Method and system for reducing a footprint of a predictive computational model, in particular for predicting a structure of biological protein structures

A method of predicting a structure of a biological protein using a predictive computational model, the method comprising:

• loading the predictive computational model onto a computational hardware, which includes processing and storage units,
• applying the predictive computational model to output a first prediction, such as a first structure of biological protein,
• reducing a footprint of the predictive computational model by applying a method of reducing a footprint of a predictive computational model, comprising
• compressing the predictive computational model to come up with a compressed model, using a model compressor based on advanced network structures, wherein the predictive computational model comprises computational layers with data matrices,
• wherein the compression comprises
• identifying computational layers in the predictive computational model, reducing data matrices in the identified computational layers via mathematical operations, wherein the data matrices are truncated, to produce a compressed model,
• retraining the compressed model to adjust the compressed model and thereby produce an optimised predictive computational model that uses less storage,
• configuring the system designed to execute a method for predicting the structure of biological protein structures,
• inputting input data into the optimised predictive compressed model, wherein the input data represent a sequence of amino acids of the biological protein,
• running said optimised predictive compressed model and outputting a forecast of the structure of the biological protein, wherein the structure comprises a spatial arrangement of the target protein.