BIOLOGICAL STATUS DETERMINATION USING CELL-FREE NUCLEIC ACIDS

The techniques and systems described herein relate to using machine learning models to associate a known biological state of an organism with patterns of expression exhibited by the organism of genes of a gene signature associated with a disease state, such as to train the machine learning models to determine unknown biological states associated with the patterns of expression. Some techniques include determining an unknown biological status of an organism based on an expression pattern of genes of a gene signature in the organism, which the machine learning model may compare to known expression patients learned during the training technique. The expression patterns may be determined based on sequences of exosomal RNAs isolated from exosomes from a sample of bodily fluid from the organism and an approximate number of times each RNA sequence that substantially aligns with a gene of the gene signature occurs in the sample of bodily fluid.