo Drug Generative Model Using Graph Convolution Networks.
Shikha Mallick, Sahely Bhadra
2023Computing Shortest Hyperpaths for Pathway Inference in Cellular Reaction Networks.
Spencer Krieger, John D. Kececioglu
2023DM-Net: A Dual-Model Network for Automated Biomedical Image Diagnosis.
Xiaogen Zhou, Zhiqiang Li, Tong Tong
2023MTGL-ADMET: A Novel Multi-task Graph Learning Framework for ADMET Prediction Enhanced by Status-Theory and Maximum Flow.
Bing-Xue Du, Yi Xu, Siu-Ming Yiu, Hui Yu, Jian-Yu Shi
2023Percolate: An Exponential Family JIVE Model to Design DNA-Based Predictors of Drug Response.
Soufiane Mourragui, Marco Loog, Mirrelijn M. van Nee, Mark A. van de Wiel, Marcel J. T. Reinders, Lodewyk F. A. Wessels
2023Research in Computational Molecular Biology - 27th Annual International Conference, RECOMB 2023, Istanbul, Turkey, April 16-19, 2023, Proceedings
Haixu Tang
2023Sequence to Graph Alignment Using Gap-Sensitive Co-linear Chaining.
Ghanshyam Chandra, Chirag Jain
2023Spectrum Preserving Tilings Enable Sparse and Modular Reference Indexing.
Jason Fan, Jamshed Khan, Giulio Ermanno Pibiri, Rob Patro
2023Statistically Consistent Rooting of Species Trees Under the Multispecies Coalescent Model.
Yasamin Tabatabaee, Sébastien Roch, Tandy J. Warnow
2023T-Cell Receptor Optimization with Reinforcement Learning and Mutation Polices for Precision Immunotherapy.
Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning
2023Translation Rate Prediction and Regulatory Motif Discovery with Multi-task Learning.
Weizhong Zheng, John H. C. Fong, Yuk Kei Wan, Athena H. Y. Chu, Yuanhua Huang, Alan S. L. Wong, Joshua W. K. Ho
2023VStrains: De Novo Reconstruction of Viral Strains via Iterative Path Extraction from Assembly Graphs.
Runpeng Luo, Yu Lin