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The Uniprot protein database (http://www.uniprot.org) was used as an initial resource to define the protein domain locations of specific amino acid residues in TLR proteins.
The data presented here is a resource to define the genome structure of this HapMap cell line, as well as that of HCT116, a commonly used colorectal cancer cell line.
We used the linked resource to define the cumulative incidence (by ages 11 and 19) of six outcomes: any mental illness, any respiratory illness (excluding asthma), asthma and/or allergies, ever smoked (up to 19 only), been pregnant (19 only), and been classified as "child at risk" (eAppendix; http://links.lww.com/EDE/A898).lww.com/EDE/A898
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Applications require significant design effort and complex coordination of resources to define, deploy and execute components on heterogeneous and often unknown resources.
It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge.
Overall, 5 major themes related to educational needs and clinical concerns were found: utilization of resources to define blood pressure (BP), correct BP measurement method(s), co-morbidities, barriers to care, and experience level with HTN.
In particular, proteomic technologies are expected to play a key role in the study and treatment of cancer as they provide invaluable resources to define and characterize regulatory and functional networks, to investigate the precise molecular defect in diseased tissues and biological fluids, and to develop specific reagents to precisely pinpoint a particular disease or stage of a disease.
As mentioned above, it was apparent that several themes emerged more frequently in regards to pediatric hypertension recognition, diagnosis and evaluation during these sessions than others (major themes or issues: utilization of resources to define BP, BP measurement method, co-morbidities, barriers to care, and experience level with HTN).
Therefore, we first used data from different public resources to define nine cancer-relevant categories containing genes that are essential for cell survival, oncogenes, tumor suppressor genes, cancer census genes, phosphatases, kinases, metabolome genes, signaling pathway genes, and transcriptional regulators (Additional file 1: Table S5).
It was left to these human resource managers to define their role, liaise with the hospital or provincial managers and fulfil these undefined roles to the best of their abilities.
We also present a discussion on the theoretical resources used to define lower bounds for exact and heuristic algorithms.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com