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The TM-score indicates the similarity between two structures by a score between (,], where 1 indicates a perfect match between two structures (thus the higher the better). [1] Generally scores below 0.20 corresponds to randomly chosen unrelated proteins whereas structures with a score higher than 0.5 assume roughly the same fold. [ 2 ]
Transitive Consistency Score (TCS) is an extended version of the T-Coffee scoring scheme. [14] It uses T-Coffee libraries of pairwise alignments to evaluate any third party MSA. Pairwise projections can be produced using fast or slow methods, thus allowing a trade-off between speed and accuracy.
TM-align TM-score based protein structure alignment: Cα: Pair: nil: server and download: Y. Zhang & J. Skolnick: 2005 mTM-align Multiple protein structure alignment based on TM-align Cα Multi No server and download: R. Dong, Z. Peng, Y. Zhang & J. Yang 2018 VAST Vector Alignment Search Tool: SSE: Pair: nil: server: S. Bryant: 1996 PrISM
TM-score – a different structure comparison measure; Longest continuous segment (LCS) — A different structure comparison measure; Global distance calculation (GDC_sc, GDC_all) — Structure comparison measures that use full-model information (not just α-carbon) to assess similarity
Each of these scenarios is assigned a score and the sum of the scores of all the pairings is the score of the whole alignment candidate. Different systems exist for assigning scores; some have been outlined in the Scoring systems section below. For now, the system used by Needleman and Wunsch [1] [failed verification] will be used:
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The profile-HMM implementation used in the HMMER software was based on the work of Krogh and colleagues. [3] HMMER is a console utility ported to every major operating system, including different versions of Linux, Windows, and macOS. HMMER is the core utility that protein family databases such as Pfam and InterPro are based upon.
In software development, a traceability matrix (TM) [1]: 244 is a document, usually in the form of a table, used to assist in determining the completeness of a relationship by correlating any two baselined documents using a many-to-many relationship comparison.