{% extends "base.html" %} {% import "bootstrap/wtf.html" as wtf %} {% import "bootstrap/fixes.html" as fixes %} {% import "bootstrap/utils.html" as util %} {% block title %}Query Builder{% endblock %} {% block head %} {{ super() }} {% endblock %} {% block styles %} {{ super() }} {% endblock %} {% block scripts %} {{ super() }} {% endblock %} {% block content %}
{{ util.flashed_messages(dismissible=True, container=False) }}
{% if use_all_networks is defined and use_all_networks %} {% elif network is defined %} {% else %}

Assembly

Choose networks to assemble for the query. All public networks, networks that you have uploaded, and networks shared with projects in which you participate are shown.

{% for network in networks %} {% endfor %}
Name Version Created
{% if preselected and network.id == preselected %} {% else %} {% endif %} {{ network.name }} {{ network.version }} {{ network.created }}
{% endif %}

Seeding

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

{% if current_user.is_beta_tester %} {% endif %}

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.

{% include "footer.html" %} {% endblock %}