Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens
Publication Date
July 12, 2016
Journal
PLOS Computational Biology
Authors
Deborah Chasman, Kevin B. Walters, Tiago J. S. Lopes, Amie J. Eisfeld, et al
Volume
12
Issue
7
Pages
e1005013
DOI
https://dx.plos.org/10.1371/journal.pcbi.1005013
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1005013
Scopus
84980043254
Mendeley
http://www.mendeley.com/research/integrating-transcriptomic-proteomic-data-using-predictive-regulatory-network-models-host-response-p
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Mendeley | Further Information

{"title"=>"Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens", "type"=>"journal", "authors"=>[{"first_name"=>"Deborah", "last_name"=>"Chasman"}, {"first_name"=>"Kevin B.", "last_name"=>"Walters"}, {"first_name"=>"Tiago J. S.", "last_name"=>"Lopes"}, {"first_name"=>"Amie J.", "last_name"=>"Eisfeld"}, {"first_name"=>"Yoshihiro", "last_name"=>"Kawaoka"}, {"first_name"=>"Sushmita", "last_name"=>"Roy"}], "year"=>2016, "source"=>"PLOS Computational Biology", "identifiers"=>{"issn"=>"1553-7358", "doi"=>"10.1371/journal.pcbi.1005013", "pmid"=>"27403523"}, "id"=>"a96fa724-0f7a-3443-bed7-a527f351cd10", "abstract"=>"Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of patho-gens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a net-work-based approach. Our approach combines expression-based regulatory network infer-ence, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influ-enza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon sig-naling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our inte-grated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.", "link"=>"http://www.mendeley.com/research/integrating-transcriptomic-proteomic-data-using-predictive-regulatory-network-models-host-response-p", "reader_count"=>31, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>10, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>2, "Student > Master"=>2, "Other"=>1, "Student > Bachelor"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>10, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>2, "Student > Master"=>2, "Other"=>1, "Student > Bachelor"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>11, "Agricultural and Biological Sciences"=>12, "Physics and Astronomy"=>1, "Computer Science"=>4, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>12}, "Computer Science"=>{"Computer Science"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>11}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"United States"=>2, "United Kingdom"=>2}, "group_count"=>3}

Scopus | Further Information

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