Computational Core for Plant Metabolomics (CCPM v4.4)

Privileges for Registered Users

  • A registered user may browse data and analysis results reported in projects that have been published in this portal. Currently the published projects mainly contain data from published papers available in the net.
  • Registered users, after appropriate approval, may also create their own projects and carry out operations corresponding to the currently completed and functional modules. Such projects will be stored as ‘Unpublished’ projects and will be visible only to the ‘Owner’ of the project, or to those who have been explicitly permitted by the ‘Owner’. Please register and browse ‘Help’ for further details.

Release Notes for CCPM v4.4

New functionalities of CCPM v4.4 are as follows:

1. KEGG Module Integration:

The KEGG module for pathway mapping is very useful for researchers belonging to Life Sciences community. This module gives the information for single pathway of a metabolite and also indicates the other pathways in which that particular metabolite also take part and change the whole biochemical scenario of the particular organism. On the other hand, the KEGG module also gives the list of pathways in which one or more metabolites involved, this is also a good expect of the module.


2. NMR Module:

NMR Metabolite identification tool uses the open source metabohunter scripts for semi-automatic assignment of 1D NMR spectra of metabolites. The metabolite identification interface search two major publicly available NMR database (HMDB: Human Metabolome Database and MMCD: Madison Metabolomics Consortium Database) in background and display the result output from the selected database based on user input parameters. This tool for metabolite identification is based on spectra or peak lists with different search methods and with possibility for peak drift in a user defined spectral range.


3. Cytoscape Connectivity Integration:

Cytoscape will help to visualize correlation network of different metabolites.


4. Multigroup:

Multigroup comparison allows user for the identification of differentially expressed metabolite features across multiple classes of data. multigroup analysis aims to identify differences between groups and reveal the diversity of metabolic patterns across different groups.


5. Bulk Upload:

Meta data for multiple groups and its samples in a project can be uploaded as a single .csv file by the user. The corresponding file can be uploaded by clicking the button Choose File followed by clicking Upload Bulk Data. User can also upload Multiple Raw files with a group simultaneously using this Bulk Upload option.

IIIT Hyderabad DBT, India JNU, New Delhi