Automatic annotation of protein motif function with Gene Ontology terms. - Xinghua Lu 001; Chengxiang Zhai; Vanathi Gopalakrishnan; Bruce G. Buchanan (BMC Bioinform., 2004)

UIUC/MUSC at TREC 2005 Genomics Track. - ChengXiang Zhai; Xu Ling; Xin He 001; Atulya Velivelli; Xuanhui Wang; Hui Fang 001; Azadeh Shakery; Xinghua Lu 001 (TREC, 2005)

Research Paper: Enhancing Text Categorization with Semantic-enriched Representation and Training Data Augmentation. - Xinghua Lu 001; Bin Zheng; Atulya Velivelli; ChengXiang Zhai (J. Am. Medical Informatics Assoc., 2006)

Multi-label literature classification based on the Gene Ontology graph. - Bo Jin; Brian Muller; Chengxiang Zhai; Xinghua Lu 001 (BMC Bioinform., 2008)

A graph model and an exact algorithm for finding transcription factor modules. - Songjian Lu; Xinghua Lu 001 (BCB, 2011)

Using graph model to find transcription factor modules: the hitting set problem and an exact algorithm. - Songjian Lu; Xinghua Lu 001 (Algorithms Mol. Biol., 2013)

An exact algorithm with the time complexity of $O^*(1.299^m)$ for the weighed mutually exclusive set cover problem - Songjian Lu; Xinghua Lu 001 (CoRR, 2013)

An exact algorithm for the weighed mutually exclusive maximum set cover problem. - Songjian Lu; Xinghua Lu 001 (CoRR, 2014)

Trans-species learning of cellular signaling systems with bimodal deep belief networks. - Lujia Chen 001; Chunhui Cai; Vicky Chen; Xinghua Lu 001 (Bioinform., 2015)

Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data. - Henry Ogoe; Shyam Visweswaran; Xinghua Lu 001; Vanathi Gopalakrishnan (BMC Bioinform., 2015)

The center for causal discovery of biomedical knowledge from big data. - Gregory F. Cooper; Ivet Bahar; Michael J. Becich; Panayiotis V. Benos; Jeremy M. Berg; Jeremy U. Espino; Clark Glymour; Rebecca Crowley Jacobson; Michelle Kienholz; Adrian V. Lee; Xinghua Lu 001; Richard Scheines (J. Am. Medical Informatics Assoc., 2015)

Identifying Driver Genomic Alterations in Cancers by Searching Minimum-Weight, Mutually Exclusive Sets. - Songjian Lu; Kevin N. Lu; Shi-Yuan Cheng; Bo Hu; Xiaojun Ma; Nicholas Nystrom; Xinghua Lu 001 (PLoS Comput. Biol., 2015)

An exact algorithm for finding cancer driver somatic genome alterations: the weighted mutually exclusive maximum set cover problem. - Songjian Lu; Gunasheil Mandava; Gaibo Yan; Xinghua Lu 001 (Algorithms Mol. Biol., 2016)

Learning a hierarchical representation of the yeast transcriptomic machinery using an autoencoder model. - Lujia Chen 001; Chunhui Cai; Vicky Chen; Xinghua Lu 001 (BMC Bioinform., 2016)

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma. - Jonathan D. Young; Chunhui Cai; Xinghua Lu 001 (BMC Bioinform., 2017)

Deep Contextualized Biomedical Abbreviation Expansion. - Qiao Jin 001; Jinling Liu; Xinghua Lu 001 (BioNLP@ACL, 2019)

PubMedQA: A Dataset for Biomedical Research Question Answering. - Qiao Jin 001; Bhuwan Dhingra; Zhengping Liu; William W. Cohen; Xinghua Lu 001 (EMNLP/IJCNLP (1), 2019)

Integrating data and knowledge to identify functional modules of genes: a multilayer approach. - Lifan Liang; Vicky Chen; Kunju Zhu; Xiaonan Fan 001; Xinghua Lu 001; Songjian Lu (BMC Bioinform., 2019)

Probing Biomedical Embeddings from Language Models. - Qiao Jin 001; Bhuwan Dhingra; William W. Cohen; Xinghua Lu 001 (CoRR, 2019)

Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference. - Chunhui Cai; Gregory F. Cooper; Kevin N. Lu; Xiaojun Ma; Shuping Xu; Zhenlong Zhao; Xueer Chen; Yifan Xue; Adrian V. Lee; Nathan Clark; Vicky Chen; Songjian Lu; et al. (PLoS Comput. Biol., 2019)

Learning Latent Causal Structures with a Redundant Input Neural Network. - Jonathan D. Young; Bryan Andrews; Gregory F. Cooper; Xinghua Lu 001 (CD@KDD, 2020)

Predicting Drug Sensitivity of Cancer Cell Lines via Collaborative Filtering with Contextual Attention. - Yifeng Tao; Shuangxia Ren; Michael Q. Ding; Russell Schwartz; Xinghua Lu 001 (MLHC, 2020)

From Genome to Phenome: Predicting Multiple Cancer Phenotypes Based on Somatic GenomicAlterations via the Genomic Impact Transformer. - Yifeng Tao; Chunhui Cai; William W. Cohen; Xinghua Lu 001 (PSB, 2020)

Explicit representation of protein activity states significantly improves causal discovery of protein phosphorylation networks. - Jinling Liu; Xiaojun Ma; Gregory F. Cooper; Xinghua Lu 001 (BMC Bioinform., 2020)

Robust and accurate estimation of cellular fraction from tissue omics data via ensemble deconvolution. - Manqi Cai; Molin Yue; Tianmeng Chen; Jinling Liu; Erick Forno; Xinghua Lu 001; Timothy Billiar; Juan C. Celedón; Chris McKennan; Wei Chen 074; Jiebiao Wang (Bioinform., 2022)

An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors. - Xueer Chen; Lujia Chen 001; Cornelius H. L. Kürten; Fattaneh Jabbari; Lazar Vujanovic; Ying Ding 003; Binfeng Lu; Kevin Lu; Aditi Kulkarni; Tracy Tabib; Robert Lafyatis; Gregory F. Cooper; et al. (PLoS Comput. Biol., 2022)

An interpretable deep learning framework for genome-informed precision oncology. - Shuangxia Ren; Gregory F. Cooper; Lujia Chen 001; Xinghua Lu 001 (Nat. Mac. Intell., 2024)

Knowledge-guided Contextual Gene Set Analysis Using Large Language Models. - Zhizheng Wang; Chi-Ping Day; Chih-Hsuan Wei; Qiao Jin 001; Robert Leaman; Yifan Yang 006; Shubo Tian; Aodong Qiu; Yin Fang; Qingqing Zhu; Xinghua Lu 001; Zhiyong Lu (CoRR, 2025)