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Integrated protein interaction networks for 11 microbes
- In Proceedings of the 10th Annual International Conference on Research in Computational Molecular Biology (RECOMB
, 2006
"... Abstract. We have combined four different types of functional genomic data to create high coverage protein interaction networks for 11 microbes. Our integration algorithm naturally handles statistically dependent predictors and automatically corrects for differing noise levels and data corruption in ..."
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Cited by 26 (10 self)
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Abstract. We have combined four different types of functional genomic data to create high coverage protein interaction networks for 11 microbes. Our integration algorithm naturally handles statistically dependent predictors and automatically corrects for differing noise levels and data corruption in different evidence sources. We find that many of the predictions in each integrated network hinge on moderate but consistent evidence from multiple sources rather than strong evidence from a single source, yielding novel biology which would be missed if a single data source such as coexpression or coinheritance was used in isolation. In addition to statistical analysis, we demonstrate via case study that these subtle interactions can discover new aspects of even well studied functional modules. Our work represents the largest collection of probabilistic protein interaction networks compiled to date, and our methods can be applied to any sequenced organism and any kind of experimental or computational technique which produces pairwise measures of protein interaction. 1
Fax +41 61 306 12 34 E-Mail karger@karger
, 2006
"... netic analysis comparing the relationships of the GenBank GBP sequences to the correctly annotated set of GBPs identified a large number of previously unclassified and mis-annotated GBPs. Given these promising results, we developed a tree-parsing algorithm for automated phylogenetic annotation and ..."
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netic analysis comparing the relationships of the GenBank GBP sequences to the correctly annotated set of GBPs identified a large number of previously unclassified and mis-annotated GBPs. Given these promising results, we developed a tree-parsing algorithm for automated phylogenetic annotation and tested it with GenBank sequences. Our algorithm was able to automatically classify 30 unidentified and 15 misannotated GBPs out of 78 sequences. Altogether, our results support the potential for phylogenomics to increase the accuracy of sequence annotations.
ii HIGH-THROUGHPUT GENOMIC/PROTEOMIC STUDIES, FINDING STRUCTURE AND MEANING BY SIMILARITY BY
, 2010
"... To my family, extending back to the first stirrings of carbon chemistry, and reaching forward to my children Ashley and Meredith and recently to my new granddaughter, Madison; but most especially to my wife Maureen, who has been my life companion, teacher, and confidant. iv Acknowledgements I would ..."
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To my family, extending back to the first stirrings of carbon chemistry, and reaching forward to my children Ashley and Meredith and recently to my new granddaughter, Madison; but most especially to my wife Maureen, who has been my life companion, teacher, and confidant. iv Acknowledgements I would like to thank Dr. Maggie Werner-Washburne, my advisor, for her support, and enthusiasm for research as a way of life, and for keeping me on track (no easy job!). I also want to acknowledge the support and kindness of my committee members, Drs. Mary Anne Nelson, Richard Cripps, and Shawn Martin; thank you for your help and insights. I’d also like to acknowledge Dr. Vicky Peck and thank her for showing me the world of microbial genomics and for first suggesting I write about microarrays for her class; I particularly thank Dr. Stuart Kim who ‘got it ’ even before I really learned how to explain what ‘it ’ was with respect to analyzing high-throughput data with VxInsight. I thank Dr. Cheryl Wilman who taught so many of us about leukemia and cancer research
REFERENCES CONTENT ALERTS
, 1998
"... This article cites 33 articles, 18 of which can be accessed free ..."
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unknown title
, 2007
"... doi:10.1093/bib/bbm038 Current progress in network research: toward reference networks for key model organisms ..."
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doi:10.1093/bib/bbm038 Current progress in network research: toward reference networks for key model organisms
Practical Applications of Bacterial Functional Genomics
"... Microbial genome sequencing started in the late 1990s, and now, one decade later, we researchers have access to hundreds of genome sequences. This advance has revolutionized the way research is conducted, and microbial biology has solidly transitioned into the era of post-genomics. Researchers routi ..."
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Microbial genome sequencing started in the late 1990s, and now, one decade later, we researchers have access to hundreds of genome sequences. This advance has revolutionized the way research is conducted, and microbial biology has solidly transitioned into the era of post-genomics. Researchers routinely have access to the
Disparate Data Fusion for Protein Phosphorylation Prediction
"... New challenges in knowledge extraction include interpreting and classifying data sets while simultaneously considering related information to confirm results or identify false positives. We discuss a data fusion algorithmic framework targeted at this problem. It includes separate base classifiers fo ..."
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New challenges in knowledge extraction include interpreting and classifying data sets while simultaneously considering related information to confirm results or identify false positives. We discuss a data fusion algorithmic framework targeted at this problem. It includes separate base classifiers for each data type and a fusion method for combining the individual classifiers. The fusion method is an extension of current ensemble classification techniques and has the advantage of allowing data to remain in heterogeneous databases. In this paper, we focus on the applicability of this framework to the protein phosphorylation prediction problem. Key words: ensemble classification, phosphorylation, base classifier 1
ANALYSIS OF GENETIC VARIATION IN PEDICULUS HUMANUS AND POPULUS TRICHOCARPA BY
"... With the advent of sequencing technologies that are both affordable and readily available, biologists are now able to address questions that were previously intractable. New species are having their genomes mapped at an increasing rate, including non-model organisms. Two such organisms are the human ..."
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With the advent of sequencing technologies that are both affordable and readily available, biologists are now able to address questions that were previously intractable. New species are having their genomes mapped at an increasing rate, including non-model organisms. Two such organisms are the human body louse, Pediculus humanus corporis and the black cottonwood, Populus trichocarpa. While unrelated, these two organisms each represent a study system with questions that challenge our current understanding of each organism. Body and head lice, while closely related, are thought to be separate species with their most important difference being that only body lice vector disease to humans. The first question is: Are body lice (Pediculus humanus coporis) and head lice (Pediculus humanus capitis) the same species? A total of 10,771 body louse and 10,770 head louse transcripts were predicted from a combined assembly of Roche 454 and Illumina sequenced cDNAs from whole body tissues collected at all life stages and during pesticide exposure and bacterial infection treatments. Illumina reads mapped to the 10,775 draft body louse gene models from the whole genome assembly predicted nine presence/absence differences, but PCR confirmation resulted in