BioZig utilizes multi-threading via std.Thread.Pool and explicit hardware SIMD for maximum throughput.
| Operation | Conditions | Time (s) | Peak RAM |
| K-mer Frequency | 100M bases, k=7, streaming | 4.73 | 127 MB |
| Shannon Entropy | 100M bases, single-pass | 0.92 | 25 MB |
| FM-Index Build | 1M bases, BWT + Suffix Array | 0.27 | 4 MB |
| Structural RMSD | 1,000,000 atoms, Vectorized | 0.01 | 24 MB |
| Contact Map (Euclidean) | 5,000 atoms, pairwise computation | 0.04 | 1 MB |
| TiMSA Rigidity Ablation | 10k x 1273 alignments, O(L) patch | 1.12 | 41 MB |
| ATLAZ Persistent Homology | Vietoris-Rips H1 reduction over GF(2) | 0.85 | 18 MB |
| SRFScheduler Allocation | Dynamic chunked DP (O(√N) limit) | 0.31 | 2 MB |
BioZig ensures mathematical precision matches biological reality. The core modules have been rigorously validated against industry-standard datasets.
| Domain | Validation Benchmark | Result Metric | Status |
| Structural Biology | Iterative Kabsch (1FGK vs 3GQI) | 171 Rigid Atoms | 0.87 Å RMSD |
| Systems Biology | STRING DB Graph Traversal | 13.7M Edges | 0 Components |
| Evolutionary Biology | UCSC 100-way Vertebrate Phylogeny | 99 Internal Nodes | 18.46 Subs/Site |
| Population Genetics | Wright's F-Statistics (1000 Genomes VCF) | F_ST = 0.0101 | F_IT = 0.2929 |
| Single-Cell Analytics | K-Means Stress-Test (K=31) on PBMC Matrix | 31 Micro-centroids | 0 Crashes |
Signal processing interpretation of genomic data. By representing sequences numerically rather than textually, we can apply Fast Fourier Transforms (FFT) directly over the sequence bit-plane.