Multi-resolution modeling of discrete stochastic processes for computationally-efficient information search and retrieval

An information search and retrieval apparatus for use with an input dataset that is a non-stationary discrete stochastic process representing a pattern of mutations across a genome of a cancer of interest, wherein events of interest are cancer-specific mutations that occur within the process approximately independently at units i within a region R, and with an unknown rate λR that is approximately constant across R, wherein λR has an associated estimation uncertainty defined by a set of parameters that include expectation μR and variance σR2, and wherein the non-stationary discrete stochastic process comprising a plurality of regions, wherein at least one region is a non-coding region of the genome, comprising:

• a hardware processor;
• and
• computer memory holding computer program code executed by the hardware processor, the computer program code comprising:
• a neural network that uses the input dataset to one-time train a model for the cancer of interest to predict rate parameters and their associated estimation uncertainty for each region of the plurality of regions;
• and
• a query function that receives a query associated with any arbitrary set of indexed positions within the plurality of regions and, in response, scales existing predictions of the rate parameters and their associated estimation uncertainties from the trained model for any region of the plurality of regions to obtain a response to the query, the response being a distribution of the events of interest and their associated estimation uncertainties for the set of indexed positions;
• and
• an output function that applies data derived from the response to a target application.

A computer program product in a non-transitory computer readable medium for use in a data processing system, the computer program product holding computer program instructions which, when executed by the data processing system, are operative to perform information search and retrieval with respect to a non-stationary discrete stochastic process representing a pattern of mutations across a genome for a cancer of interest, wherein events of interest are cancer-specific mutations that occur within the process approximately independently at units i within a region R, and with an unknown rate λR that is approximately constant across R, wherein λR has an associated estimation uncertainty defined by a set of parameters that include expectation μR and variance σR2, and wherein the non-stationary discrete stochastic process comprises a plurality of regions, wherein at least one region is a non-coding region of the genome, the computer program instructions comprising program code configured to:

• train a model for the cancer of interest a single time to predict rate parameters and their associated estimation uncertainty for each region of the plurality of regions;
• receiving a set of one or more queries, wherein a query is associated with any arbitrary set of indexed positions within the plurality of regions;
• responsive to receipt of each query, scale existing predictions of the rate parameters and their associated estimation uncertainties from the trained model for any region of the plurality of regions to obtain a response to the query, the response being a distribution of the events of interest and their associated estimation uncertainties for the set of indexed positions;
• and
• provide the response for use in a target application.