Toward the regularization of E value from BLAST similarity search into a dissimilarity measure as distance function, and the metrication of protein sequence space
Boryeu Mao · 2026
Read Toward the regularization of E value from BLAST similarity search into a dissimilarity measure as distance function, and the metrication of protein sequence space by Boryeu Mao (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13395823.txt.
Description
Boryeu Mao, a bioinformatician, reworks the E value that BLAST reports when it matches a new sequence against known ones. A low E value marks a strong match, but comparing E values across very different searches can mislead. The mix-up stems from treating one number as both a likeness score and its opposite.
Through a simulated setup, Mao shows that adjusting the E value for self-matching fixes odd comparisons that crop up between searches. The corrected score behaves more like a true distance: it gains the reflexivity and triangle rules that metric spaces demand. In practice, the fix sharpens clustering of sequences and the picking of diverse subsets. The paper aims at cleaner all-against-all comparisons in big databases.
Catalog record
| CREATOR | Boryeu Mao |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |