{"id":358016,"date":"2017-01-25T20:01:59","date_gmt":"2017-01-26T04:01:59","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/?post_type=msr-research-item&#038;p=358016"},"modified":"2018-10-16T21:01:31","modified_gmt":"2018-10-17T04:01:31","slug":"protein-ranking-local-global-structure-protein-similarity-network","status":"publish","type":"msr-research-item","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/protein-ranking-local-global-structure-protein-similarity-network\/","title":{"rendered":"Protein Ranking: From Local to Global Structure in the Protein Similarity Network"},"content":{"rendered":"<p>Biologists regularly search databases of DNA or protein sequences for evolutionary or functional relationships to a given query sequence. We describe a ranking algorithm that exploits the entire network structure of similarity relationships among proteins in a sequence database by performing a diffusion operation on a precomputed, weighted network. The resulting ranking algorithm, evaluated by using a human-curated database of protein structures, is efficient and provides significantly better rankings than a local network search algorithm such as <span class=\"sc\">psi-blast<\/span>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Biologists regularly search databases of DNA or protein sequences for evolutionary or functional relationships to a given query sequence. We describe a ranking algorithm that exploits the entire network structure of similarity relationships among proteins in a sequence database by performing a diffusion operation on a precomputed, weighted network. The resulting ranking algorithm, evaluated by [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"Proceedings of the National Academy of Science (PNAS) 101(17)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"17","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"6559\u20136563","msr_page_range_start":"6559","msr_page_range_end":"6563","msr_series":"","msr_volume":"101","msr_copyright":"","msr_conference_name":"Proceedings of the National Academy of Science (PNAS) 101(17)","msr_doi":"10.1073\/pnas.0308067101","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2004-12-04","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"http:\/\/www.pnas.org\/content\/101\/17\/6559.abstract","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13561,13553],"msr-publication-type":[193716],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-358016","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-algorithms","msr-research-area-medical-health-genomics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the National Academy of Science (PNAS) 101(17)","msr_affiliation":"","msr_published_date":"2004-12-04","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"6559\u20136563","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"101","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"17","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"http:\/\/www.pnas.org\/content\/101\/17\/6559.abstract","msr_doi":"10.1073\/pnas.0308067101","msr_publication_uploader":[{"type":"url","title":"http:\/\/www.pnas.org\/content\/101\/17\/6559.abstract","viewUrl":false,"id":false,"label_id":0},{"type":"doi","title":"10.1073\/pnas.0308067101","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[{"id":0,"url":"http:\/\/www.pnas.org\/content\/101\/17\/6559.abstract"}],"msr-author-ordering":[{"type":"text","value":"Jason Weston","user_id":0,"rest_url":false},{"type":"text","value":"Andre Elisseeff","user_id":0,"rest_url":false},{"type":"user_nicename","value":"denzho","user_id":31609,"rest_url":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=denzho"},{"type":"text","value":"Christina S. 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