Comparative Analysis of Pathway Databases

Pathway gene sets were generated based on the GeneCards platform (12 ), implementing the gene symbolization process allowing for comparison of pathway gene sets, from 12 different manually curated sources, including: Reactome (13 (link)), KEGG (14 (link)), PharmGKB (15 (link)), WikiPathways (16 (link)) QIAGEN, HumanCyc (17 (link)), Pathway Interaction Database (18 (link)), Tocris Bioscience, GeneGO, Cell Signaling Technologies (CST), R&D Systems and Sino Biological (see Table 1). A binary matrix was generated for all 3125 pathways, where each column represents a gene indicated by 1 for presence in the pathway and 0 for absence. Additionally, six sources were analysed for their cumulative tallying of genes content, including: BioCarta (19 ), SMPDB (20 (link)), INOH (21 (link)), NetPath (22 (link)), EHMN (23 (link)) and SignaLink (24 (link)).

Table 1.

Pathway sources

Source	Number of pathways	Number of genes	Pathway size average	Pathwaysize stdev	% of singletons	Reference
Reactome	1411	7157	46.2	105.5	2.5	13
KEGG	284	6746	81.9	91.2	28.8	14
QIAGEN	317	3626	123.1	124.2	17.6	http://www.qiagen.com/geneglobe/
HumanCyc	319	831	6.5	7.6	10.0	17
GeneGO	250	3413	48.7	22.1	22.8	http://lsresearch.thomsonreuters.com/maps/
WikiPathways	229	4504	48.1	46.0	41.5	16
Pathway Interaction Database	186	2239	34.9	21.1	62.9	18
PharmGKB	102	2239	16.4	14.5	29.4	15
RnD systems	36	863	52.1	28.6	22.2	http://www.rndsystems.com/Pathways.aspx
Cell signaling technologies	21	1820	127.4	63.4	80.1	http://www.cellsignal.com/contents/science/cst-pathways/science-pathways
Tocris	12	263	55.6	29.2	8.3	http://www.tocris.com/signalling Path ways. php
Sino Biological	11	450	64.9	34.9	27.3	http://www.sinobiological.com/

Free full text: Click here

Belinky F., Nativ N., Stelzer G., Zimmerman S., Iny Stein T., Safran M, & Lancet D. (2015). PathCards: multi-source consolidation of human biological pathways. Database: The Journal of Biological Databases and Curation, 2015, bav006.

Publication 2015

Biological Gene process Genes Maps Sino

Corresponding Organization : Weizmann Institute of Science

Top 5 similar protocols

Protocol cited in 30 other protocols

Variable analysis

independent variables

None explicitly mentioned

dependent variables

None explicitly mentioned

control variables

None explicitly mentioned

controls

No positive or negative controls specified by the authors.

Annotations

Based on most similar protocols

Etiam vel ipsum. Morbi facilisis vestibulum nisl. Praesent cursus laoreet felis. Integer adipiscing pretium orci. Nulla facilisi. Quisque posuere bibendum purus. Nulla quam mauris, cursus eget, convallis ac, molestie non, enim. Aliquam congue. Quisque sagittis nonummy sapien. Proin molestie sem vitae urna. Maecenas lorem.

As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Revolutionizing how scientists
search and build protocols!