# Raw Results

In this section, you can view the output results generated by our
program.

The output contains a list of all the genes, with their TNoM score and
p-value, sorted by their p-value.

## Step 1 – Running data without noise.

For the output of the non-weighted version on the raw data (before
adding the noise), __click here__.

## Step 2 – Running data with noise produced using table 2

After adding the noise using the table 2 in the quality analysis section
and running the un-weighted algorithm we’ve received these results (__click
here__).

The attached algorithm output can be found __here__.

The unattached algorithm output can be found __here__.

A summery comparing the un-weighted algorithm to the attached algorithm
can be found __here__.

A summery comparing the un-weighted algorithm to the unattached
algorithm can be found __here__.

## Step 3 – Running data with noise produced using the statistical
method.

Since we observed that the attached version is the one improving the
results while the unattached version does not, we decided to continue our
testing using only the attached version. From this point on, we used the second
(statistical) method for producing noise. For each gene quality, we’ve run 10
tests, each time re-creating the weights and noise matrices. Since there are a
total of 220 output files, we shall only list the summery files containing the
M-measures and their averages.

For the summery, __click here.__

## Results of running the algorithms on Real Data

__Normal artery vs. diseased artery:__

The non-weighted algorithm output can be found __here__.

The weighted algorithm output can be found __here__.

Diseased arteries from patients who suffer from
diabetes vs. diseased arteries from patients who don't suffer from diabetes:

The non-weighted algorithm output can be found __here__.

The weighted algorithm output can be found __here__.

Normal arteries from patients who suffer from
diabetes vs. normal arteries from patients who don't suffer from diabetes:

The non-weighted algorithm output can be found __here__.

The weighted algorithm output can be found __here__.