Databases

In this section, we describe the types of networks (databases) you can select to run diffusion methods over. These include the following and are described in detail in this section *:

  • Select a network representing an individual biological database

  • Select multiple databases to generate a harmonized network

  • Select from one of four predefined collections of biological databases representing a harmonized network

  • Submit your own network from one of the accepted formats

*

Please note that all networks available through DiffuPath have been generated using PyBEL v.0.13.2.

If there are duplicated nodes in your network, please take a look at this Jupyter Notebook to address the issue.

Network Dumps

Because of the high computational cost of generating the kernel, we provide links to pre-calculated kernels for a set of networks representing biological databases.

Database

Description

Reference

Download

DDR

Disease-disease associations

1

ddr.json

DrugBank

Drug and drug target interactions

2

drugbank.json

Gene Ontology

Hierarchy of tens of thousands of biological processes

3

go.json

HSDN

Associations between diseases and symptoms

4

hsdn.json

KEGG

Multi-omics interactions in biological pathways

5

kegg.json

miRTarBase

Interactions between miRNA and their targets

6

mirtarbase.json

Reactome

Multi-omics interactions in biological pathways

7

reactome.json

SIDER

Associations between drugs and side effects

8

sider.json

WikiPathways

Multi-omics interactions in biological pathways

9

wikipathways.json

If you would like to use one of our predefined collections, you can similarly download pre-calculated kernels for sets of networks representing integrated biological databases.

Collection

Database

Description

Download

#1

KEGG, Reactome and WikiPathways

-omics and biological processes/pathways

pathme.json

#2

KEGG, Reactome, WikiPathways and DrugBank

-omics and biological processes/pathways with a strong focus on drug/chemical interactions

pathme_drugbank.json

#3

KEGG, Reactome, WikiPathways and MirTarBase

-omics and biological processes/ pathways enriched with miRNAs

pathme_mirtarbase.json

Custom-network formats

You can also submit your own networks in any of the following formats:

  • BEL (.bel)

  • CSV (.csv)

  • Edge list (.lst)

  • GML (.gml or .xml)

  • GraphML (.graphml or .xml)

  • Pickle (.pickle)

  • TSV (.tsv)

Minimally, please ensure each of the following columns are included in the network file you submit:

  • Source

  • Target

Optionally, you can choose to add a third column, “Relation” in your network (as in the example below). If the relation between the Source and Target nodes is omitted, and/or if the directionality is ambiguous, either node can be assigned as the Source or Target.

Custom-network example

Source

Target

Relation

A

B

Increase

B

C

Association

A

D

Association

You can also take a look at our sample networks folder for some examples networks.

References

1

Menche, J., et al. (2015). Disease networks. Uncovering disease-disease relationships through the incomplete interactome. Science, 347(6224), 1257601.

2

Wishart, D. S., et al. (2018). DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Research, 46(D1), D1074–D1082.

3

Ashburner, M., et al. (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genetics, 25(1), 25–9.

4

Zhou, X., Menche, J., Barabási, A. L., & Sharma, A. (2014). Human symptoms–disease network. Nature communications, 5(1), 1-10.

5

Kanehisa, et al. (2017). KEGG: new perspectives on genomes, pathways, diseases and drugs.. Nucleic Acids Res. 45,D353-D361.

6

Huang, H. Y., et al. (2020). miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database. Nucleic acids research, 48(D1), D148-D154.

7

Fabregat, A et al. (2016). The Reactome Pathway Knowledgebase. Nucleic Acids Research 44. Database issue: D481–D487.

8

Kuhn, M., et al. (2016). The SIDER database of drugs and side effects. Nucleic Acids Research, 44(D1), D1075–D1079.

9

Slenter, D.N., et al. (2017). WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Research, 46(D1):D661-D667.