Linear Discriminant Analysis

Linear Discriminant Analysis (LDA) is one of the most famous statistical approach to extract a feature vector separating the data into two response groups.


1. Select a target for which the extracted data is compared


Compare for

Graph will be plotted for each group in the target selected here.

Threshold of Structural resolution (Å)

Please set the maximum value of structural resolution in Å. This value is shared in 2 groups. More accurate result is expected for lower value, but the amount of data in the extracted dataset becomes smaller.

Å
1.4 8.2


2. Extract data from the database for Group #1

Extracting data for 1 of 2 datasets compared with each other.


Axial ligand (Group #1)

Please select the axial ligands of target hemes of Group #1. "ALL" includes all kinds of ligand stored in PyDISH other than listed below. The numbers in parentheses represent the number of data of each group stored in PyDISH.



Protein function (Group #1)

Please select the protein function of targe hemes of Group #1. "ALL" includes all kinds of function stored in PyDISH other than listed below. The numbers in parentheses represent the number of data of each group stored in PyDISH.



3. Extract data from the database for Group #2

Extracting data for 2 of 2 datasets compared with each other.
The same dataset selected in the process 2 cannot be selected.


Axial ligand (Group #2)

Please select the axial ligands of target hemes of Group #2. "ALL" includes all kinds of ligand stored in PyDISH other than listed below. The numbers in parentheses represent the number of data of each group stored in PyDISH.



Protein function (Group #2)

Please select the protein function of targe hemes of Group #2. "ALL" includes all kinds of function stored in PyDISH other than listed below. The numbers in parentheses represent the number of data of each group stored in PyDISH.




Please complete your selection above.