CliPro™ is a comprehensive, easy to access knowledgebase of proteins in various biological sources that reflects alterations between normal versus diseased conditions, manually mined from literature.
The knowledgebase currently includes a vast repertoire of clinically significant proteins with their concentration values under various pathological states, with an emphasis on functional and diagnostic utility. CliPro™ would serve as an effective platform to identify novel protein-disease associations and validate new potential biomarker-disease associations.

clipro

  • Protein : can be searched using public identifiers
  • Disease : can be searched using MeSH or common disease term
  • Biomarker : can be searched based on biomarker type
  • BioFluid : can be searched based on the biological fluid
  • Protein Type: can be searched based on function and/or occurrence
  • Plasma Catalogue: provides a concise report of the protein across diseases
  • Specialized platform to validate mass spectrometry and high-throughput proteomics data using the pre-annotated information from the literature.
  • Provides a good repertoire of biomarker-disease associations for novel biomarker prediction and validation.
  • Customized datasets for proteins from various biological fluids including serum/plasma, cerebrospinal fluid, synovial fluid, amniotic fluid, urine, tears.
  • Enables comparison between protein concentration levels of disease oriented studies and normal/control studies.
  • The knowledgebase also contains information on post-translational modifications, genetic variations associated with disease.
Human plasma proteome module
  • Covers all classes of protein from highly abundant classical plasma protein to aberrantly secreted proteins, cytokines/receptor ligands.
  • With annotations on influence of factors such as genetics, age, sex, physiological state, diseases on altered levels the protein in the human plasma.
  • Annotated with post translational modifications, variation information associated with a disease.
  • Ontology for various data fields such as Biomarker, BioFluid, Disease, Pathological State, Clinical Outcome, GO making it easier for the data to be accessed and filtered across various entities.