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{"title"=>"Prediction of protein-protein interaction sites in sequences and 3D structures by random forests", "type"=>"journal", "authors"=>[{"first_name"=>"Mile", "last_name"=>"Šikić", "scopus_author_id"=>"23971743300"}, {"first_name"=>"Sanja", "last_name"=>"Tomić", "scopus_author_id"=>"7103046286"}, {"first_name"=>"Kristian", "last_name"=>"Vlahoviček", "scopus_author_id"=>"6602149624"}], "year"=>2009, "source"=>"PLoS Computational Biology", "identifiers"=>{"sgr"=>"59149087824", "doi"=>"10.1371/journal.pcbi.1000278", "issn"=>"1553734X", "pui"=>"354131993", "isbn"=>"0360362214", "pmid"=>"19180183", "scopus"=>"2-s2.0-59149087824"}, "id"=>"2f03c095-4861-3dc6-91b1-a23bd0266601", "abstract"=>"Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i) a combination of sequence- and structure-derived parameters and (ii) sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.", "link"=>"http://www.mendeley.com/research/prediction-proteinprotein-interaction-sites-sequences-3d-structures-random-forests-6", "reader_count"=>10, "reader_count_by_academic_status"=>{"Researcher"=>3, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>2, "Student > Postgraduate"=>1, "Student > Master"=>1, "Other"=>1, "Student > Bachelor"=>1}, "reader_count_by_user_role"=>{"Researcher"=>3, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>2, "Student > Postgraduate"=>1, "Student > Master"=>1, "Other"=>1, "Student > Bachelor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Biochemistry, Genetics and Molecular Biology"=>2, "Mathematics"=>1, "Agricultural and Biological Sciences"=>3, "Physics and Astronomy"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Mathematics"=>{"Mathematics"=>1}}, "group_count"=>0}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/910497"], "description"=>"a<p>The ratio between the number of positive labeled instaces and the number of negative labeled instances.</p>b<p>The results obtained by combining classifiers.</p>", "links"=>[], "tags"=>["3d"], "article_id"=>580955, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.t004", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_of_the_results_obtained_by_prediction_based_on_sequence_and_3D_structure_information_/580955", "title"=>"Evaluation of the results obtained by prediction based on sequence and 3D structure information.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 07:05:10"}
• {"files"=>["https://ndownloader.figshare.com/files/910152"], "description"=>"<p>It can been seen that the most important variables are residue names, followed by non-polar ASA, maximum depth index, relative non-polar ASA, average depth index, and minimum protrusion index.</p>", "links"=>[], "tags"=>["Computational biology"], "article_id"=>580613, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g005", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Variable_importance_/580613", "title"=>"Variable importance.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:03:09"}
• {"files"=>["https://ndownloader.figshare.com/files/910253"], "description"=>"<p>The figure presents precision–recall curves of the following methods: prediction of interacting residues when a positive class is labelled if at least the central residue is an interacting residue (red curve), combining classifiers (blue curve), randomization testing (green curve).</p>", "links"=>[], "tags"=>["graph", "3d"], "article_id"=>580712, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g006", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Precision_8211_recall_graph_for_prediction_based_on_both_sequence_and_3D_structure_/580712", "title"=>"Precision–recall graph for prediction based on both sequence and 3D structure.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:03:44"}
• {"files"=>["https://ndownloader.figshare.com/files/910605"], "description"=>"a<p>The ratio between the number of positive labeled instaces and the number of negative labeled instances.</p>b<p>The results obtained by combining classifiers.</p>", "links"=>[], "tags"=>["Computational biology"], "article_id"=>581065, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.t001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_of_the_results_obtained_by_prediction_based_on_sequence_information_/581065", "title"=>"Evaluation of the results obtained by prediction based on sequence information.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 07:05:47"}
• {"files"=>["https://ndownloader.figshare.com/files/910092"], "description"=>"<p>The histogram of recall values for overall set precision at 48% and recall at 53%.</p>", "links"=>[], "tags"=>["Computational biology"], "article_id"=>580556, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g004", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Histogram_of_recall_values_for_chains_/580556", "title"=>"Histogram of recall values for chains.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:02:49"}
• {"files"=>["https://ndownloader.figshare.com/files/909945"], "description"=>"<p>The figure presents precision–recall curves of the following methods: prediction of interacting residues when a positive class is labelled if at least the central residue is an interacting residue (red curve), combining classifiers (blue curve), randomization testing (green curve).</p>", "links"=>[], "tags"=>["graph"], "article_id"=>580402, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Precision_8211_recall_graph_for_prediction_based_on_sequence_alone_/580402", "title"=>"Precision–recall graph for prediction based on sequence alone.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:01:53"}
• {"files"=>["https://ndownloader.figshare.com/files/910035"], "description"=>"<p>The histogram of recall values for overall set precision at 48% and recall at 53%.</p>", "links"=>[], "tags"=>["Computational biology"], "article_id"=>580495, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Histogram_of_recall_values_for_protein_complexes_/580495", "title"=>"Histogram of recall values for protein complexes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:02:26"}
• {"files"=>["https://ndownloader.figshare.com/files/909877"], "description"=>"<p>Entropies for different window lengths were calculated and subtracted from entropies calculated for the uniform distribution of the number of interacting residues in the window.</p>", "links"=>[], "tags"=>["differences"], "article_id"=>580338, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g001", "stats"=>{"downloads"=>2, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Entropy_differences_for_different_window_lengths_/580338", "title"=>"Entropy differences for different window lengths.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:01:25"}
• {"files"=>["https://ndownloader.figshare.com/files/910323"], "description"=>"<p>The amino acid residues found as possible interacting sites are labelled using the three letters type name for Raf and the one letter type name for Ras. The Ras residues are shown in stick representation, and Raf in ball and stick representation.</p>", "links"=>[], "tags"=>["Computational biology"], "article_id"=>580787, "categories"=>["Biological Sciences"], "users"=>["Mile Šikić", "Sanja Tomić", "Kristian Vlahoviček"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000278.g007", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_of_the_Raf_8211_Ras_complex_/580787", "title"=>"Model of the Raf–Ras complex.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 07:04:11"}
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F1000Prime