Abstract: The present invention relates to a process for identifying and/or isolating T cells which are capable of binding to a tumour in a mammalian subject having the tumour. Such T cells are of use in cancer immunotherapy. The invention also relates to a method of identifying a peptide neo-antigen for use in cancer immunotherapy in a mammalian subject having a tumour.

Abstract: Technologies relating to improving performance of a computer-implemented model that acts as a multi-class classifier are described herein. A chatbot includes the computer-implemented model, and the computer-implemented model receives natural language input from end users. A subset of the natural language inputs are identified as training examples that are to be used to update the computer-implemented model, wherein the natural language inputs are identified as the training examples based upon comparisons between scores for the natural language inputs output by different classifiers of the computer-implemented model. The training examples are labeled by a developer, and the computer-implemented model is updated based upon the labeled training examples.

Abstract: The present invention relates to a method of whole genome sequencing of a single cell or cell-group for identification of single nucleotide variants, determining chromosome structural variations, or determining phasing information in the genome of the single cell or cell-group. Methods of preparing an indexed DNA library for sequencing of nucleic acid molecules; preparing an indexed DNA library for whole genome sequencing of single cells or cell-groups for the identification of single nucleotide variants, determining chromosome structural variations, or determining phasing information in the genome of the single cells or cell-groups; and whole genome sequencing of a single cell or cell-group to provide data for the identification of single nucleotide variants (SNVs), determining chromosome structural variations, or determining phasing information in the genome of the single cell or cell-group are also described.

Abstract: The present invention relates to a method of determining the status of high-grade serous ovarian carcinoma (HGSOC) in a subject, the method comprising: providing a sample obtained from the subject; and detecting the presence of HGSOC biomarkers in the sample, wherein the method comprises detecting the presence of: a differentiated cell type; a KRT17 Cluster cell type; an epithelial-mesenchymal transition (EMT) cell type; a cell cycle cell type; and a ciliated cell type; wherein the level of the biomarkers is used to determine the fraction of EMT cells in the high-grade serous ovarian carcinoma in the subject. The invention further relates to associated kits, use and methods of treatment.

Abstract: Technologies relating to improving performance of a computer-implemented model that acts as a multi-class classifier are described herein. A chatbot includes the computer-implemented model, and the computer-implemented model receives natural language input from end users. A subset of the natural language inputs are identified as training examples that are to be used to update the computer-implemented model, wherein the natural language inputs are identified as the training examples based upon comparisons between scores for the natural language inputs output by different classifiers of the computer-implemented model. The training examples are labeled by a developer, and the computer-implemented model is updated based upon the labeled training examples.