| Autor: |
Kenneth C. Smith, Daniel G. Chawla, Bhavjinder K. Dhillon, Zhou Ji, Randi Vita, Eva C. van der Leest, Jing Yi Jessica Weng, Ernest Tang, Amani Abid, The Human Immunology Project Consortium (HIPC), Bjoern Peters, Robert E. W. Hancock, Aris Floratos, Steven H. Kleinstein |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Scientific Data, Vol 9, Iss 1, Pp 1-11 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2052-4463 |
| DOI: |
10.1038/s41597-022-01558-1 |
| Popis: |
Abstract Recent advances in high-throughput experiments and systems biology approaches have resulted in hundreds of publications identifying “immune signatures”. Unfortunately, these are often described within text, figures, or tables in a format not amenable to computational processing, thus severely hampering our ability to fully exploit this information. Here we present a data model to represent immune signatures, along with the Human Immunology Project Consortium (HIPC) Dashboard ( www.hipc-dashboard.org ), a web-enabled application to facilitate signature access and querying. The data model captures the biological response components (e.g., genes, proteins, cell types or metabolites) and metadata describing the context under which the signature was identified using standardized terms from established resources (e.g., HGNC, Protein Ontology, Cell Ontology). We have manually curated a collection of >600 immune signatures from >60 published studies profiling human vaccination responses for the current release. The system will aid in building a broader understanding of the human immune response to stimuli by enabling researchers to easily access and interrogate published immune signatures. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
Full text from SpringerLink