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    線上研討會：COVID-19: Impacts and Insights from AI & Machine Learning Webinar - August 13

    2020-07-30 系統管理員

    Elsevier 於 8/13 (Thursday) 10:00AM – 11:40AM  舉辦 COVID-19: Impacts and Insights from AI & Machine Learning線上研討會，全程英語演講

     

    此次線上研討會邀請到二位美籍華裔科學家張元豪博士以及林清詠博士一同討論人工智慧及機器學習對於COVID-19的影響與帶來的洞見。

     

    • 張元豪博士目前為史丹佛大學教授也是美國國家院士與中研院院士，他最近發表在Cell期刊 的文章用一個新開發的方法檢驗RNA 在細胞的位置， 然後用AI 來預測SARS-CoV-2 RNA在細胞裡的位置和可能的功能。
    • 林清詠博士是Graphen Inc 的CEO 與創辦人，他所帶領的團隊利用人工智慧工具監控COVID-19病毒演化，在三月繪製全球首個AI「COVID-19基因演化路徑分析」，目前已完成全球超過12,294病毒株基因序列，把比對全球新冠病毒分成八大類 ，感染越多、時間越長變異越高。
    • 最後演講者是 Elsevier Pure 區域解決方案銷售經理 Adam Goh ，他為我們介紹 Elsevier COVID-19 專家人才平台，如何協助研究人員尋找研究合作者，並且能夠找出與聯絡全球進行 COVID-19 各方面相關的研究。

     

    https://www.elsevier.com/zh-tw/events/past-events/COVID-19-Impacts-and-Insights-from-AI-and-Machine-Learning

     

    Agenda

    Time Topic
    10:00AM
    -
    10:40AM

    RNA address codes for human and viral genomes

    Howard Chang , MD, PhD
    Virginia and D. K. Ludwig Professor of Cancer Genomics and of Genetics
    Stanford University

    In biology as in real estate, location is a cardinal organizational principle that dictates the accessibility and flow of informational traffic. An essential question in cell biology is the nature of the address code--how objects are placed and later searched for and retrieved. RNAs have emerged as key components of the address code, allowing protein complexes, genes, and chromosomes to be trafficked to appropriate locations and subject to proper activation and deactivation. I will discuss the development of APEX-seq, a method that quantifies RNA subcellular residency on a genome-wide scale. Genome-scale RNA localization data then propelled the development of computational models that can predict the RNA localization of human and viral transcripts, such as for SARS-CoV-2 viral RNAs.
    10:40AM
    -
    11:20AM

    Mapping COVID-19 Virus Mutations through Artificial Intelligence

    Dr. Ching-Yung Lin
    Founder & CEO of Graphen Inc. and Adjunct Professor in Columbia University

    Graphen, Inc., a startup building graphed based AI solutions, launched its AI gene evolution pathway analysis of the virus that causes the Coronavirus, COVID-19 on March 11, 2020. The team led by Dr. Ching-Yung Lin, AI big data analysis expert and Graphen founder in the United States, took only one week to map out the COVID-19 virus genes that have appeared so far. As of June 18, 2020, 22,402 different strains have been found from worldwide COVID-19 viruses distributed into eight categories.  In this session, Dr. Lin will discuss how viruses evolve and propagate over time. Mapping mutations and propagation patterns can help companies better identify targets for drug development, public health predictions on virus spreading speed, or predict the harmfulness of specific variants that may cause symptoms beyond those observed from the original strain.
    11:20AM
    -
    11:40AM       

    Supporting Research Collaboration during COVID-19

     

    Elsevier is committed to help researchers and life science companies accelerate efforts to address the COVID-19 global health crisis. We are pleased to offer the new Elsevier Coronavirus Research Hub, which currently includes a biomedical database, scientific and clinical content, COVID-19 specific datasets, a biomedically-focused text mining solution and several research collaboration tools.

    For this session, we would like to share in more detail how we support the research community via the COVID-19 Research Collaboration Portal and finding datasets on Mendeley Data.

     

    Adam Jia Kang Goh
    Regional Solution Sales Manager, Pure
    Elsevier