Abstract: There is a need for more effective and efficient anomaly detection. This need can be addressed by, for example, solutions for performing/executing graph convolutional anomaly detection. In one example, a method includes identifying related graph database input data associated with a predictive entity; generating related graph feature data for the predictive entity; generating, based on the related graph feature data and using a graph convolutional neural network model, an anomaly detection score for the predictive entity, wherein at least a portion of the graph convolutional neural network model is trained using confirmation feedback data; performing an anomaly confirmation to generate the confirmation feedback data object for the predictive entity, and integrating the confirmation feedback data object for the predictive entity into the confirmation feedback data associated with the graph convolutional anomaly detection.

Abstract: Antibody molecules that specifically bind to C5aR1 are disclosed. The antibody molecules can be used to treat, prevent, and/or diagnose disorders, such as ANCA-vasculitis.

Abstract: Polypeptides, such as antibody molecules and TCR molecules, and methods of making the same, are disclosed. The polypeptides can be used to treat, prevent, and/or diagnose disorders.

Abstract: Antibody molecules that specifically bind to APRIL are disclosed. The antibody molecules can be used to treat, prevent, and/or diagnose disorders, such as IgA nephropathy.

Abstract: Antibody molecules that specifically bind to C5aR1 are disclosed. The antibody molecules can be used to treat, prevent, and/or diagnose disorders, such as ANCA-vasculitis.

Abstract: The present disclosure provides, among other things, two different formats of humanized antibodies against human complement component 5a receptor I. The disclosure also provides a method of treating a subject having dysfunctions of C5a/C5aR1 axis pathway, including but not limited to ANCA-associated vasculitis, comprising administering to the subject in need thereof a an effective amount of antibody or a nucleic encoding an antibodies binding to C5aR1 described herein, and wherein administering results in a decrease in symptoms associated with C5a/C5aR1 associated dysfunction in the subject.

Abstract: There is a need for more effective and efficient anomaly detection. This need can be addressed by, for example, solutions for performing/executing graph convolutional anomaly detection. In one example, a method includes identifying related graph database input data associated with a predictive entity; generating related graph feature data for the predictive entity; generating, based on the related graph feature data and using a graph convolutional neural network model, an anomaly detection score for the predictive entity, wherein at least a portion of the graph convolutional neural network model is trained using confirmation feedback data; performing an anomaly confirmation to generate the confirmation feedback data object for the predictive entity, and integrating the confirmation feedback data object for the predictive entity into the confirmation feedback data associated with the graph convolutional anomaly detection.

Abstract: There is a need for more effective and efficient anomaly detection. This need can be addressed by, for example, solutions for performing/executing graph convolutional anomaly detection. In one example, a method includes identifying related graph database input data associated with a predictive entity; generating related graph feature data for the predictive entity; generating, based on the related graph feature data and using a graph convolutional neural network model, an anomaly detection score for the predictive entity, wherein at least a portion of the graph convolutional neural network model is trained using confirmation feedback data; performing an anomaly confirmation to generate the confirmation feedback data object for the predictive entity, and integrating the confirmation feedback data object for the predictive entity into the confirmation feedback data associated with the graph convolutional anomaly detection.

Abstract: There is a need for more effective and efficient anomaly detection. This need can be addressed by, for example, solutions for performing/executing graph convolutional anomaly detection. In one example, a method includes identifying related graph database input data associated with a predictive entity; generating related graph feature data for the predictive entity; generating, based on the related graph feature data and using a graph convolutional neural network model, an anomaly detection score for the predictive entity, wherein at least a portion of the graph convolutional neural network model is trained using confirmation feedback data; performing an anomaly confirmation to generate the confirmation feedback data object for the predictive entity, and integrating the confirmation feedback data object for the predictive entity into the confirmation feedback data associated with the graph convolutional anomaly detection.