DataVXAdvanced MaterialsPaper
journal article·2023-05Open access

Assessing Biomaterial‐Induced Stem Cell Lineage Fate by Machine Learning‐Based Artificial Intelligence (Adv. Mater. 19/2023)

Yingying Zhou, Xianfeng Ping, Yusi Guo, Boon Chin Heng, Yijun Wang, Yanze Meng, Shengjie Jiang, Yan Wei, Binbin Lai, Xuehui Zhang, Xuliang Deng

Advanced Materials· Volume 35· Issue 19
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Source abstract

Abstract

Stem Cell Lineage Fate Highly accurate, efficient, and convenient evaluation for biomaterial-induced stem cell lineage fate is pivotal for regenerative biomaterials research. In article number 2210637, Binbin Lai, Xuehui Zhang, Xuliang Deng, and co-workers report MeD-P, a machine-learning-supported intelligent evaluation model, for predicting human mesenchymal stem cell–biomaterial interaction based on RNA-seq data. This framework shows the potential of artificial intelligence in facilitating biological performance optimization of biomaterials in stem cell lineage fate regulation.
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Research context

Biomaterials

OpenAlex topics: E-commerce and Technology Innovations

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Affiliations

Department of Dental Materials and Dental Medical Devices Testing Center Peking University School and Hospital of Stomatology Beijing 100081 P. R. China

National Engineering Research Center of Oral Biomaterials and Digital Medical Devices NMPA Key Laboratory for Dental Materials Beijing Laboratory of Biomedical Materials Peking University School and Hospital of Stomatology Beijing 100081 P. R. China

Central Laboratory Peking University School and Hospital of Stomatology Beijing 100081 P. R. China

Department of Geriatric Dentistry Peking University School and Hospital of Stomatology Beijing 100081 P. R. China

Biomedical Engineering Department Peking University Beijing 100191 P. R. China

Department of Dermatology and Venereology Peking University First Hospital Beijing 100034 P. R. China

References

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