PathArt

PathArt is a comprehensive collection of curated data from literature as well as public domain databases for more than 2,400 signaling and metabolic pathways. PathArt includes a dynamic pathway articulator component, which builds molecular interaction networks from curated databases. PathArt provides a tool for analysis, biological interpretation and visualization of microarray data results in these curated pathways. In addition, PathArt provides a collection of 33 high priority disease pathways with emphasis on pathway responsive genes and knockouts. The data sets within PathArt are linked back to PubMed references as well as Genbank and Kegg metabolic pathways. Quarterly PathArt updates will extend the disease, signaling, and metabolic data sets.

Currently, PathArt includes comprehensive pathways for clients using this approach. Some examples include:

• Signaling and Metabolic pathways
• Disease pathways for Breast Cancer, Chronic Myeloid Leukemia, Colon Cancer , Glioblastoma , Liver Cancer , Lung Cancer, Melanoma , Ovarian Cancer, Pancreatic Cancer, Prostate Cancer, Stomach cancer and other diseases viz., AIDS, Alzheimer’s, Arrhythmia, Asthma, Atherosclerosis, Bipolar Disorder, Chronic Obstructive Pulmonary Disease (Chronic Bronchitis and Emphysema), Crohn's Disease, Depression, Diabetes Type II, Erectile Dysfunction, Hypertension, Inflammatory Bowel Disease, Multiple Sclerosis, Obesity, Osteoarthritis, Osteoporosis, Parkinson’s Disease, Rheumatoid Arthritis, Schizophrenia, Ulcerative Colitis and a newly added disease viz., Cardiac Hypertrophy.
• Pathways for humans, medically important mammalian model systems (mouse, rat), and others.
• Interaction Maps Module that comprises of 169,900 Biomolecular interactions and 46,850 components across species.

Users are encouraged to suggest priority pathways for future examination and addition to the Pathart database.

Users at UNC-Chapel Hill may access the PathArt database directly through their workstations at no charge by going to http://pathart.med.unc.edu/pathart/index.html in a Java-enabled browser (Java 1.5 and either Firefox or Microsoft Explorer 5.5 or newer highly recommended).

**NEW** The latest version allows users to load and save individual sessions. Please refer to the PathArt Documentation/Tutorials section of this website to access the document explaining this feature.

For assistance in the use of the Pathart tools set please contact Tom Randall ( ; 3-3891).

The User Guide or shorter tutorials for PathArt are available in the Documents section for the PathArt application.

NOTE: The links above will only work for users that have valid UNC-Chapel Hill IP addresses