Faculty

Xinghua Lu, MD, PhD, MS

Room 525
5607 Baum Boulevard
Pittsburgh, PA 15206
Phone Number: 
412-624-3303
Fax: 
412-624-5310
Admin Support: 

Research Interests

Dr. Lu’s research focuses on the computational methods for identifying signaling pathways underlying biological processes and diseases as well as statistical methods for acquiring knowledge from biomedical literature. He was trained in Pharmacology and works in the field of bioinformatics after NLM sponsored postdoctoral training in Biomedical Informatics. His research interest concentrates on applying latent variable models to simulate biological signaling system and text mining.

Currently, Dr. Lu is working on developing his research in translational bioinformatics and systems/computational biology and its application to specific domains relevant to human disease. He is pursuing collaboration in the area of natural language processing and text mining with the eventual goal of establishing a Center or Institute in Translational Bioinformatics.

 

Appointments and Positions

Associate Professor of Biomedical Informatics
Biomedical Informatics Training Program Core Faculty

Recent Publications

Cowart, LA., Shotwell, M., Worley, ML.,  Richards, AJ, Montefusco, DJ, Hannun YA, and Lu, X. (2010) Revealing a signaling role of PHS1P in yeast using integrative systems approaches.  Molecular Systems Biology 6:349 PMID: 20160710(Selected for presentation at the Highlight Track of ISMB 2010 as a major advance in the field)

Richards*, AJ, Muller, B., Shotwell, M, Cowart, LA, Rohrer, B, and Lu, X (2010) Assessing the functional coherence of gene sets with metrics based on the Gene Ontology graph.  Bioinformatics, supplement issue for the Proceedings for the Intelligent Systems in Molecular Biology (ISMB) 2010 (19% acceptance) PMID: 20529941

Zheng*, B. and Lu, X (2009) Application of semantic modeling in bioinformatics domain.  In: Data Management in Semantic Web, Ed. Jin, H. and Lv, Z,.  Nova Science Publishers, Inc.

Jin*, B and Lu, X (2009) Enhancing GO-graph-based multi-label classification using semantic-rich GO terms.   Proceedings of the Annual Meeting of the ISMB BioLINK Workshop 2009

Muller*, B., Richards, AJ., Jin, B., Lu, X. (2009) GOGrapher; A Python library for GO graph representation and analysis.  BMC Research Notes 2:122 PMID:19583843