diff --git a/server.R b/server.R
index 949a1b7..9395af9 100644
--- a/server.R
+++ b/server.R
@@ -19,8 +19,18 @@ server <- function(input, output) {
 
         # Compute scoring factors and the weighted score.
 
-        results[, score := input$clusteriness / 100 * clusteriness +
-            input$correlation / 100 * r_mean]
+        clusteriness_weight <- input$clusteriness / 100
+        correlation_weight <- input$correlation / 100
+        total_weight <- clusteriness_weight + correlation_weight
+        clusteriness_factor <- clusteriness_weight / total_weight
+        correlation_factor <- correlation_weight / total_weight
+
+        results[, score := clusteriness_factor * clusteriness +
+            correlation_factor * r_mean]
+
+        # Apply the cut-off score.
+
+        results <- results[score >= input$cutoff / 100]
 
         # Order the results based on their score. The resulting index will be
         # used as the "rank".
@@ -29,17 +39,20 @@ server <- function(input, output) {
     })
 
     output$genes <- renderDT({
-        datatable(
-            results()[, .(.I, name, clusteriness, r_mean)],
+        dt <- datatable(
+            results()[, .(.I, name, clusteriness, r_mean, score)],
             rownames = FALSE,
             colnames = c(
                 "Rank",
                 "Gene",
                 "Clusteriness",
-                "Correlation"
+                "Correlation",
+                "Score"
             ),
             style = "bootstrap"
         )
+
+        formatPercentage(dt, c("clusteriness", "r_mean", "score"), digits = 1)
     })
 
     output$synposis <- renderText({
diff --git a/ui.R b/ui.R
index 9f1b4a2..05aec8f 100644
--- a/ui.R
+++ b/ui.R
@@ -25,7 +25,7 @@ ui <- fluidPage(
                 min = 0,
                 max = 100,
                 step = 1,
-                value = 50
+                value = 100
             ),
             sliderInput(
                 "correlation",
@@ -35,6 +35,15 @@ ui <- fluidPage(
                 max = 100,
                 step = 1,
                 value = 100
+            ),
+            sliderInput(
+                "cutoff",
+                "Cut-off score",
+                post = "%",
+                min = 0,
+                max = 100,
+                step = 1,
+                value = 50
             )
         ),
         wellPanel(