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Open Source Science

https://github.com/compomics/proteinassociationpair

https://github.com/compomics/proteinassociationpair

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
    Links to: ncbi.nlm.nih.gov
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (5.9%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: CompOmics
  • License: apache-2.0
  • Language: Python
  • Default Branch: master
  • Size: 29.3 KB
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  • Watchers: 2
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Archived
Created about 9 years ago · Last pushed almost 9 years ago

https://github.com/CompOmics/ProteinAssociationPair/blob/master/ 

# ProteinAssociationPair


 * [Project Description](#project-description)
 * [Usage](#usage)
 * [Project Support](#project-support)

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![Protein-Association Workflow](http://genesis.ugent.be/uvpublicdata/Protein-Association/workflow.png)

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## Project Description

In this study, we have used publicly available mass-spectrometry data from pride to investigate the biological importance of protein co-occurrence in various experiments. To calculate the statistical weight of protein co-occurrence we have used Jaccard similarity method. Protein pairs with a similarity above 0.4 were mapped to knowledgebases; [Uniprot](http://www.uniprot.org/), [Reactome](http://www.reactome.org), [Ensembl](http://www.ensembl.org), [IntAct](http://www.ebi.ac.uk/intact/), [BioGRID](https://thebiogrid.org/), and [CORUM](http://mips.helmholtz-muenchen.de/corum/), to assign potential biological relevance. Moreover, using published articles and [String](http://string-db.org/) database, we were able to determine the possible biological connection between unannotated protein pairs with no known biological correspondence. 

### Citation
*Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs* 
Surya Gupta, Kenneth Verheggen, Jan Tavernier, and Lennart Martens. *Journal of Proteome Research 2017*, PMID: [28480704](http://www.ncbi.nlm.nih.gov/pubmed/28480704)

[Go to top of the page](#projectassociationpair)

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## Usage

Use main python file "ProteinPairWithCommonPepCheck.py" for running the method

direct the location to the database files in the "ProteinPairWithCommonPepCheck.py"


[Go to top of the page](#projectassociationpair)

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## Project Support

Protein-Association project is supported by:

| Compomics | VIB | Ghent University|
|:--:|:--:|:--:|
| [![compomics](http://genesis.ugent.be/uvpublicdata/image/compomics.png)](http://www.compomics.com) | [![vib](http://genesis.ugent.be/uvpublicdata/image/newVIBlogo.png)](http://www.vib.be) | [![ugent](http://genesis.ugent.be/uvpublicdata/image/ugent.png)](http://www.ugent.be/en) |

[Go to top of the page](#projectassociationpair)

Owner

  • Name: Computational Omics and Systems Biology Group
  • Login: CompOmics
  • Kind: organization
  • Email: compomics.list@gmail.com

The CompOmics group, headed by Prof. Dr. Lennart Martens, specializes in the management, analysis and integration of high-throughput Omics data.

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