{"id":2845,"date":"2019-02-19T15:00:45","date_gmt":"2019-02-19T20:00:45","guid":{"rendered":"https:\/\/www.med.unc.edu\/flowcytometry\/?post_type=tribe_events&p=2845"},"modified":"2019-02-19T15:00:45","modified_gmt":"2019-02-19T20:00:45","slug":"lunch-n-learn-the-antibody-crisis-leveraging-machine-learning-for-evidence-based-antibody-search","status":"publish","type":"tribe_events","link":"https:\/\/www.med.unc.edu\/flowcytometry\/event\/lunch-n-learn-the-antibody-crisis-leveraging-machine-learning-for-evidence-based-antibody-search\/","title":{"rendered":"Lunch ‘N Learn: The Antibody Crisis: Leveraging machine learning for evidence-based antibody search"},"content":{"rendered":"

Join us for an engaging presentation on<\/p>\n

The Antibody Crisis: Leveraging machine learning for evidence-based antibody search<\/h3>\n

by Maurice Shen from BenchSci<\/p>\n

The\u201creproducibility crisis\u201d has generated much attention in the research community over the past years. While the issue is multifaceted at its core, rogue antibodies have been identified as one of the major culprits.<\/p>\n

To ensure scientists can find antibodies that have been proven to work repeatedly by peers, we developed an open-access resource that uses a machine learning algorithm to screen the literature and identify which and how antibodies have been cited. The resulting peer-reviewed data are searchable by protein targets or product identifier, and are filterable by experimental contexts as cited in papers, including technique, tissue, cell line, to help users pinpoint antibodies that have been published under experimental conditions matching their study interest.<\/p>\n

Freely accessible resource for UNC and affiliated scientists at\u00a0https:\/\/landing.benchsci.com\/academic<\/a><\/p>\n

Location: Bondurant Hall, Room G030<\/p>\n

Please RVSP for this Lunch N’ Learn<\/strong> event so we can prepare enough food for everyone!\u00a0RVSP link:\u00a0https:\/\/www.addevent.com\/event\/ON3105846<\/a><\/p>\n

Sponsored by the SOM Office of Research Technologies<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Join us for an engaging presentation on The Antibody Crisis: Leveraging machine learning for evidence-based antibody search by Maurice Shen from BenchSci The\u201creproducibility crisis\u201d has generated much attention in the research community over the past years. 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