Cover art for scientific journal “Multi-omics microsampling for the profiling of lifestyle-associated changes in health”
publishing date: January 2023
On the cover: Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors.
Cover art for scientific journal “Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity”
print publishing date: August/September 2022
On the cover: Natural killer (NK) cells (pale blue) attacking SARS-CoV-2 viruses (red) with machine learning methodology signified by patterned numerals. In this issue of Cell Systems, Zhang et al. (p. 598) propose a machine learning method that integrates single-cell mult-iomic data with GWAS summary statistics to discover cell-type-specific disease risk genes. Application to severe COVID-19 identifies over 1,000 risk genes in 19 human lung cell types. Genetic risk is found to be enriched within NK cells and CD56 bright cytokine-producing NK cells. Cover art by Lettie McGuire.
Cover art for scientific journal “Precision environmental health monitoring by longitudinal exposome and multi-omics profiling” print publishing date: June/July 2022
In this issue, thousands of longitudinally measured chemical and biological components along with physical factors in the personal exposome cloud were investigated for their impact on internal -omes, such as the proteome, metabolome, gut microbiome, as well as cytokines and blood markers. On the cover, the dynamic and diverse exposomics profile is depicted as a mixture and its complex interactions with the gut microbiome and internal biomolecules in various organs is illustrated. These potential gene–environment interactions elucidate how the exposome shapes human phenome and impacts precision health. (Cover artwork by Lettie McGuire [https://lettiemcguire.com]. [For details, see Gao et al., pp. 1199–1214.])
The Stanford Personal Health Dashboard (PHD) platform is an open-source, end-to-end solution for biomedical research projects that require integrating wearable and clinical data.
Antarctica Research Study Web Design and Development, Stanford Genetics
a collaborative research study with NASA, the European Space Agency & Snyder Lab, Stanford Genetics. Conducting research at the ends of the earth, we examine human health in earth’s most extreme environments.
