Optimize transfection efficiency measurement with AI
The strategic development of AI algorithms is important for precise transfection efficiency measurements. These algorithms may be either pre-trained with prior knowledge or custom trained for unique experimental conditions. Factors like cell morphology, fluorescence intensity, and background noise should be considered to gain insights on cellular dynamics.
AI versus manual evaluation
Cases which show AI effectiveness for transfection-efficiency measurements are discussed. Transfection efficiency was measured using the Mateo FL microscope. AI both elevates measurement precision and streamlines the workflow compared to manual estimations.
Impact on upstream workflows
Beyond optimizing transfection efficiency measurements, AI also helps streamline upstream workflows for the purification, isolation, and extraction of proteins, microscopy imaging, and flow cytometry. For example, AI algorithms can predict optimal conditions for protein purification based on data, reducing trial and error. Concerning imaging, AI enables automated analysis of images, resulting in faster extraction of meaningful information.
