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.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {📚}

Education
Science
Social Networks

Content Management System {📝}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month

Based on our best estimate, this website will receive around 7,625,932 visitors per month in the current month.

check SE Ranking
check Ahrefs
check Similarweb
check Ubersuggest
check Semrush

How Does Link.springer.com Make Money? {💸}

We can't tell how the site generates income.

Not every website is profit-driven; some are created to spread information or serve as an online presence. Websites can be made for many reasons. This could be one of them. Link.springer.com has a revenue plan, but it's either invisible or we haven't found it.

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 {🗺️}

WebPage:
      mainEntity:
         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.
         datePublished:
         dateModified:
         pageStart:112
         pageEnd:125
         sameAs:https://doi.org/10.1007/BF02100085
         keywords:
            Amino acid sequence alignment
            Tyrosine kinases
            Globins
            Homologies
            Evolutionary Biology
            Microbiology
            Plant Sciences
            Plant Genetics and Genomics
            Animal Genetics and Genomics
            Cell Biology
         image:
         isPartOf:
            name:Journal of Molecular Evolution
            issn:
               1432-1432
               0022-2844
            volumeNumber:21
            type:
               Periodical
               PublicationVolume
         publisher:
            name:Springer-Verlag
            logo:
               url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
               type:ImageObject
            type:Organization
         author:
               name:D. F. Feng
               affiliation:
                     name:University of California
                     address:
                        name:Department of Chemistry, University of California, San Diego, La Jolla, USA
                        type:PostalAddress
                     type:Organization
               type:Person
               name:M. S. Johnson
               affiliation:
                     name:University of California
                     address:
                        name:Department of Chemistry, University of California, San Diego, La Jolla, USA
                        type:PostalAddress
                     type:Organization
               type:Person
               name:R. F. Doolittle
               affiliation:
                     name:University of California
                     address:
                        name:Department of Chemistry, University of California, San Diego, La Jolla, USA
                        type:PostalAddress
                     type:Organization
               type:Person
         isAccessibleForFree:
         hasPart:
            isAccessibleForFree:
            cssSelector:.main-content
            type:WebPageElement
         type:ScholarlyArticle
      context:https://schema.org
ScholarlyArticle:
      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.
      datePublished:
      dateModified:
      pageStart:112
      pageEnd:125
      sameAs:https://doi.org/10.1007/BF02100085
      keywords:
         Amino acid sequence alignment
         Tyrosine kinases
         Globins
         Homologies
         Evolutionary Biology
         Microbiology
         Plant Sciences
         Plant Genetics and Genomics
         Animal Genetics and Genomics
         Cell Biology
      image:
      isPartOf:
         name:Journal of Molecular Evolution
         issn:
            1432-1432
            0022-2844
         volumeNumber:21
         type:
            Periodical
            PublicationVolume
      publisher:
         name:Springer-Verlag
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:D. F. Feng
            affiliation:
                  name:University of California
                  address:
                     name:Department of Chemistry, University of California, San Diego, La Jolla, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:M. S. Johnson
            affiliation:
                  name:University of California
                  address:
                     name:Department of Chemistry, University of California, San Diego, La Jolla, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:R. F. Doolittle
            affiliation:
                  name:University of California
                  address:
                     name:Department of Chemistry, University of California, San Diego, La Jolla, USA
                     type:PostalAddress
                  type:Organization
            type:Person
      isAccessibleForFree:
      hasPart:
         isAccessibleForFree:
         cssSelector:.main-content
         type:WebPageElement
["Periodical","PublicationVolume"]:
      name:Journal of Molecular Evolution
      issn:
         1432-1432
         0022-2844
      volumeNumber:21
Organization:
      name:Springer-Verlag
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:University of California
      address:
         name:Department of Chemistry, University of California, San Diego, La Jolla, USA
         type:PostalAddress
      name:University of California
      address:
         name:Department of Chemistry, University of California, San Diego, La Jolla, USA
         type:PostalAddress
      name:University of California
      address:
         name:Department of Chemistry, University of California, San Diego, La Jolla, USA
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
      name:D. F. Feng
      affiliation:
            name:University of California
            address:
               name:Department of Chemistry, University of California, San Diego, La Jolla, USA
               type:PostalAddress
            type:Organization
      name:M. S. Johnson
      affiliation:
            name:University of California
            address:
               name:Department of Chemistry, University of California, San Diego, La Jolla, USA
               type:PostalAddress
            type:Organization
      name:R. F. Doolittle
      affiliation:
            name:University of California
            address:
               name:Department of Chemistry, University of California, San Diego, La Jolla, USA
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Department of Chemistry, University of California, San Diego, La Jolla, USA
      name:Department of Chemistry, University of California, San Diego, La Jolla, USA
      name:Department of Chemistry, University of California, San Diego, La Jolla, USA
WebPageElement:
      isAccessibleForFree:
      cssSelector:.main-content

External Links {🔗}(105)

Analytics and Tracking {📊}

Google Tag Manager

Libraries {📚}

Clipboard.js
Prism.js

CDN Services {📦}

Crossref

5.04s.

LINK . SPRINGER . COM {}