diff --git a/GNNGraphs/src/GNNGraphs.jl b/GNNGraphs/src/GNNGraphs.jl
index b82ea39eb..2d9850f4c 100644
--- a/GNNGraphs/src/GNNGraphs.jl
+++ b/GNNGraphs/src/GNNGraphs.jl
@@ -97,6 +97,7 @@ export rand_graph,
 
 include("sampling.jl")
 export sample_neighbors
+export induced_subgraph
 
 include("operators.jl")
 # Base.intersect
diff --git a/GNNGraphs/src/sampling.jl b/GNNGraphs/src/sampling.jl
index 01a601f5b..48efa44d5 100644
--- a/GNNGraphs/src/sampling.jl
+++ b/GNNGraphs/src/sampling.jl
@@ -116,3 +116,53 @@ function sample_neighbors(g::GNNGraph{<:COO_T}, nodes, K = -1;
     end
     return gnew
 end
+
+"""
+    induced_subgraph(graph::GNNGraph, nodes::Vector{Int}) -> GNNGraph
+
+Generates a subgraph from the original graph using the provided `nodes`. 
+    The function includes the nodes' neighbors and creates edges between nodes that are connected in the original graph. 
+    If a node has no neighbors, an isolated node will be added to the subgraph.
+
+# Arguments:
+- `graph::GNNGraph`: The original graph containing nodes, edges, and node features.
+- `nodes::Vector{Int}`: A vector of node indices to include in the subgraph.
+
+# Returns:
+A new `GNNGraph` containing the subgraph with the specified nodes and their features.
+"""
+function Graphs.induced_subgraph(graph::GNNGraph, nodes::Vector{Int})
+    if isempty(nodes)
+        return GNNGraph()  # Return empty graph if no nodes are provided
+    end
+
+    node_map = Dict(node => i for (i, node) in enumerate(nodes))
+
+    # Collect edges to add
+    source = Int[]
+    target = Int[]
+    backup_gnn = GNNGraph()
+    for node in nodes
+        neighbors = Graphs.neighbors(graph, node, dir = :in)
+        if isempty(neighbors)
+            backup_gnn = add_nodes(backup_gnn, 1)
+        end
+        for neighbor in neighbors
+            if neighbor in keys(node_map)
+                push!(source, node_map[node])
+                push!(target, node_map[neighbor])
+            end
+        end
+    end
+
+    # Extract features for the new nodes
+    #new_features = graph.x[:, nodes]
+
+    if isempty(source) && isempty(target)
+        #backup_gnn.ndata.x = new_features ### TODO fix & add edges data (probably push themto the new vector?)
+        return backup_gnn  # Return empty graph if no nodes are provided
+    end
+
+    return GNNGraph(source, target)
+    #, ndata = new_features)  # Return the new GNNGraph with subgraph and features
+end
diff --git a/GNNGraphs/test/sampling.jl b/GNNGraphs/test/sampling.jl
index 658cee8da..284589ee9 100644
--- a/GNNGraphs/test/sampling.jl
+++ b/GNNGraphs/test/sampling.jl
@@ -45,4 +45,20 @@ if GRAPH_T == :coo
         @test sg.ndata.x1 == g.ndata.x1[sg.ndata.NID]
         @test length(union(sg.ndata.NID)) == length(sg.ndata.NID)
     end
+
+    @testset "induced_subgraph" begin
+        # Create a simple GNNGraph with two nodes and one edge
+        graph = GNNGraph()  # Initialize graph
+        add_nodes!(graph, 2)  # Add 2 nodes
+        add_edge!(graph, 1, 2)  # Add an edge from node 1 to node 2
+        graph.x = rand(10, 2)  # Assign random features to both nodes (10 features per node)
+    
+        # Induce subgraph on both nodes
+        nodes = [1, 2]
+        subgraph = induced_subgraph(graph, nodes)
+    
+        @test num_nodes(subgraph) == 2  # Subgraph should have 2 nodes
+        @test num_nodes(subgraph) == 1  # Subgraph should have 1 edge
+        ### TODO @test subgraph.ndata.x == graph.x[:, nodes]  # Features should match the original graph
+    end
 end
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