Research Experience

Publications – peer reviewed journal articles

1. Liangqun Lu, and Bernie J. Daigle Jr. 2020. “Prognostic Analysis of Histopathological Images Using Pre-Trained Convolutional Neural Networks: Application to Hepatocellular Carcinoma.” PeerJ 8 (March): e8668.
2. Liangqun Lu, Kevin A. Townsend, and Bernie J. Daigle. 2019. “GEOlimma: Differential Expression Analysis and Feature Selection Using Pre-Existing Microarray Data.” bioRxiv (Under Review)
3. Chaudhary Kumardeep, Olivier B. Poirion, Liangqun Lu, Sijia Huang, Travers Ching, and Lana X. Garmire. 2018. “Multi-Modal Meta-Analysis of 1494 Hepatocellular Carcinoma Samples Reveals Significant Impact of Consensus Driver Genes on Phenotypes.” Clinical Cancer Research: An Official Journal of the American Association for Cancer Research, September.
4. Chaudhary Kumardeep, Olivier B. Poirion, Liangqun Lu, and Lana X. Garmire. 2017. Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.” Clinical Cancer Research: An Official Journal of the American Association for Cancer Research 24 (6): 1248–59.
5. Liangqun Lu , Sara McCurdy *, Sijia Huang, Xun Zhu, Karolina Peplowska, Maarit Tiirikainen, William A. Boisvert, and Lana X. Garmire. 2016. “Time Series miRNA-mRNA Integrated Analysis Reveals Critical miRNAs and Targets in Macrophage Polarization.” Scientific Reports 6 (December): 37446.

Conference abstracts/posters

1. Multi-Omic Data Integration to Discover Subgroups of PTSD Using Deep Denoising Autoencoder. Big Data in Precision Health 2019, Stanford, CA, May 22 - 23, 2019
2. Prognostic Analysis of Histopathological Images Using Pre-Trained Convolutional Networks, Birmingham, AL, March 28 – 30, 2019
3. Generating ECG signals with Generative Adversarial Networks, Silver Spring, MD, August 01, 2018
4. Clinical Subgroup-Specific PTSD Classification and Biomarker Identification. Big Data in Precision Health 2018, Stanford, CA, May 23 - 24, 2018
5. Large-scale Microarray Data Based Feature Selection For Improved Molecular Classification. 16th annual UT-KBRIN Bioinformatics Summit 2017, Burns, TN, April 21-23, 2017
6. Association analysis of driver genes of hepatocellular carcinoma with cancer hallmarks. 13th Rocky Mountain Bioinformatics Conference, Aspen, CO, Dec.10-13, 2015
7. Integrative analysis of RNA-seq and miRNA-seq revealed functional miRNAs in the macrophage. Jabsom Symposium, Honolulu, HI, Apr. 15, 2015

PhD Dissertation

Liangqun Lu, "Machine Learning Approaches for Disease Classification Using Genome Scale Data Sets and Biomedical Images (2020), [Slides] [pdf]

Master Thesis

Liangqun Lu, "End-To-End Adversarial Learning for Conversational Generation Using Pre-Trained Word Embeddings", University of Memphis (2019), [Slides] [pdf]

Master Thesis

Liangqun Lu, "Multi-omic data integration to stratify population in hepatocellular carcinoma", University of Hawaii at Manoa (2016), [Slides] [pdf]