Tutorial: Functional Module Identification in Biological Networks

Presenter:   Xiaoning Qian

*Email: <xqian, ece.tamu.edu>


Intended Audience

    This tutorial provides an introduction to computational methods for functional module identification in biological networks, covering basic concepts, mathematical models, and optimization algorithms centering around specific challenges arising from large-scale biological networks. It may help students, postdocs, and researchers at all stages of their career in the broad bioinformatics and computational biology community better understand the involved biological as well as computational problems, develop more effective methods for functional module identification, and identify their applications in biomedical research problems.



    Cellular functions or dysfunctions arise from complex interactions among biological units at different levels in cells. Advances in high-throughput profiling techniques have enabled researchers to analyze large-scale interaction data to yield a better understanding of biological systems. Functional module identification may provide such an avenue to identify molecules working in coordination as functional modules and help reveal cellular functional organization. This tutorial provides introductory overview of basic concepts, mathematical definitions, and state-of-the-art computational algorithms for functional module identification, focusing on specific challenges in biological network analysis. It is intended for researchers with interest and expertise on biological network analysis to identify both biological and computational challenges, potential solution strategies, as well as biomedical applications for future research.



[Slides], updated by Xiaoning Qian @ 2017.



·         Siamak Zamani Dadaneh and Xiaoning Qian,
"Bayesian module identification from multiple noisy networks
," [Paper]
EURASIP Journal on Bioinformatics and Systems Biology, 2016:5, 2016.

·         Yijie Wang and Xiaoning Qian,
"Clustering noisy graphs via non-negative matrix factorization with sparsity regularization
," [Paper]
Texas A&M ECE Tech Report, 2016.

·         Yijie Wang and Xiaoning Qian,
"Joint clustering of protein interaction networks through Markov random walk
," [Paper]
BMC Systems Biology, 8(S1):S9, 2014.

·         Yijie Wang and Xiaoning Qian,
"Functional module identification in protein interaction networks by interaction patterns
," [Paper]
Bioinformatics, 30(1):81-93, 2014.

·         Yijie Wang and Xiaoning Qian,
"A novel subgradient-based optimization algorithm for blockmodel functional module identification
," [Paper]
BMC Bioinformatics, 14(Suppl 2):S23, 2013.

·         Byung-Jun Yoon, Xiaoning Qian, Sayed Mohammad Ebrahim Sahraeian,
"Comparative analysis of biological networks using Markov chains and hidden Markov models
," [Paper]
IEEE Signal Processing Magazine, Special Issue on Genomic and Proteomic Signal Processing in Biomolecular Pathways, 29(1): 22--34, 2012.

·         Mark E. J. Newman, "Communities, modules and large-scale structure in networks," Nature Physics, 8: 25--31, 2012.

·         Jorg Reichardt, "Structure in Complex Networks," Springer Lecture Notes in Physics, 2009.