Systems and methods for genetic imputation, feature extraction, and dimensionality reduction in genomic sequences

A system for dynamically producing predictive data using varying data, wherein the system is structured to generate imputed genomic sequence by inputting actual genomic sequence into an artificial neural network, the system comprising:

• a. an artificial neural network;
• b. a communication device;
• c. a processing device communicably coupled to the communication device, wherein the processing device is configured to:
• (i) receive actual genetic information;
• (ii) generate an input vector, wherein the input vector comprises probabilistic or binary data converted from allelic data;
• (iii) access the neural network comprising a dynamic reservoir containing units, wherein each of the units is connected to at least one other unit in the dynamic reservoir and the connections between the units are weighted;
• (iv) input the input vector into the neural network in order to generate an imputed sequence;
• (vi) generate, via the neural network, an imputed sequence, wherein the imputed sequence is an output of the neural network and at least partially based on the input vector;
• (vii) modify the initial prediction to generate a final prediction;
• (viii) present the final prediction to a user;
• and
• (ix) export the final prediction to a computer system.