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Bio-panning is a common process involved in recombinant antibody selection against defined targets. The biopanning process aims to isolate specific antibodies against an antigen via affinity selection from a phage display library. In general, antigens are immobilized on solid surfaces such as polystyrene plastic, magnetic beads, and nitrocellulose. For high-throughput selection, semi-automated panning selection allows simul-taneous panning against multiple target antigens adapting automated particle processing systems such as the KingFisher Flex. The system setup allows for minimal human intervention for pre-and post-panning steps such as antigen immobilization, phage rescue, and amplification. In addition, the platform is also adaptable to perform polyclonal and monoclonal ELISA for the evaluation process. This chapter will detail the protocols involved from the selection stage until the monoclonal ELISA evaluation with important notes attached at the end of this chapter for optimization and troubleshooting purposes.
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.