Inferring functional groups from microbial gene catalogue with probabilistic topic models

Proceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011

Volumn , Issue , 2011, Pages 3-9

  Chen, Xin ^a   He, Ting Ting ^b   Hu, Xiaohua ^a   An, Yuan ^a   Wu, Xindong ^c  

^a Drexel University   (United States)

^b CENTRAL CHINA NORMAL UNIVERSITY   (China)

^c University of Vermont   (United States)

Author keywords

Bioinformatics databases; Biological data mining; Metagenomics; Probabilistic topic model

Indexed keywords

BAYESIAN METHODS; BIOINFORMATICS DATABASE; BIOLOGICAL DATA MINING; CDS; FUNCTIONAL ELEMENTS; METAGENOMICS; PATHWAY MAPPING; PROBABILISTIC TOPIC MODEL; PROBABILISTIC TOPIC MODELS; RELATIVE ABUNDANCE; UNLABELED DATA;

BAYESIAN NETWORKS; DATA MINING; FUNCTIONAL GROUPS; GENES; LIBRARIES;

BIOINFORMATICS;

EID: 84862969635     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBM.2011.12     Document Type: Conference Paper

References (16)

1. Aso T, Eguchi K: Predicting protein-protein relationships from literature using latent topics. Genome Inform 2009, 23:3-12.
2. Blei D., Ng A. and Jordan M. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993-1022,2003.
3. Daniel C. Richter and Daniel H. Huson, Functional Metagenome Analysis using Gene Ontology (MEGAN 4), Talk at the SIG M3 meeting (ISMB 2009), Stockholm
4. Fei-Fei, L. and Perona, P., "A Bayesian Heirarcical Model for Learning Natural Scene Categories", Proc. CVPR, 2005.
5. Flaherty, P., Giaever, G., Kumm, J., Jordan, M.I., Arkin, A.P.: A latent variable model for chemogenomic profiling; Bioinformatics(2005) 3286-3293 (Pubitemid 41418443)
6. Gerald W. Tannock, "The Bowel Microbiota and Inflammatory Bowel Diseases," International Journal of Inflammation, vol. 2010, Article ID 954051, 9 pages, 2010. doi:10.4061/2010/954051
7. Gerber, Georg K., Dowell, Robin D., Jaakkola, Tommi S., Gifford, David K. Hierarchical Dirichlet Process-Based Models For Discovery of Cross-species Mammalian Gene Expression. Technical report (2007)
8. Griffiths T. L. and Steyvers M. Finding scientific topics. Proceedings of the National Academy of Sciences of the United States of America, 101:5228-5235, 2004. (Pubitemid 38469131)
9. Harry S., et al. Specificities of the fecal microbiota in inflammatory bowel disease, Inflammatory Bowel Diseases,Volume 12, Issue 2, pages 106-111, February 2006
10. Huson D., Richter D., Mitra S., Auch A., Schuster S., Methods for comparative metagenomics, BMC Bioinformatics, Vol. 10, No. Suppl 1. (2009), S12.
11. Manichanh C et al., Reduced diversity of faecal microbiota in Crohn's disease revealed by a meta-genomic approach. Gut. 2006 February; 55(2): 205-211.doi: 10.1136 /gut.2005.073817.
12. Qin J et al. A human gut microbial gene catalogue established by metagenomic sequencing Nature. 2010 Mar 4; 464(7285):59-65
13. Sudderth E. B., Torralba A., Freeman W. T., and Wilsky A. S. Learning Hierarchical Models of Scences, Objects, and Parts. In International Conf. on Computer Vision, Beijing, China, 2005.
14. Walker A. et al., J High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease. BMC Microbiology 2011, 11:7.
15. Zheng B., Mclean D. C., and Lu X., Identifying biological concepts from a protein-related corpus with a probabilistic topic model. BMC Bioinformatics, 7, 2006.
16. Muller J, Szklarczyk D, Julien P, Letunic I, Roth A, Kuhn M, Powell S, von Mering C, Doerks T, Jensen LJ, Bork P: eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced nonsupervised orthologous groups, species and functional annotations. Nucleic Acids Res 2010, 38:D190-D195.