A software package for annotation and identification of the KEGG
pathways.
SubpathwayMiner is an R-based software for flexible
pathway identification. (1) SubpathwayMiner can provide users
with sub-pathway annotation and identification of metabolic
pathways based on enzyme commission (EC) numbers. (2)
SubpathwayMiner can provide users with sub-pathway annotation
and identification based on KEGG Orthology (KO) identifiers.
(3) SubpathwayMiner can provide annotation and identification
of entire pathways. (4) SubpathwayMiner can support most of
organisms in the KEGG GENE database. (5) Data can be
automatically updated on demand by the user. (6)
SubpathwayMiner can provide identification of disease related
sub-pathways.(new!) The version 3.1 use a new approach to store
organism-related data (e.g., gene-enzyme relation data), which
make the running time of the function updateOrgAndIdType reduce
significantly compared with the old version. Therefore, the
environment variables of organisms will be provided no longer
for reducing size of the software package. When using this
tool, please cite: Li, C., Li, X., Miao, Y., Wang, Q., Jiang,
W., Xu, C., Li, J., Han, J., Zhang, F., Gong, B. et al. (2009)
SubpathwayMiner: a software package for flexible identification
of pathways. Nucleic Acids Res, 37, e131. Full text:
http://nar.oxfordjournals.org/cgi/content/full/37/19/e131
D2P.R ann.R initialize.R subGraph.R graph.R go2go.R
visualize.R ko.R

Prioritization of Candidate Cancer Subtype Specific Drugs
A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype.
The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially
expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease
reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <DOI:10.1126/science.1132939>).