Difference between revisions of "Sub Cellular Localization"

From Protein Prediction 2 Winter Semester 2014
(Implementation)
(Roadmap)
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** Storing protein's score.
 
** Storing protein's score.
 
* Writing functions for identifiying "x" and "y" positions of cell's compartments.
 
* Writing functions for identifiying "x" and "y" positions of cell's compartments.
* Highlighting cell's compartments upon "mouse-over" event.
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* Highlighting cell's compartments (static).
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* Visualization by:
 
* Visualization by:
 
** Grouping proteins based on localization in the cell component.
 
** Grouping proteins based on localization in the cell component.
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** Highlighting cell's compartments (dynamic).
 
** Updating cell’s compartments based on particular protein’s score (Confidence).
 
** Updating cell’s compartments based on particular protein’s score (Confidence).
 
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Revision as of 20:43, 3 December 2014

Sub Cellular Localization in Cell

Objective

"To visualize biological cells and highlight by a user selected sub-cellular compartments in a way that they stand out from the un-selected ones"

GUI mockups

Figure 1 : Protein's score in cell compartment (One protein)
Figure 2 : Number of Proteins in cell compartment (more than one protein)
Figure 3 : Protein's score in cell compartment (more than one protein)
  • User experience
    • Interactivity
    • Easy identification of the number of proteins in cell compartment
    • Good visualization of data
  • Functionality
    • Parsing the user input “txt” file
    • Mapping the file content into visualization
  • Features
    • Good color scheme to highlight :
      • Number of proteins in a compartment
      • Score of each protein (confidence)

Application design

Data

  • Remarks about input format
    • Text file must contain proteins of only one type of cell
    • Text file format :
      • Cell type (File’s first line)
      • Protein id
      • Score (certainty of existence of particular protein within a cell compartment)
      • Localization (component)
      • User’s file can have more than 3 columns but additional columns will not be executed


Figure 4 : Text File format

Roadmap

Figure 5 : Roadmap
Project progress
Week number Completed tasks Status
Week 1
  • Researching Biology literature in order to identify proteins belonging to different cells (Archaea / Bacteria / Eukaryota)
  • Identify existing tools or libraries which can help us in visualizing input data.
  • Identification of importance of protein localization in cell's compartments.
  • Obtaining images of Archea, Bacteria and Eukaryota.
  • Creation of repository in github.
  • Definition of input file format.
Check.jpg
Week 2
  • Coding for uploading file.
  • Parsing input file.
    • Counting number of proteins in cell's compartments.
    • Storing protein's score.
  • Writing functions for identifiying "x" and "y" positions of cell's compartments.
  • Highlighting cell's compartments (static).
Check.jpg
Week 3
  • Visualization by:
    • Grouping proteins based on localization in the cell component.
    • Highlighting cell's compartments (dynamic).
    • Updating cell’s compartments based on particular protein’s score (Confidence).
Week 4
  • Development of deployable component for reuse by BioJS.
Week 5
  • Final presentation of project.


Implementation

Figure 6 : Validation File size
Figure 7 : Validation Cell type
Figure 8 : Validation Use cases 1 & 2