AlloSigMA statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Protein-ligand docking Allosteric site prediction chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

AlloSigMA specifications


Unique identifier OMICS_25247
Name AlloSigMA
Alternative name Allosteric SIGnaling and Mutation Analysis
Interface Web user interface
Restrictions to use None
Input data A protein sequence or a PDB ID.
Input format PDB
Programming languages Python
Computer skills Basic
Stability Stable
Maintained Yes


  • person_outline Igor N. Berezovsky <>
  • person_outline Enrico Guarnera <>
  • person_outline Zhen Wan Tan <>

Publication for Allosteric SIGnaling and Mutation Analysis

AlloSigMA in publication

PMCID: 5835713
PMID: 29437904
DOI: 10.1042/BSR20171113

[…] large subunits of rt (i.e. effects caused by the pockets on the p51 subunit to the polymerase active site on the p66 subunit). for this, we used a statistical mechanical model [] (implemented in the allosigma server []) to estimate the energies exerted by the allosteric communication., in the allosigma server, the allosteric communications were estimated based on the responses of each residue […]

To access a full list of publications, you will need to upgrade to our premium service.

AlloSigMA institution(s)
Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Biological Sciences (DBS), National University of Singapore (NUS), Singapore

AlloSigMA reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review AlloSigMA