Query Builder for Anti-aggregant tau mutant promotes neurogenesis v1.0.0

Seeding

Please choose the seeding type your want to use for the query. Note: it's possible to use multiple seeding types.

Seeding by Nodes

This method of seeding will acquire the given nodes and expand around them using given seed method.

Use Case: The leukemia drug, nilotinib, triggers cells to get rid of faulty components - including the ones associated with several brain diseases. In 2015, Georgetown University Medical Center published findings that the drug had a helpful effect on patients in Alzheimer's and Parkinson's diseases. Though it is currently unknown, a search of the paths between this drug and these diseases could provide insight to nilotinib's mechanism of action.

Seeding by Name Search

This method acquires the nodes whose names are superstrings of the search query

Use Case: Users may be interested in a whole class of nodes related to a certain name, such as th MGI, RGD, HGNC, and HGNC Families related to AKT1.

Seeding by Authorship

This method acquires the nodes and edges asserted by the given authors and expands around their neighborhoods to show peripheral knowledge.

Use Case: Users may be interested in the representation of their own work, their colleagues' work, and their favorite publications in the knowledge assembly. For users that are new to a given field, this is an excellent research tool to identify what papers to read next.

Seeding by Citation

This method acquires the nodes and edges asserted by the given citations and expands around their neighborhoods to show peripheral knowledge.

Use Case: Users may be interested in the representation of their own work, their colleagues' work, and their favorite publications in the knowledge assembly. For users that are new to a given field, this is an excellent research tool to identify what papers to read next.

Seeding by Annotation

This method of will acquire edges matching any of the given annotations.

Use Case: The Amyloidogenic Cascade describes the processes resulting from amyloid beta peptides deposition in the brain; and is a central to Alzheimer Disease (AD) pathology. Using the NeuroMMSig functional annotations, this sub-network can be extracted and its periphery can be investigated to identify novel overlaps with other canonical pathways implicated in AD.

Transformations

Please choose any filters, enrichments, or transformations you want to apply to the query. For a list of available functions, please see here.

Use Case: You might want to collapse all protein, RNA, and miRNA nodes to their corresponding gene to simplify visualization and exploration.

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.