Protein-Protein Interaction Profiling
Traditional PPI analysis often suffers from the overhead of high-level languages. Zinapse leverages Zig’s manual memory management and “Comptime” to optimize the traversal of sparse protein matrices.
The Algorithm
The prioritization of disease genes within the PPI network is calculated using a weighted adjacency score:
\[S_{uv} = \frac{|\mathcal{N}(u) \cap \mathcal{N}(v)|}{\sqrt{|\mathcal{N}(u)| \cdot |\mathcal{N}(v)|}}\]Implementation
By utilizing a Compressed Sparse Row (CSR) format, Zinapse achieves significant cache efficiency over standard adjacency lists.
```zig const PPI_Network = struct { values: []f32, col_indices: []u32, row_ptr: []u32,
pub fn deinit(self: *PPI_Network, allocator: Allocator) void {
allocator.free(self.values);
allocator.free(self.col_indices);
allocator.free(self.row_ptr);
} };