Artificial intelligence for life sciences: A comprehensive guide and future trends
Ming Luo, Wenyu Yang, Long Bai, Lin Zhang, Jiawei Huang, Yin-Hong Cao, Yuhua Xie, Liping Tong, Haibo Zhang, Yu Lei, Li‐Wei Zhou, Yi Shi, Peng Yu, Zuoyun Wang, Zuoqiang Yuan, Peijun Zhang, Youjun Zhang, Feng Ju, Bin Zhang, Fang Wang, Yuanzheng Cui, Jin Zhang, Gongxue Jia, Dan Wan, Changshun Ruan, Zhuowei Yu, Pengpeng Wu, Zhaobing Gao, Wenrui Zhao, Yongjun Xu, Guangchuang Yu, Caihuan Tian, Ling Jin, Jiyan Dai, Bingqing Xia, Baojun Sun, Fei Chen, Yi‐Zhou Gao, Haijun Wang, Bing Wang, Dake Zhang, Xin Cao, Huai‐Yu Wang, Tao Huang
Abstract
<p>Artificial intelligence has had a profound impact on life sciences. This review discusses the application, challenges, and future development directions of artificial intelligence in various branches of life sciences, including zoology, plant science, microbiology, biochemistry, molecular biology, cell biology, developmental biology, genetics, neuroscience, psychology, pharmacology, clinical medicine, biomaterials, ecology, and environmental science. It elaborates on the important roles of artificial intelligence in aspects such as behavior monitoring, population dynamic prediction, microorganism identification, and disease detection. At the same time, it points out the challenges faced by artificial intelligence in the application of life sciences, such as data quality, black-box problems, and ethical concerns. The future directions are prospected from technological innovation and interdisciplinary cooperation. The integration of Bio-Technologies (BT) and Information-Technologies (IT) will transform the biomedical research into AI for Science and Science for AI paradigm.</p>