PathArt^TM

PathArt™ is a comprehensive collection of manually curated information from literature as well as public domain databases on 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 high priority disease and physiology pathways with emphasis on pathway responsive genes and knockouts.  The coverage is for pathways of Human, Rat and Mouse for cell specific, tissue specific and organism specific data.

The present version of PathArt covers the following:

•  Includes 3527 regulatory and signaling pathways across diseases and physiologies.

• Provides information on 39 high priority diseases, and pathway and disease responsive genes.

• Provides pathway information on 23 diverse physiologies.

• Covers information on ~8783 Knockouts and ~18000 mutation data points.

• Coverage of pathways for Human, Mouse and Rat for cell specificity, tissue specificity and organism specific data.

The diseases covered in the current version of PathArt are: AIDS, Acute Myeloid Leukemia, Alzheimer’s, Arrhythmia, Asthma, Atherosclerosis, Bipolar Disorder, Breast Cancer, Cardiac Hypertrophy, Chronic Myeloid Leukemia, Chronic Obstructive Pulmonary Disease (Chronic Bronchitis and Emphysema), Colon Cancer, Crohn's Disease, Depression, Diabetes Type II, Erectile Dysfunction, Glioblastoma, Hypertension, Inflammatory Bowel Disease, Liver Cancer, Lung Cancer, Melanoma, Multiple Sclerosis, Obesity, Osteoarthritis, Osteoporosis, Ovarian Cancer, Pancreatic Cancer, Parkinson’s Disease, Prostate Cancer, Renal cancer, Rheumatoid Arthritis, Schizophrenia, Stomach cancer, Thyroid cancer, Head and Neck Cancer, Ulcerative Colitis, Cervical Cancer and Urinary Bladder Cancer.

The physiologies covered in the current version of PathArt are: Adipogenesis, Angiogenesis, Apoptosis, Cell Adhesion, Cell Cycle, DNA Repair, Development, Erythropoiesis, Germ Cell Differentiation, Growth and Differentiation, Inflammation, Keratinocyte Differentiation, Myogenesis, Neurogenesis, Pain, Protein Families, Skeletal Development, Thrombopoiesis, Lymphopoiesis, Monopoiesis, Granulopoiesis, Cardiomyocyte Development and Others.

The Database Component integrates pathway information curated from peer-reviewed articles and other public domain sources, namely Unigene, Locuslink, Homologene, Genbank, Agilent, Affymetrix, GO, OMIM, Pubmed, SWISS-PROT, KEGG databases, PUBCHEM.

PathArt™ has following modules:

Core PathArt™

Database of Signal transduction & metabolic pathways, over 3400 signaling pathways across 38 diseases & 23 physiologies.

Interaction Maps

Module of protein-protein interactions with ~2, 19, 598 interactions.

Druggable Targets Database

A module for finding out drug and inhibitor information.  Currently 350 Drug molecules are covered

Some Applications of PathArt™:

Proteomics:

To determine the myriad functions performed by the protein is the major task of scientist in this field. Manually curated protein-protein interactions put a ray of light into the functionality of the proteins.

The protein-protein interactions are captured by manually curating full text article in case of PathArt™ and abstracts in Interaction maps.

The protein interactions are captured along with their mechanism, mode of action, domain and motif details, detection method used to capture the study and the animal model in which the study is carried out. The presence of mutation and knock-out details help in confirming the protein functionality.

Disease Specific Studies:

The extensive coverage of various pathways under disease heading makes it a close associate of scientists involved in deciphering Disease mechanisms.

Scientists involved in deciphering disease mechanism are keen on to have a platform where all the details regarding the particular disease is been captured in terms of protein-protein interaction and protein effects. Protein linkage to inhibitor list assists them in designing Bio assays. The presence of canonical pathways in PathArt™ gives a complete picture on the difference that prevails between diseased stage and normal condition.

Microarray

Microarray data analysis helps drug discovery researchers to identify appropriate candidates for participating in clinical trials of new drugs. Microarray data can be filtered, analyzed for statistical data, gene expression data and mapped into pathways. Microarray data uploading on to PathArt™ pathways and its visualization, from any known source makes it a valuable tool for microarray users. 

Microarray data can be analyzed by using several probe set identifiers.

The result gives all the pathways, with the queried gene IDs classified under their respective disease or physiology name. Information could also be obtained for these genes summarized from over 12 public domain databases. The database is also compatible with all commonly used microarray data analysis software packages such as Spotfire, Genespring and FDA Array track.