{"id":166805,"date":"2014-06-06T00:00:00","date_gmt":"2014-06-06T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/defining-an-essential-transcriptional-factor-program-for-naive-pluripotency\/"},"modified":"2018-11-27T05:38:11","modified_gmt":"2018-11-27T13:38:11","slug":"defining-an-essential-transcriptional-factor-program-for-naive-pluripotency","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/defining-an-essential-transcriptional-factor-program-for-naive-pluripotency\/","title":{"rendered":"Defining an essential transcriptional factor program for naive pluripotency"},"content":{"rendered":"<div class=\"asset-content\">\n<p>The gene regulatory circuitry through which pluripotent embryonic stem (ES) cells choose between self-renewal and differentiation appears vast and has yet to be distilled into an executive molecular program. We developed a data-constrained, computational approach to reduce complexity and to derive a set of functionally validated components and interaction combinations sufficient to explain observed ES cell behavior. This minimal set, the simplest version of which comprises only 16 interactions, 12 components, and three inputs, satisfies all prior specifications for self-renewal and furthermore predicts unknown and nonintuitive responses to compound genetic perturbations with an overall accuracy of 70%. We propose that propagation of ES cell identity is not determined by a vast interactome but rather can be explained by a relatively simple process of molecular computation.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The gene regulatory circuitry through which pluripotent embryonic stem (ES) cells choose between self-renewal and differentiation appears vast and has yet to be distilled into an executive molecular program. We developed a data-constrained, computational approach to reduce complexity and to derive a set of functionally validated components and interaction combinations sufficient to explain observed ES [&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":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"Science","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"1156","msr_page_range_end":"","msr_series":"","msr_volume":"344","msr_copyright":"","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Graziano Martello, Austin Smith","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":"2014-6-6","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"http:\/\/www.sciencemag.org\/content\/344\/6188\/1156.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":[13546],"msr-publication-type":[193715],"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-166805","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-computational-sciences-mathematics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2014-6-6","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"Science","msr_volume":"344","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","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.sciencemag.org\/content\/344\/6188\/1156.abstract","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"http:\/\/www.sciencemag.org\/content\/344\/6188\/1156.abstract","label_id":"243109","label":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.sciencemag.org\/content\/344\/6188\/1156.abstract"}],"msr-author-ordering":[{"type":"user_nicename","value":"Sara-Jane Dunn","user_id":33523,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sara-Jane Dunn"},{"type":"text","value":"Graziano Martello","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Boyan Yordanov","user_id":35043,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Boyan Yordanov"},{"type":"user_nicename","value":"Stephen Emmott","user_id":33572,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Stephen Emmott"},{"type":"text","value":"Austin Smith","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[544545,170870],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":544545,"post_title":"Station B","post_name":"stationb","post_type":"msr-project","post_date":"2019-03-11 15:56:07","post_modified":"2021-09-28 09:10:36","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/stationb\/","post_excerpt":"Our work on the Station B project has now been retired. We continue to actively explore the exciting intersection of computing and life sciences, with other projects located on\u00a0www.microsoft.com\/research. Building a platform for programming biology The ability to program biology could enable fundamental breakthroughs across a broad range of industries, including medicine, agriculture, food, construction, textiles, materials and chemicals. It could also help lay the foundation for a future bioeconomy based on sustainable technology. 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The development of system-level, mechanistic, computational models has the potential to become a foundation for improving our understanding of natural biological systems, and for designing engineered biological systems with wide-ranging applications in nanomedicine, nanomaterials and computing. 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