Use cases

Here you find practical applications of the ProCope API which guide you through different parts of the functionality in this library.

  1. Generating score networks, clustering, cluster evaluation
  2. Working with score networks
  3. Working with complex sets
  4. Integrating data into Petri nets, exporting to XGMML and ToPNeT

Sample Use Case 1: Generating score networks, clustering, cluster evaluation

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This first use case introduces you to the basic functionality of ProCope, namely the prediction of protein complexes from purification data and the quality assessment of the resulting complexes using experimental data.

What will be done?
Techniques used
  • Generation of Socio Affinity and Purification Enrichment score networks based on purification data
  • Clustering of these networks using hierarchical agglomerative clustering (average-link)
  • Comparison of the resulting clusterings with the MIPS[l] gold-standard complex set
  • Evaluation of the clusterings using Colocalization score and GO semantic similarity 
  • Purification data loading from the file system
  • Purification data merging
  • Socio affinity score network generation
  • PE score network generation (weighted combination of two networks)
  • Clustering
  • Complex set loading from the file systen
  • Complex set writing to the file system
  • Complex set comparison (Brohee measure)
  • Loading of localization data from the file system
  • Calculating Colocalization scores
  • Name mappings
  • Loading of a GO network from the file system
  • Calculating GO semantic similarity scores

Sample Use Case 2: Working with score networks

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In this use case we load different score networks from the file system and do some manipulation, filtering and evaluation steps.

What will be done?
Techniques used
  • Comparison of scores networks with each other
  • Evaluation of scores network using complex enrichment and ROC curves
  • Different network manipulation/merging/filtering steps
  • Iterating over networks
  • Network loading from the file system
  • Network comparison, correlation coefficient calculation
  • Removing edges below a given score (score cutoff)
  • Random network generation
  • Complex set loading from the file system
  • Removing complexes with more than a given number of proteins (size cutoff)
  • Calculating complex enrichments
  • Calculating, plotting and saving ROC curves
  • Network merging
  • Network filtering using boolean expressions
  • Network iteration
  • Working with the ProteinManager (internal protein IDs)

Sample Use Case 3: Working with complex sets

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Here we learn how to manipulate and filter complex sets and how to iterate over all complexes and proteins contained in a complex set.

What will be done?
Techniques used
  • Decomposition of a complex set using a given scores network
  • Complex filtering by size
  • Extraction of highly confident complexes
  • Loading complex sets and network from the file system
  • Decomposition
  • Singleton removing
  • Filtering complexes by their average complex score
  • Iterating over a complex set
  • Working with the ProteinManager (internal protein IDs)
  • Writing a complex set to the file system

Sample Use Case 4: Integrating data into Petri nets, exporting to XGMML and ToPNeT

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This use case shows you how to integrate the information from scores networks, complex sets and purification data into single Petri nets and export these nets to XGMML or ToPNeT format. The XGMML format is compatible with Cytoscape.

What will be done?
Techniques used
  • Generating a Petri net from a small set of data
  • Exporting this Petri net to XGMML and ToPNet format
  • Loading and restricting protein networks
  • Loading and restricting complex sets
  • Petri net generation
  • Petri net conversion





ProCope documentation