Cheng Ruihua1, Hu Pengcheng2
1.Tianjin University of Finance and Economics, 2.Dingzheng xinxing Biotechnology (Tianjin) Co., Ltd.
Abstract：
Big data technology is profoundly transforming the research paradigm of life sciences. This study systematically explores the innovative paths in data collection, storage, and analysis in life sciences driven by big data. At the level of data collection and storage, standardized collection processes for multimodal data, optimized distributed storage architectures, and advancements in data cleaning techniques provide a high-quality data foundation for life science research. At the level of analytical techniques, innovative applications of machine learning algorithms in fields such as genomics and protein structure prediction have significantly enhanced research efficiency. Visualization analysis methods for complex biological networks and integration strategies for multi-omics data provide new perspectives for understanding the complexity of living systems. These technological innovations collectively drive the paradigm shift from hypothesis-driven to data-driven research in life sciences, bringing new development opportunities to fields such as precision medicine and new drug development. In the future, it is necessary to further strengthen interdisciplinary cooperation, establish unified data standards, and promote deep transformation of the research paradigm in life sciences.
Key Words：
life sciences; big data; research paradigm; multi-omics; machine learning
