[et_pb_section fb_built=”1″ fullwidth=”on” next_background_color=”#ffffff” admin_label=”Hero” _builder_version=”4.9.0″ background_image=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-content\/uploads\/sites\/417\/2022\/02\/it-services-02.jpg” parallax=”on” transform_scale=”102%|100%” transform_translate_linked=”off” custom_padding=”0px|0|0px|0px|false|false” bottom_divider_style=”wave2″ hover_enabled=”0″ sticky_enabled=”0″][et_pb_fullwidth_header title=”The Pejaver Laboratory” background_overlay_color=”rgba(0,0,0,0.24)” admin_label=”Fullwidth Header” _builder_version=”4.9.0″ title_font=”Share Tech||||||||” title_text_align=”left” title_font_size=”69px” title_line_height=”1.2em” content_font=”Open Sans||||||||” content_text_align=”left” content_font_size=”18px” background_color=”rgba(0,0,0,0)” use_background_color_gradient=”on” background_color_gradient_start=”rgba(0,72,114,0.9)” background_color_gradient_end=”rgba(41,17,96,0.8)” background_color_gradient_direction=”140deg” background_color_gradient_overlays_image=”on” background_image=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-content\/uploads\/sites\/417\/2022\/04\/modified_Dream_TradingCard.png” background_size=”initial” background_position=”bottom_right” background_repeat=”repeat-x” background_blend=”exclusion” transform_translate=”1px|0px” module_alignment=”left” custom_margin=”-34px||||false|false” custom_padding=”12vw||6vw||false|false” custom_padding_tablet=”100px||100px||true” custom_padding_phone=”|||” custom_padding_last_edited=”on|desktop” hover_enabled=”0″ title_font_size_tablet=”60px” title_font_size_phone=”36px” title_font_size_last_edited=”on|phone” content_font_size_tablet=”” content_font_size_phone=”16px” content_font_size_last_edited=”on|phone” button_one_text_size_tablet=”” button_one_text_size_phone=”” button_one_text_size_last_edited=”on|desktop” button_one_border_color_hover=”#ff8a3d” button_one_border_radius_hover=”100px” button_one_letter_spacing_hover=”5px” button_one_bg_color_hover=”#ff8a3d” button_one_text_size__hover_enabled=”off” button_two_text_size__hover_enabled=”off” button_one_text_color__hover_enabled=”off” button_two_text_color__hover_enabled=”off” button_one_border_width__hover_enabled=”off” button_two_border_width__hover_enabled=”off” button_one_border_color__hover_enabled=”on” button_one_border_color__hover=”#ff8a3d” button_two_border_color__hover_enabled=”off” button_one_border_radius__hover_enabled=”on” button_one_border_radius__hover=”100px” button_two_border_radius__hover_enabled=”off” button_one_letter_spacing__hover_enabled=”on” button_one_letter_spacing__hover=”5px” button_two_letter_spacing__hover_enabled=”off” button_one_bg_color__hover_enabled=”on” button_one_bg_color__hover=”#ff8a3d” button_two_bg_color__hover_enabled=”off” background_overlay_color__hover_enabled=”on|desktop” sticky_enabled=”0″]<\/p>\n
We develop, adapt and apply machine learning methods to relate <\/strong>genetic <\/strong><\/span><\/p>\n variation to molecular function and disease using secondary biomedical data sets<\/strong><\/span><\/p>\n [\/et_pb_fullwidth_header][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Our Services” _builder_version=”4.9.0″ min_height=”910.9px” custom_margin=”||||false|false” custom_padding=”|||”][et_pb_row _builder_version=”4.9.0″ min_height=”100px” custom_margin=”||||false|false” custom_padding=”5px||0px||false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.9.0″ text_font=”Share Tech||||||||” text_text_color=”rgba(0,0,0,0.02)” text_font_size=”100px” text_line_height=”0.2em” header_font=”||||||||” header_2_font=”Share Tech||||||||” header_2_font_size=”48px” header_2_line_height=”1.4em” text_orientation=”center” custom_margin=”||30px||false” custom_margin_tablet=”||0px|” custom_margin_phone=”” custom_margin_last_edited=”on|tablet” hover_enabled=”0″ text_font_size_tablet=”80px” text_font_size_phone=”60px” text_font_size_last_edited=”on|desktop” header_2_font_size_tablet=”” header_2_font_size_phone=”36px” header_2_font_size_last_edited=”on|phone” sticky_enabled=”0″]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.9.0″ custom_margin=”-29px|auto||auto||” custom_padding=”0px||||false|false”][et_pb_column type=”1_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_blurb title=”Genome Interpretation” url=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/research#vari” image=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-content\/uploads\/sites\/417\/2022\/04\/dna_white.png” alt=”Dna icons created by Eucalyp – Flaticon” _builder_version=”4.9.0″ header_font=”Share Tech||||||||” header_font_size=”24px” header_line_height=”1.2em” body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”1.8em” background_color=”#5499bf” background_layout=”dark” custom_padding=”40px|30px|40px|30px|true|true” animation=”off” link_option_url=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/research#vari” hover_enabled=”0″ sticky_enabled=”0″]<\/p>\n We integrate functional annotations and predictions to infer the impact of genetic variants individually and jointly over a genome on molecular and organismal phenotypes<\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_blurb title=”Data-driven Phenotyping” url=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/research#ehrs” image=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-content\/uploads\/sites\/417\/2022\/04\/data-analysis_white.png” alt=”Vaccine record icons created by pongsakornRed – Flaticon” _builder_version=”4.9.0″ header_font=”Share Tech||||||||” header_font_size=”24px” header_line_height=”1.2em” body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”1.8em” background_color=”#f75199″ custom_padding=”40px|30px|40px|30px|true|true” animation=”off” link_option_url=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/research#ehrs” hover_enabled=”0″ locked=”off” sticky_enabled=”0″]<\/p>\n We extract and model information from electronic health records (EHRs) to derive quantitative definitions of disease to aid in biomedical discovery and clinical diagnosis<\/span><\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_blurb title=”Applied Machine Learning” url=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/research#appliedml” image=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-content\/uploads\/sites\/417\/2022\/04\/cluster_white.png” alt=”Cluster icons created by Freepik – Flaticon” _builder_version=”4.9.0″ header_font=”Share Tech||||||||” header_font_size=”24px” header_line_height=”1.2em” body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”1.8em” background_color=”#41256d” custom_padding=”40px|30px|40px|30px|true|true” animation=”off” link_option_url=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/research#appliedml” border_width_all=”1px” border_color_all=”rgba(21,49,78,0.17)” locked=”off”]<\/p>\n We develop and adapt machine learning approaches that specifically address challenges relevant to biomedical data such as noise, bias and limited availability<\/span><\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.9.0″ _module_preset=”default” height=”100px” custom_margin=”-20px||||false|false”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_text _builder_version=”3.27.4″ text_font=”Share Tech||||||||” text_text_color=”rgba(0,0,0,0.02)” text_font_size=”100px” text_line_height=”0.2em” header_font=”||||||||” header_2_font=”Share Tech||||||||” header_2_font_size=”48px” header_2_line_height=”1.4em” text_orientation=”center” custom_margin=”||30px||false” custom_margin_tablet=”||0px|” custom_margin_phone=”” custom_margin_last_edited=”on|tablet” text_font_size_tablet=”80px” text_font_size_phone=”60px” text_font_size_last_edited=”on|desktop” header_2_font_size_tablet=”” header_2_font_size_phone=”36px” header_2_font_size_last_edited=”on|phone” locked=”off”]<\/p>\n <\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.9.0″ _module_preset=”default”][et_pb_column type=”4_4″ _builder_version=”4.9.0″ _module_preset=”default”][et_pb_slider _builder_version=”4.9.0″ _module_preset=”default”][et_pb_slide heading=”Multiple positions available” button_text=”Learn More” button_link=”https:\/\/labs.icahn.mssm.edu\/pejaverlab\/positions\/” _builder_version=”4.9.0″ _module_preset=”default” sticky_transition=”on”]<\/p>\n We are actively recruiting postdoctoral fellows and graduate students for a variety of projects. If you are interested in the intersection of biomedical data science, genomic medicine and machine learning and are looking for a supportive training environment, come join us!<\/p>\n [\/et_pb_slide][et_pb_slide heading=”COVID-19 prediction DREAM Challenge paper published” button_text=”Read the paper” button_link=”https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/article-abstract\/2784779″ url_new_window=”on” _builder_version=”4.9.0″ _module_preset=”default” sticky_transition=”on”]<\/p>\n Our paper titled “A continuously benchmarked and crowdsourced challenge for rapid development and evaluation of models to predict COVID-19 diagnosis and hospitalization” was just published in\u00a0JAMA Network Open<\/em>.<\/p>\n [\/et_pb_slide][et_pb_slide heading=”Published: natural language processing for lower back pain” button_text=”Read the paper” button_link=”https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1076633221004189?via%3Dihub” url_new_window=”on” _builder_version=”4.9.0″ _module_preset=”default” sticky_transition=”on”]<\/p>\n Our paper titled “A comparison of natural language processing methods for the classification of lumbar spine imaging findings related to lower back pain” was just published in\u00a0Academic Radiology<\/em>.<\/p>\n [\/et_pb_slide][\/et_pb_slider][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" We develop, adapt and apply machine learning methods to relate genetic variation to molecular function and disease using secondary biomedical data setsWhat We DoWe integrate functional annotations and predictions to infer the impact of genetic variants individually and jointly over a genome on molecular and organismal phenotypesWe extract and model information from electronic health records […]<\/p>\n","protected":false},"author":503,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-2","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/pages\/2","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/users\/503"}],"replies":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/comments?post=2"}],"version-history":[{"count":54,"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/pages\/2\/revisions"}],"predecessor-version":[{"id":295,"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/pages\/2\/revisions\/295"}],"wp:attachment":[{"href":"https:\/\/labs.icahn.mssm.edu\/pejaverlab\/wp-json\/wp\/v2\/media?parent=2"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}What We Do<\/h2>\n
News and Highlights<\/h2>\n