Omics‐Based Systems Vaccinology for Vaccine Target Identification

Preclinical Research Omics technologies include genomics, transcriptomics, proteomics, metabolomics, and immunomics. These technologies have been used in vaccine research, which can be summarized using the term “vaccinomics.” These omics technologies combined with advanced bioinformatics analysis form the core of “systems vaccinology.” Omics technologies provide powerful methods in vaccine target identification. The genomics‐based reverse vaccinology starts with predicting vaccine protein candidates through in silico bioinformatics analysis of genome sequences. The VIOLIN V axign vaccine design program ( http://www.violinet.org/vaxign ) is the first web‐based vaccine target prediction software based on the reverse vaccinology strategy. Systematic transcriptomics and proteomics analyses facilitate rational vaccine target identification by detesting genome‐wide gene expression profiles. Immunomics is the study of the set of antigens recognized by host immune systems and has also been used for efficient vaccine target prediction. With the large amount of omics data available, it is necessary to integrate various vaccine data using ontologies, including the G ene O ntology ( GO ) and V accine O ntology ( VO ), for more efficient vaccine target prediction and assessment. All these omics technologies combined with advanced bioinformatics analysis methods for a systems biology‐based vaccine target prediction strategy. This article reviews the various omics technologies and how they can be used in vaccine target identification.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94576/1/ddr21049.pd

Ancestry in translational genomic medicine: handle with care

Disparities in health outcomes of members of different ancestral or ethnic groups can be observed in both developed and developing countries and continue to be a global concern. Genomic medicine can help toward closing this gap by expanding the knowledge on novel alleles related to disease risk and drug response, their frequencies, and their relation with disease and drug-response phenotypes, in as many countries and ethnic groups as possible. Without such knowledge, genomic medicine cannot deliver upon its promise of contributing to health for all. However, the use of ancestry or ethnicity-related genetic information as a selection criterion for assigning varying levels of access to health care is condemnable. Translational genomic medicine will allow for individualized clinical decision making - doing away with the use of race, ethnicity or ancestry as a proxy

Grant Application Review: The Case of Transparency

The Legitimacy of Peer Reviewing Transparency Policies at Funding Agencies Incremental Perspective: How to Improve Effectiveness and Robustness Further through Transparency The Radical Perspective: Transformative Potential of Transparency Acknowledgments Reference

Educating the Next Generation of Pharmacogenomics Experts: Global Educational Needs and Concepts

Personalised Therapeutic