We are analyzing https://link.springer.com/article/10.1007/bf02100085.

Title:
Aligning amino acid sequences: Comparison of commonly used methods | Journal of Molecular Evolution
Description:
We examined two extensive families of protein sequences using four different alignment schemes that employ various degrees of “weighting” in order to determine which approach is most sensitive in establishing relationships. All alignments used a similarity approach based on a general algorithm devised by Needleman and Wunsch. The approaches included a simple program, UM (unitary matrix), whereby only identities are scored; a scheme in which the genetic code is used as a basis for weighting (GC); another that employs a matrix based on structural similarity of amino acids taken together with the genetic basis of mutation (SG); and a fourth that uses the empirical log-odds matrix (LOM) developed by Dayhoff on the basis of observed amino acid replacements. The two sequence families examined were (a) nine different globins and (b) nine different tyrosine kinase-like proteins. It was assumed a priori that all members of a family share common ancestry. In cases where two sequences were more than 30% identical, alignments by all four methods were almost always the same. In cases where the percentage identity was less than 20%, however, there were often significant differences in the alignments. On the average, the Dayhoff LOM approach was the most effective in verifying distant relationships, as judged by an empirical “jumbling test.” This was not universally the case, however, and in some instances the simple UM was actually as good or better. Trees constructed on the basis of the various alignments differed with regard to their limb lengths, but had essentially the same branching orders. We suggest some reasons for the different effectivenesses of the four approaches in the two different sequence settings, and offer some rules of thumb for assessing the significance of sequence relationships.
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Keywords {🔍}

google, scholar, article, pubmed, sequence, amino, acid, protein, sequences, mol, usa, dayhoff, proteins, gene, biol, structure, proc, natl, sci, nucleotide, virus, doolittle, access, acad, sarcoma, nature, privacy, cookies, content, journal, research, search, methods, relationships, alignments, similarity, evolutionary, fitch, transforming, analysis, information, publish, basis, structural, related, products, kinase, smith, cell, data,

Topics {✒️}

month download article/chapter tyrosine-specific kinase activity barker wc genome sequence analysis amino acid sequence amino acid sequences feline retroviral oncogenes empirical log-odds matrix primary structure homology molecular evolution aims related subjects full article pdf bovine liver rhodanese privacy choices/manage cookies usage analysis 3d-structural information multiple protein alignments protein sequence otheronc gene products protein evolution tyrosine kinase unique oncogene transduced rous sarcoma virus fujinami sarcoma virus mouse sarcoma virus biological sequence metrics protein sequences empirical “jumbling test check access koshland de jr instant access european economic area scope submit manuscript alignment schemes ubiquitous edge effect establishing homologies similar conformational states ein neuer hämkomplex sequence families examined matching biological sequences conditions privacy policy major polypeptide chain maximum parsimony method general method applicable comparative biosequence metrics smallest polypeptide chain verifying distant relationships detecting distant relationships general algorithm devised minimal length trees

Questions {❓}

Doolittle RF (1981) Similar amino acid sequences: chance or common ancestry?

Schema {🗺️}

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         headline:Aligning amino acid sequences: Comparison of commonly used methods
         description:We examined two extensive families of protein sequences using four different alignment schemes that employ various degrees of “weighting” in order to determine which approach is most sensitive in establishing relationships. All alignments used a similarity approach based on a general algorithm devised by Needleman and Wunsch. The approaches included a simple program, UM (unitary matrix), whereby only identities are scored; a scheme in which the genetic code is used as a basis for weighting (GC); another that employs a matrix based on structural similarity of amino acids taken together with the genetic basis of mutation (SG); and a fourth that uses the empirical log-odds matrix (LOM) developed by Dayhoff on the basis of observed amino acid replacements. The two sequence families examined were (a) nine different globins and (b) nine different tyrosine kinase-like proteins. It was assumed a priori that all members of a family share common ancestry. In cases where two sequences were more than 30% identical, alignments by all four methods were almost always the same. In cases where the percentage identity was less than 20%, however, there were often significant differences in the alignments. On the average, the Dayhoff LOM approach was the most effective in verifying distant relationships, as judged by an empirical “jumbling test.” This was not universally the case, however, and in some instances the simple UM was actually as good or better. Trees constructed on the basis of the various alignments differed with regard to their limb lengths, but had essentially the same branching orders. We suggest some reasons for the different effectivenesses of the four approaches in the two different sequence settings, and offer some rules of thumb for assessing the significance of sequence relationships.
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      headline:Aligning amino acid sequences: Comparison of commonly used methods
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