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{"title"=>"Amino acid properties conserved in molecular evolution", "type"=>"journal", "authors"=>[{"first_name"=>"Witold R.", "last_name"=>"Rudnicki", "scopus_author_id"=>"6603769382"}, {"first_name"=>"Teresa", "last_name"=>"Mroczek", "scopus_author_id"=>"56045543500"}, {"first_name"=>"Paweł", "last_name"=>"Cudek", "scopus_author_id"=>"57028650200"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"24967708", "isbn"=>"10.1371/journal.pone.0098983", "doi"=>"10.1371/journal.pone.0098983", "issn"=>"19326203", "scopus"=>"2-s2.0-84903388936", "pui"=>"373399498", "sgr"=>"84903388936"}, "id"=>"010ec2d2-6d2d-3557-869d-5c9ef56658bb", "abstract"=>"That amino acid properties are responsible for the way protein molecules evolve is natural and is also reasonably well supported both by the structure of the genetic code and, to a large extent, by the experimental measures of the amino acid similarity. Nevertheless, there remains a significant gap between observed similarity matrices and their reconstructions from amino acid properties. Therefore, we introduce a simple theoretical model of amino acid similarity matrices, which allows splitting the matrix into two parts - one that depends only on mutabilities of amino acids and another that depends on pairwise similarities between them. Then the new synthetic amino acid properties are derived from the pairwise similarities and used to reconstruct similarity matrices covering a wide range of information entropies. Our model allows us to explain up to 94% of the variability in the BLOSUM family of the amino acids similarity matrices in terms of amino acid properties. The new properties derived from amino acid similarity matrices correlate highly with properties known to be important for molecular evolution such as hydrophobicity, size, shape and charge of amino acids. This result closes the gap in our understanding of the influence of amino acids on evolution at the molecular level. The methods were applied to the single family of similarity matrices used often in general sequence homology searches, but it is general and can be used also for more specific matrices. The new synthetic properties can be used in analyzes of protein sequences in various biological applications.", "link"=>"http://www.mendeley.com/research/amino-acid-properties-conserved-molecular-evolution", "reader_count"=>15, "reader_count_by_academic_status"=>{"Researcher"=>2, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>1, "Other"=>2, "Student > Master"=>2, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Researcher"=>2, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>1, "Other"=>2, "Student > Master"=>2, "Student > Bachelor"=>2, "Professor"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>3, "Agricultural and Biological Sciences"=>7, "Medicine and Dentistry"=>1, "Physics and Astronomy"=>1, "Computer Science"=>3}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>7}, "Computer Science"=>{"Computer Science"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}}, "reader_count_by_country"=>{"Poland"=>1, "United Kingdom"=>1, "France"=>1}, "group_count"=>0}

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• http://doi.org/10.1038/s41598-019-45916-3
• http://doi.org/10.1186/s12862-018-1304-0

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• {"id"=>"482287994708054016", "text"=>"#PLOSONE: Amino Acid Properties Conserved in Molecular Evolution http://t.co/8dsa8VG4Xv", "created_at"=>"2014-06-26T22:23:13Z", "user"=>"DrJCThrash", "user_name"=>"Cameron Thrash", "user_profile_image"=>"http://pbs.twimg.com/profile_images/469124779589382144/5UBI8ekz_normal.jpeg"}
• {"id"=>"482310361459073025", "text"=>"RT @DrJCThrash: #PLOSONE: Amino Acid Properties Conserved in Molecular Evolution http://t.co/8dsa8VG4Xv", "created_at"=>"2014-06-26T23:52:05Z", "user"=>"OmicsOmicsBlog", "user_name"=>"Keith Robison", "user_profile_image"=>"http://pbs.twimg.com/profile_images/458775500815863810/_Lep3QcI_normal.jpeg"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/1568060"], "description"=>"<p>The optimal number of eigenvectors was obtained with the help of the Bayesian Information Criterion.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "optimal", "eigenvectors", "reconstruction", "blosum"], "article_id"=>1085216, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.g004", "stats"=>{"downloads"=>2, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_optimal_number_of_eigenvectors_for_reconstruction_of_the_BLOSUM_matrices_/1085216", "title"=>"The optimal number of eigenvectors for reconstruction of the BLOSUM matrices.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568062"], "description"=>"<p>The matrix was reconstructed using G-matrix and 5 eigenvectors derived from BLOSUM100 matrix. The triangle above diagonal displays differences between matrices scaled to half bit units and rounded, the diagonal and triangle below displays differences between matrices scaled to half bit units and not rounded. The shades of gray correspond to the differences.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "differences", "blosum62", "matrix"], "article_id"=>1085217, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.g005", "stats"=>{"downloads"=>1, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_differences_between_original_BLOSUM62_matrix_and_its_reconstruction_/1085217", "title"=>"The differences between original BLOSUM62 matrix and its reconstruction.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568064"], "description"=>"<p>Six panels display projections of amino acids on all combinations space spanned on four eigenvectors: EV2, EV3, EV4 and EV5.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "acids", "eigenvector"], "article_id"=>1085219, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.g006", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Amino_acids_in_the_eigenvector_space_/1085219", "title"=>"Amino acids in the eigenvector space.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568065"], "description"=>"<p>The column heads: L²_2–5– The square of length of property vector projected onto hyperplane spanned on the eigenvectors 2–5; r_i² (i = 1–6) – the square of correlation coefficient with i-th eigenvector. The values highlighted in boldface are a maximum in the column; the corresponding property is also highlighted in boldface. The values above 0.10 are underlined.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "amino", "correlate", "eigenvectors", "blosum100"], "article_id"=>1085220, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.t004", "stats"=>{"downloads"=>8, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_amino_acid_properties_that_highly_correlate_with_the_eigenvectors_of_the_BLOSUM100_matrix_/1085220", "title"=>"The amino acid properties that highly correlate with the eigenvectors of the BLOSUM100 matrix.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568067"], "description"=>"<p>Eigenvectors of BLOSUM100 matrix.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "blosum100"], "article_id"=>1085222, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.t001", "stats"=>{"downloads"=>4, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Eigenvectors_of_BLOSUM100_matrix_/1085222", "title"=>"Eigenvectors of BLOSUM100 matrix.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568068"], "description"=>"<p>The N refers to the number of eigenvectors used in the final reconstruction, whereas Ei are the optimised coefficients. In the case of BLOSUM30 the eigenvalues of BLOSUM30 are used.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "coefficients", "matrix", "reconstruction"], "article_id"=>1085223, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.t003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Optimised_coefficients_for_matrix_reconstruction_for_final_models_/1085223", "title"=>"Optimised coefficients for matrix reconstruction for final models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568069"], "description"=>"<p>The fraction of variance in an original BLOSUM matrix explained by reconstruction carried out with the eigenvectors of BLOSUM100 matrix. The number of eigenvectors varied between 0 (the reconstruction using the non-specific G-matrix only) and 5.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "variance", "explained", "eigenvectors", "reconstructed", "blosum"], "article_id"=>1085225, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.t002", "stats"=>{"downloads"=>5, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_variance_explained_by_the_eigenvectors_in_reconstructed_BLOSUM_matrices_/1085225", "title"=>"The variance explained by the eigenvectors in reconstructed BLOSUM matrices.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568042"], "description"=>"<p>Squares of correlation coefficients between eigenvectors obtained from B^x matrix with the eigenvectors obtained from the B¹⁰⁰ matrix.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "coefficients", "eigenvectors", "matrix"], "article_id"=>1085197, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Squares_of_correlation_coefficients_between_eigenvectors_obtained_from_B_x_matrix_with_the_eigenvectors_obtained_from_the_B_100_matrix_/1085197", "title"=>"Squares of correlation coefficients between eigenvectors obtained from B^x matrix with the eigenvectors obtained from the B¹⁰⁰ matrix.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568048"], "description"=>"<p>The i-th model of each matrix is reconstructed using i eigenvectors. The reconstruction with i = 0 is limited to G-matrix, the remaining models use eigenvectors EVi (i = 1…6). The left panel displays entire range of r², the right panel is a close-up for r² larger than 0.8.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "coefficients", "of-diagonal", "elements", "matrices"], "article_id"=>1085203, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.g002", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Squares_of_correlation_coefficients_between_the_of_diagonal_elements_of_B_x_matrices_and_their_reconstructions_/1085203", "title"=>"Squares of correlation coefficients between the of-diagonal elements of B^x matrices and their reconstructions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-26 03:06:51"}
• {"files"=>["https://ndownloader.figshare.com/files/1568057"], "description"=>"<p>The value on Y-axis is a fraction of best possible reconstruction achieved by the model. It is estimated as a fraction of r² achieved in reconstruction with eigenvectors derived from <b>B</b>¹⁰⁰ and r² obtained in reconstruction with its own eigenvectors. The left panel displays entire range of Y, the right panel is a close-up for Y larger than 0.9.</p>", "links"=>[], "tags"=>["Biochemistry", "proteomics", "biophysics", "Biophysics theory", "Computational biology", "Evolutionary biology", "Evolutionary processes", "microevolution", "genetics", "Molecular genetics", "molecular biology", "Molecular biology techniques", "Sequencing techniques", "Sequence analysis", "Theoretical biology", "reconstructed"], "article_id"=>1085212, "categories"=>["Biological Sciences"], "users"=>["Witold R. Rudnicki", "Teresa Mroczek", "Paweł Cudek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098983.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_relative_quality_of_the_reconstructed_matrices_/1085212", "title"=>"The relative quality of the reconstructed matrices.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-26 03:06:51"}
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• {"unique-ip"=>"22", "full-text"=>"20", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
• {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[282]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[271]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[286]}]}

F1000Prime