The immune system, by any standard is complex. As the number of components in a system and interactions between components grows, our ability to fully comprehend the system diminishes significantly. Principally, humans in comparison to computers, do poorly in tasks such as memorizing, searching and constructing multi-component, multi-scale images. The need to """"""""free our knowledge"""""""" from free text, and place it in a computer system which will memorize our knowledge, allow for easy searching and visualization of our understanding of the immune system is apparent. The use of natural language processing to represent molecular findings from the scientific literature, and the use of network visualization have both made a clear impact across biology. Here, we plan to build a new informatics tool that uses both of these techniques to represent the complex network between cells, immunological processes, secreted cytokines, expressed transcripts, and phosphorylated signaling proteins, called ImuuneXpresso. We will then apply this tool to the multiple type of molecular measurements made throughout this program, to suggest the cellular cause of influenza vaccine non-response. Our tools will be available for beta tested to investigators within this program and released to the general community.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI057229-10
Application #
8508799
Study Section
Special Emphasis Panel (ZAI1-KS-I)
Project Start
2013-04-01
Project End
2014-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
10
Fiscal Year
2013
Total Cost
$135,182
Indirect Cost
$38,310
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Haynes, Winston A; Vallania, Francesco; Liu, Charles et al. (2016) EMPOWERING MULTI-COHORT GENE EXPRESSION ANALYSIS TO INCREASE REPRODUCIBILITY. Pac Symp Biocomput 22:144-153
Fragiadakis, Gabriela K; Baca, Quentin J; Gherardini, Pier Federico et al. (2016) Mapping the Fetomaternal Peripheral Immune System at Term Pregnancy. J Immunol 197:4482-4492
Sharon, Eilon; Sibener, Leah V; Battle, Alexis et al. (2016) Genetic variation in MHC proteins is associated with T cell receptor expression biases. Nat Genet 48:995-1002
Adams, Jarrett J; Narayanan, Samanthi; Birnbaum, Michael E et al. (2016) Structural interplay between germline interactions and adaptive recognition determines the bandwidth of TCR-peptide-MHC cross-reactivity. Nat Immunol 17:87-94
Rubelt, Florian; Bolen, Christopher R; McGuire, Helen M et al. (2016) Individual heritable differences result in unique cell lymphocyte receptor repertoires of naïve and antigen-experienced cells. Nat Commun 7:11112
Angst, Martin S; Fragiadakis, Gabriela K; Gaudillière, Brice et al. (2016) In Reply. Anesthesiology 124:1414-5
Holmes, Tyson H; He, Xiao-Song (2016) Human immunophenotyping via low-variance, low-bias, interpretive regression modeling of small, wide data sets: Application to aging and immune response to influenza vaccination. J Immunol Methods 437:1-12
Frei, Andreas P; Bava, Felice-Alessio; Zunder, Eli R et al. (2016) Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat Methods 13:269-75
Sweeney, Timothy E; Braviak, Lindsay; Tato, Cristina M et al. (2016) Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis. Lancet Respir Med 4:213-24
Kovats, S; Turner, S; Simmons, A et al. (2016) West Nile virus-infected human dendritic cells fail to fully activate invariant natural killer T cells. Clin Exp Immunol 186:214-226

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