In a groundbreaking announcement at the recently concluded 2024 China Life Sciences Conference, Qingdao Single-Cell Biotech. Co., Ltd. (referred to as "SCB") officially launched a pioneering cloud-based platform—RamanAI (www.ramanai.net). This innovative one-stop intelligent cloud expert system for Raman spectroscopy data analysis is set to provide researchers with a simple, zero-experience, and highly visual Raman data analysis experience. Equipped with an advanced AI expert system, RamanAI allows users to design experiments, build models, and complete data analysis through interactive chats. Additionally, models established on the cloud can be seamlessly integrated with SCB’s range of single-cell analysis and sorting instruments, facilitating Raman-activated cell sorting.

RamanAI Launch Event Draws Widespread Attention

The launch event sparked significant interest and discussion within the scientific community. Researchers expressed enthusiasm for this new tool, which promises to simplify complex data analysis and unleash researchers' creative potential. Dr. Bo Ma, Chairman of SCB and a researcher at the Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, emphasized, "RamanAI is our response to the needs of the scientific community and a key product driving technological advancement. By simplifying complex data analysis with high-tech solutions, we aim to accelerate scientific research, enhance experimental precision, and propel the industry forward."

The Significance of Ramanome: A Label-Free, Non-Invasive Single-Cell Metabolic Phenotyping Technology

Raman spectroscopy technology can identify and quantify various biomolecules within cells, such as proteins, nucleic acids, lipids, and carbohydrates. Ramanomics, a collection of single-cell Raman spectra from a cell population under specific conditions, is a label-free, non-invasive, and cost-effective method for high spatiotemporal resolution metabolic phenotyping.

Dr. Jian Xu, Director of the Single-Cell Center at the Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, highlighted that Ramanomics quantitatively translates molecular spectra of intracellular metabolites into real-time information on substrate metabolism, product synthesis, stress resistance, environmental stress responses, compound transformation networks, intercellular metabolic interactions, and cell types. In collaboration with SCB, the Single-Cell Center developed and commercialized the industry's first Flow-mode Raman-activated Cell Sorter, FlowRACS. This product, currently the only Raman-activated flow cytometer on the market globally, makes high-throughput, large-scale collection of Ramanomics data possible for the first time.

Unveiling the Depths of Ramanome

As Ramanome enters the "big data era," RamanAI emerges as the solution. Focused on this new data type, RamanAI aims to provide a one-stop cloud analysis tool for label-free, non-invasive single-cell metabolic phenotyping, driving the expansion of Raman spectroscopy applications and the construction of big data systems.

Data Is Easy, Interpretation Is Hard

With the introduction of high-throughput Raman-activated flow sorting equipment like FlowRACS, acquiring large-scale Ramanome data has become increasingly easy. However, extracting valuable information from these complex data sets remains a significant challenge.

Yongshun Wang, an engineer at SCB, explained, "RamanAI features 'Smart Analysis' and 'Smart Modeling' modules, integrating machine learning algorithms with high scenario matching, cutting-edge deep learning algorithms, various in-house algorithms, and the much-discussed large model technology. It supports highly automated spectral analysis modeling, image, and multimodal analysis processes. Depending on user-specific needs, RamanAI can generate a wide range of journal-quality visualizations."

Four Key Modules of RamanAI: AI-Powered Cloud Expertise

Can Raman spectroscopy technology be easily utilized for experiments even without knowledge of physical chemistry or data analysis experience?

"Absolutely," said Dr. Yin Yifeng, Chief Scientist at SCB. "The 'Smart Expert' module within RamanAI provides intelligent guidance throughout the data analysis process 24/7. Additionally, it features an intelligent Q&A window that can answer all your experimental design and data analysis questions!"

At the launch event, Dr. Yin also showcased several application cases using RamanAI, such as label-free, unsupervised clustering of mammalian cells, identification of probiotic species, screening of high-lycopene-producing strains, and recognition of highly tolerant cells. He emphasized that these applications demonstrate RamanAI's wide applicability and efficiency in real-world scientific research.

Synchronizing Analysis and Sorting to Enhance Instrument Performance

RamanAI has already achieved seamless integration with SCB's FlowRACS and the Raman-activated Optical Tweezers-based Cell Sorter (RACS-Seq). On the one hand, users can directly upload data from the instrument without complex data conversion and format adjustments. On the other hand, models downloaded from RamanAI can be easily imported into FlowRACS or RACS-Seq to assist subsequent single-cell sorting work.

This "synchronized analysis and sorting" approach not only improves data processing efficiency but also provides robust support for instrument performance.

Breaking Down Ramanome Data Silos and Boosting Terminal Computing Power

RamanAI is more than just a data analysis platform. It also features ultra-high cloud computing power, allowing users to conduct data analysis anytime, anywhere, without hardware limitations. The platform's centralized data management system supports up to 20GB of storage space per user group, significantly simplifying data management processes and facilitating data access and sharing.

The Core Advantages of RamanAI

Pengfei Zhu, Director of Biotechnology at SCB, explained, "Qualitatively and quantitatively measuring the metabolic phenotype of single cells using Raman spectroscopy depends on a series of 'models' that link spectral features with specific metabolic phenotypes. RamanAI is a one-stop database for these 'Raman metabolic models.' Moreover, RamanAI includes a 'Smart Marketplace' that allows users to share, trade, and apply models. We aim to build a research community where users can not only trade and apply models but also share data, promoting research collaboration and technological advancement."

In the future, SCB plans to continuously optimize and expand RamanAI's functionalities, incorporating more in-house algorithms to provide researchers with more powerful and efficient Raman data analysis tools. Additionally, SCB intends to integrate RamanAI with more types of research equipment to support broader research applications and commercial collaborations.

RamanAI, with its "one-click cloud" function, enables instant data uploading, cloud processing, and analysis, and model sharing, greatly saving researchers' time and effort. Xuanzhe Hong, General Manager of SCB, stated, "Our goal is to allow researchers to focus more on the essence of scientific exploration rather than being bogged down by tedious data processing tasks."

As big data and AI continue to evolve, society is entering a deeply intelligent era where cognition is reshaped by data and algorithms. Cloud platforms like RamanAI are becoming indispensable components of scientific research.

With the continuous advancement and refinement of RamanAI technology, we can foresee a new development phase for the "Ramanome Platform." From the large-scale collection of Ramanome data enabled by FlowRACS to the analysis and sorting of Ramanome data supported by RamanAI, and the applications built on "Ramanome Large Models," this complete innovation chain will inject continuous energy into single-cell multiomics research and industries. It will accelerate the development of new productive forces in precision medicine, synthetic biology, bioresource exploration, and utilization.