TY  - GEN
AB  - Co-expression network models help identify important biochemical pathways, biomarkers, and targets for research, but they typically focus on gene expression. In this work, co-expression network methodologies are extended to proteomics and applied to data derived from mice infected with either influenza or SARS-CoV. This work develops the methods necessary for deriving integrated network signatures of disease with an application in systems biology of infectious disease.
AD  - Oregon Health and Science University
AU  - Gibbs, David
DA  - 2012
DO  - 10.6083/M4DR2SH4
DO  - DOI
ED  - McWeeney, Shannon
ED  - Advisor
ED  - Mentor
ID  - 876
KW  - Transcriptome
KW  - Gene Regulatory Networks
KW  - Proteome
KW  - Protein Interaction Maps
KW  - Proteomics
KW  - Systems Biology
KW  - Communicable Diseases
KW  - Mice
KW  - Influenza, Human
KW  - Severe acute respiratory syndrome-related coronavirus
KW  - Biomarkers
KW  - biochemical markers
KW  - protein-protein interaction
L1  - https://digitalcollections.ohsu.edu/record/876/files/879_etd.pdf
L2  - https://digitalcollections.ohsu.edu/record/876/files/879_etd.pdf
L4  - https://digitalcollections.ohsu.edu/record/876/files/879_etd.pdf
LK  - https://digitalcollections.ohsu.edu/record/876/files/879_etd.pdf
N2  - Co-expression network models help identify important biochemical pathways, biomarkers, and targets for research, but they typically focus on gene expression. In this work, co-expression network methodologies are extended to proteomics and applied to data derived from mice infected with either influenza or SARS-CoV. This work develops the methods necessary for deriving integrated network signatures of disease with an application in systems biology of infectious disease.
PB  - Oregon Health and Science University
PY  - 2012
T1  - Integrated signatures of disease using network methods
TI  - Integrated signatures of disease using network methods
UR  - https://digitalcollections.ohsu.edu/record/876/files/879_etd.pdf
Y1  - 2012
ER  -