Abstract: Provided herein are methods and compositions for treating a subject having myasthenia gravis using T cells engineered with a chimeric antigen receptor that binds CD19. Also provided herein are methods and compositions for treating a subject having stiff person syndrome using T cells engineered with a chimeric antigen receptor that binds CD19.

Abstract: Disclosed herein are computer-implemented methods and systems for predicting transplant rejection. The methods and system may calculate a predicted probability of whether or an extent to which transplant rejection in a transplant recipient will occur may be calculated based on a score. The score may be calculated based on transplant recipient data and one or more parameter weights. The transplant recipient data may comprise transplant donor-derived cell-free DNA (dd-cfDNA) and one or more other types of parameters, such as one or more clinical parameters, one or more functional parameters, one or more immunological parameters, one or more transplant recipient characteristics, or one or more transplant characteristics. In some embodiments, the parameters used for calculating the predicted probability does not comprise a histological parameter.

Abstract: Disclosed herein are systems, kits, and methods for classifying the status of a transplant based on expression levels of a plurality of genes from a biological sample of a transplant recipient. The status of a transplant may be classified based on a predictive rejection classification including, but not limited to, antibody-mediated rejection (ABMR), T-cell mediated rejection (TCMR), mixed ABMR+TCMR, and no rejection. The predictive rejection classification may be assigned based on probability rejection scores, and a probability rejection score may be assigned to each rejection label. In some embodiments, the rejection label having the highest probability rejection score amongst the plurality of rejection labels may be assigned as the predictive rejection classification. Non-limiting rejection labels may include ABMR, TCMR, mixed ABMR+TCMR, and no rejection. The probability rejection score of each rejection label may be generated based on a plurality of sets of weights and expression levels of genes.

Abstract: The present invention relates to biomarkers associated with breast cancer prognosis. These biomarkers include coding transcripts and their expression products, as well as non-coding transcripts, and are useful for predicting the likelihood of breast cancer recurrence in a breast cancer patient. The present invention also relates to a novel method of identifying intergenic sequences that correlate with a clinical outcome.

Abstract: The present invention relates to biomarkers associated with breast cancer prognosis. These biomarkers include coding transcripts and their expression products, as well as non-coding transcripts, and are useful for predicting the likelihood of breast cancer recurrence in a breast cancer patient. The present invention also relates to a novel method of identifying intergenic sequences that correlate with a clinical outcome.

Abstract: The present invention relates to gene fusions and alternative spliced junctions associated with breast cancer. The present invention also relates to novel methods of identifying gene fusions and alternative spliced junctions in RNA sequencing data. The present invention further relates to predicting prognosis of a breast cancer patient based on the number of gene fusion events.

Abstract: The present invention relates to biomarkers associated with breast cancer prognosis. These biomarkers include coding transcripts and their expression products, as well as non-coding transcripts, and are useful for predicting the likelihood of breast cancer recurrence in a breast cancer patient, The present invention also relates to a novel method of identifying intergenic sequences that correlate with a clinical outcome.

Abstract: The present invention relates to gene fusions and alternative spliced junctions associated with breast cancer. The present invention also relates to novel methods of identifying gene fusions and alternative spliced junctions in RNA sequencing data. The present invention further relates to predicting prognosis of a breast cancer patient based on the number of gene fusion events.

Abstract: The present invention relates to biomarkers associated with breast cancer prognosis. These biomarkers include coding transcripts and their expression products, as well as non-coding transcripts, and are useful for predicting the likelihood of breast cancer recurrence in a breast cancer patient, The present invention also relates to a novel method of identifying intergenic sequences that correlate with a clinical outcome.

Abstract: The invention comprises for methods of identifying pharmacophores based on the spleen tyrosine kinase (SYK) protein or fragment thereof. The invention further provides methods of identifying SYK inhibitors using pharmacophores that are identified from co-crystals of SYK and its ligands. Further, the invention comprises methods of inhibiting SYK comprising contacting the residues lining the binding site with an inhibitor compound identified from pharmacophores.

Abstract: This invention provides an advanced platform for the analysis of biological data that emphasizes pathway mapping and relationship inference based upon data acquired from multiple diverse sources. The platform employs a bioinformatic system that integrates data from the diverse sources, connecting related genes and proteins and inferring biological functions in the context of global cellular processes.

Abstract: This invention provides an advanced platform for the analysis of biological data that emphasizes pathway mapping and relationship inference based upon data acquired from multiple diverse sources (102). The platform employs a bioinformatic system (100) that integrates data from the diverse sources (102), connecting related genes and proteins and inferring biological functions (108) in the context of global cellular processes.