Wei Wu

According to our database, Wei Wu authored at least 19 papers between 2003 and 2022.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2022

Kernel Mixed Model for Transcriptome Association Study.

Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu

J. Comput. Biol., 2022

Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model.

Haohan Wang, Oscar L. Lopez, Wei Wu, Eric P. Xing

Proceedings of the Research in Computational Molecular Biology, 2022

2021

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.

Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu, Eric P. Xing

BMC Bioinform., 2021

Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach.

Seo-Jin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric P. Xing

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Explaining a black-box using Deep Variational Information Bottleneck Approach.

Seo-Jin Bang, Pengtao Xie, Wei Wu, Eric P. Xing

CoRR, 2019

Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies.

Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu, Eric P. Xing

BMC Bioinform., 2019

Deep Inductive Matrix Completion for Biomedical Interaction Prediction.

Haohan Wang, Yibing Wei, Mengxin Cao, Ming Xu, Wei Wu, Eric P. Xing

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction.

Haohan Wang, Changpeng Lu, Wei Wu, Eric P. Xing

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018

Multiple Kernel k-means Clustering using Min-Max Optimization with l₂ Regularization.

Seo-Jin Bang, Wei Wu

CoRR, 2018

Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis.

Pengtao Xie, Wei Wu, Yichen Zhu, Eric P. Xing

Proceedings of the 35th International Conference on Machine Learning, 2018

2016

Naïve Bayes ensemble: A new approach to classifying unlabeled multi-class asthma subjects.

Seo-Jin Bang, Wei Wu

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2014

Network Analysis of Breast Cancer Progression and Reversal Using a Tree-Evolving Network Algorithm.

Ankur P. Parikh, Ross E. Curtis, Irene Kuhn, Sabine Becker-Weimann, Mina J. Bissell, Eric P. Xing, Wei Wu

PLoS Comput. Biol., 2014

Robust Reverse Engineering of Dynamic Gene Networks Under Sample Size Heterogeneity.

Ankur P. Parikh, Wei Wu, Eric P. Xing

Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

2011

TREEGL: reverse engineering tree-evolving gene networks underlying developing biological lineages.

Ankur P. Parikh, Wei Wu, Ross E. Curtis, Eric P. Xing

Bioinform., 2011

2007

GIMscan: A New Statistical Method for Analyzing Whole-Genome Array CGH Data.

Yanxin Shi, Fan Guo, Wei Wu, Eric P. Xing

Proceedings of the Research in Computational Molecular Biology, 2007

2005

Evaluation of normalization methods for cDNA microarray data by <i>k</i>-NN classification.

Wei Wu, Eric P. Xing, Connie Myers, I. Saira Mian, Mina J. Bissell

BMC Bioinform., 2005

Comparison of normalization methods for CodeLink Bioarray data.

Wei Wu, Nilesh Dave, George C. Tseng, Thomas Richards, Eric P. Xing, Naftali Kaminski

BMC Bioinform., 2005

2004

Logos: a Modular Bayesian Model for <i>de Novo</i> Motif Detection.

Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M. Karp

J. Bioinform. Comput. Biol., 2004

2003

LOGOS: a modular Bayesian model for de novo motif detection.

Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M. Karp

Proceedings of the 2nd IEEE Computer Society Bioinformatics Conference, 2003