dkNET.org provides tools and services covering 4 areas. The primary mission of dkNET it to make it easier for researchers to find and use research resources like antibodies, organisms, software tools and data.

Resource Reports

Resource reports are based on a unique integrated data set and analytics platform that combines Research Resource Identifiers (RRIDs), text mining and data aggregation to provide:

A detailed overview of each resource.

Citation metrics on published papers that have used a particular resource.

Information about what resources have been used together.

Examples of how Resource Reports can help you:

Before planning to use cell lines in an experiment, a researcher could check Resource Reports to see if there are reported problems with the cell lines, e.g., contamination, what studies have already been published using this cell line, and who could be a potential collaborators.

Before choosing antibodies for a particular experimental application, a researcher could check Resource Reports to see if there is validation information available for these antibodies.

Discovery Portal

The new dkNET Discovery Portal connects researchers directly to more than 300 biomedical databases and hundreds of millions of data and information records. Researchers can also explore community resources that are highly relevant to the disease fields in NIDDK's mission.

Examples include:

A researcher in chronic kidney disease field could use the Discovery Portal to find what expression and omics data have been produced by other researchers.

A researcher would like to start a new project in the microbiome field, and could use the Discovery Portal to find what data are available, what research projects have been funded, or what new funding opportunities are.

Rigor/Reproducibility

dkNET gives researchers the tools and services to help them comply with funding and publishing mandates in support of robust and reproducible science.

Comply with NIH mandates on resource identification and authentication.

Manage and share FAIR research data.

Generate a resource reproducibility report when you submit a proposal or publication.

Examples include:

Before planning an experiment or submitting a proposal, a researcher can generate a Reproducibility Report to make authentication plans for cell lines and antibodies, as required by the new NIH guidelines.

A researcher is planning to produce or has produced several datasets in a research project and does not know how best to comply with data sharing mandates. A researcher can use dkNET FAIR Data resources to find appropriate data repositories and learn how to comply with the FAIR principles.

Signaling Pathways Project

The Signaling Pathways Project (SPP) knowledgebase is a new component of dkNET designed to assist cell signaling researchers in generating research hypotheses using the large volume of public archived transcriptomic and ChIP-Seq datasets. A cornerstone of the SPP is consensome analysis, which uses transcriptomic and ChIP-Seq datasets to rank genomic targets on the basis of their regulatory relationships with signaling pathway nodes (receptor, enzymes and transcription factors). To learn more about generating hypotheses using SSP, contact support@signalingpathways.org.

Ochsner, S et al. (2018) The Signaling Pathways Project: an integrated 'omics knowledgebase for mammalian cellular signaling pathways. BioRxiv.
https://doi.org/10.1101/401729

Example project use cases include:

The SPP adipose tissue consensome assigns a high ranking to a target about which little is known in the literature, implying a previously uncharacterized role in adipose biology. A researcher designs experiments to validate its potential role in a facet of adipose tissue biology under study in their laboratory.

A researcher has a list of genes with known roles in inflammatory bowel disease (IBD). They query this gene list against SPP and finds that these genes are frequently targeted by a transcription factor. The researcher designs experiments to explore the role of this transcription factor in driving IBD.