Patent ID: 11935627
Assignee: MUJIN, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 11:
12. A non-transitory medium with instructions stored thereon that, when executed by a processor of a computing device, cause the computing device to perform operations comprising: generating text phrases that represent different DNA sequences, wherein the text phrases include—
expected phrases corresponding to multiple locations in an overall genome, wherein phrases corresponding to each location include different combinations of flanking texts adjacent to a text segment that represents a tandem repeat (TR) sequence associated with the corresponding location, and derived phrases representative of sampled mutations in the TR sequence, and wherein generating the text phrases includes refining an initial set of segments and/or phrases based on removing overlaps and/or duplicates therein to generate the text phrases; and developing a machine learning (ML) model based on using a subset of the text phrases as features, wherein the ML model is trained and configured to compute a cancer signature based on analyzing text-based patient DNA data according to representations therein of mutations in patient DNA, the cancer signature representing (1) a likelihood that a corresponding patient has developed one or more types of cancer, (2) a likelihood that the patient will develop the one or more types of cancer within a given duration, (3) a development status at least leading up to onset of the one or more types of cancer, (4) monitoring a progression or a treatment response of the one or more types of cancer, or a combination thereof, wherein developing the ML model includes:
receiving a DNA sample set that includes text strings representative of DNA data associated with (1) patients confirmed to have one or more types of cancer and (2) patients confirmed to be without cancer;
calculating a wild type count based on analyzing the DNA sample set, wherein the wild type count represents a number of occurrences of one or more genes found in natural non-mutated form within the DNA sample set;
calculating a variant count based on analyzing the DNA sample set, wherein the variant count represents a number of occurrences of a target derived phrase within the DNA sample set;
calculating a variant count measure for the target derived phrase based on the wild type count and the variant count; and
classifying a target mutation represented by the target derived phrase as non-somatic when the variant count measure is less than a minimum threshold.