Jubilant Biosys PathArt

Category Cross-Omics>Pathway Knowledge Bases/Databases/Tools

Abstract PathArt is a curated database of biomolecular interactions with tools for searching, analysis and visualization of data. PathArt consists of three (3) modules: 1) The Pathway module (PathArt Core); 2) The Interaction Map Module and 3) The Drug-Target Module. This product could be an invaluable tool for scientists working on target identification and validation, biomarker discovery, systems biology, microarray analysis and expression profiling.

The Pathway module (PathArt Core):

PathArt Core is a comprehensive collection of curated data from literature as well as public domain databases for more than 2,100 signaling and metabolic pathways. PathArt includes a database component and dynamic pathway articulator component, which builds directed acyclic graphs from molecular interaction networks.

Diseases Covered (31) -

Asthma, Atherosclerosis, Alzheimer's, AIDS, Chronic Myeloid Leukemia, Chronic Obstructive Pulmonary Disease (Chronic Bronchitis and Emphysema), Diabetes Type II, Breast Cancer, Colon Cancer, Glioblastoma, Lung Cancer, Prostate Cancer, Parkinson's Disease, Pancreatic Cancer, Melanoma, Multiple Sclerosis, Erectile Dysfunction, Obesity, Osteoarthritis, Osteoporosis, Ovarian Cancer, Rheumatoid Arthritis, Inflammatory Bowel Disease, Ulcerative Colitis, Crohn's Disease, Schizophrenia, Depression, Hypertension, Bipolar Disorder, Liver Cancer, and Stomach Cancer.

Physiologies covered (19) -

Apoptosis, Cell Adhesion, Cell-cycle, DNA Repair, Development, Pain, Growth and Differentiation, Inflammation, Keratinocyte Differentiation, Myogenesis, Neurogenesis, Protein Families, Skeletal Development, Thrombopoiesis, Angiogenesis, Erythropoiesis, Lymphopoiesis, Monopoiesis and others.

Interaction Maps:

Interaction Maps (IMaps) is a manually curated database with more than 120,000 interactions for 17 organisms captured from over 70,000 abstracts. Extensive data coverage on protein-protein, protein-small molecule, protein-RNA, protein-DNA and protein-drug interactions gives this database the competitive edge. Its data content grows at a rate of more than 20,000 interactions per quarter.

Druggable-Target Module:

The Druggable-Target module garners and contains manually curated data on toxicity, Pharmacokinetics and Pharmacodynamics (PK/PD), toxicogenomics etc., as well as public domain data on 300 anticancer drug molecules which can be ported to System Data Format (SDF) files. This data also contains disease centric target information.

PathArt Data Features include:

1) Three (3) different modules that are 'integrated' - PathArt (pathways module), Imaps (biomolecular interaction module) and the druggable target module (focus on anticancer drugs).

2) Classification of pathways into canonical and non canonical, containing organism, organ, and cell-type specific data.

3) Manually curated data for disease/physiology specific interactions, mutations and knockouts.

4) All the relevant details about the interaction(s) such as, the mechanism, mode, model/organism etc., have been captured.

5) Functional annotation for genes from over 12 public domain databases.

PathArt Application Features include:

1) Dynamically generated interaction networks that depict interaction data and a tabular report of the interactions.

2) Search types provided include pathway, component, public domain id, effect and inhibitor-based searches.

3) Data export options for systems biology markup language (SBML), hypertext markup language (HTML) and extensible markup language XML formats.

4) Homolog mapping for genes across species in PathArt and Interaction Maps.

5) Isoform mapping for genes captured in the database.

6) Search based on component name, 'Shortest path' and/or 'All paths' is provided in the Interaction Maps module.

7) An option to map components from Interaction maps to PathArt, in order to view them in a pathway perspective.

8) Ability to highlight the genes that inhibitor, drug, mutation or knockout information is available in the graphical representation.

9) Custom coloring of components based on cellular location, component type, etc., and also based on parameters such as expression ratios (for microarray data analysis).

10) Tagging of mutations in enzymes in metabolic pathways along with metabolic disorder information.

11) Built-in microarray data analysis capabilities which include various normalization and clustering algorithms.

12) Mapping of relevant gene sets from a statistical analysis result onto pathways.

13) Two way integration with widely used microarray analysis tools such as GeneSpring GX (see G6G Abstract Number 20003R), Mass Profiler Professional (G6G Abstract Number 20056R) and FDA/NCTR ArrayTrack (see G6G Abstract Number 20089).

System Requirements

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Manufacturer

Manufacturer Web Site PathArt

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G6G Abstract Number 20060

G6G Manufacturer Number 101600