finding the equivalent of a wild-type thermodynamic state of an existing gene segment in other (unknown) instantiations of the biologic system, in both noncoding and coding gene regions. In coding regions, TT processes amino acid sequences in a codonbased 3-letter code with additional information about choice of codon alternatives. Differences in TT (mutant-wt, case-control) were used to assess objectives 1 and 2 for the genes coding for human CD14, TLR4, tumor necrosis factor (TNF), and activated protein C (APC). Results: Comparison of calculated TT profiles of the human CD14, TLR4, TNF, and APC genes with 16 species–based conservation profiles (ENCODE http://genome.ucsc.edu/) validated the evolutionary relevance of TT profiles, showing a significant correlation of interspecies conservation to low thermodynamically tolerant regions. Network analysis of context similarities captured by TT descriptors in TNF revealed a hierarchical block structure of this network that directly identifies precursor and mature protein segments, structural domains in the mature protein structure, and noncontiguous regions that are in direct contact in the folded TNF. For CD14 and APC, TT analysis gave insights with regard to protein-protein interaction sites in the oligomeric structure, and the correlation of structural periodicity to the periodicity of the TT characterization of the coding sequence. Thermodynamic tolerance profiles were used for interspecies comparisons of human-mouse (H-M) pairs, based on the assumption that optimal alignment of sequence H and M is the alignment in which the difference between TT(H) and TT(M) is minimal. This approach was used to obtain optimal unbiased differential TT potentials for H and M paralogs that were compared with various aspects of function. Conclusions: Thermodynamic tolerance analysis is a novel method that appears applicable to various types of analysis of inflammationrelated genes. This approach of using networks of TT-based similarities captured in corresponding adjacency matrices allows for the combination of both local and global impact of a given SNP at a particular locus. Differences between wild-type and mutant coding sequence TT descriptors in and adjacency matrices capturing networks of TT-based similarities are useful for the single sequence–based quantitative characterization of structural or functional impact of a mutation on a given gene.