Automated Author ProfileLiu, Yang
Yale University
Liu, Yang
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Traditional microbiome studies rely on shotgun DNA sequencing, which loses all spatial context and information about functional interactions with the host. We recently developed a novel spatial sequencing technology called microDBIT (Spatial Co-profiling of Genome/Epigenome and Transcriptome) to simultaneously map the genomes, epigenomes, and transcriptomes of microbial and host cells within their spatial context. This approach can reveal the diverse states of the microbiome and brain tissue, and their interactions in gut tissue. microDBIT leverages deterministic barcoding in tissue for spatial omics profiling, allowing the identification of bacterial species and their activities by capturing their unique genomes and transcriptomes. Additionally, it can co-map host epigenomes and gene expression. microDBIT represents a flexible, multi-omics sequencing platform and will be the first to comprehensively map microbiome-brain interactions and the gut microenvironment of Parkinson’s disease.
Authors
- Liu, Yang
Traditional microbiome studies rely on shotgun DNA sequencing, which loses all spatial context and information about functional interactions with the host. We recently developed a novel spatial sequencing technology called microDBIT (Spatial Co-profiling of Genome/Epigenome and Transcriptome) to simultaneously map the genomes, epigenomes, and transcriptomes of microbial and host cells within their spatial context. This approach can reveal the diverse states of the microbiome and brain tissue, and their interactions in gut tissue. microDBIT leverages deterministic barcoding in tissue for spatial omics profiling, allowing the identification of bacterial species and their activities by capturing their unique genomes and transcriptomes. Additionally, it can co-map host epigenomes and gene expression. microDBIT represents a flexible, multi-omics sequencing platform and will be the first to comprehensively map microbiome-brain interactions and the gut microenvironment of Parkinson’s disease.
Authors
- Liu, Yang