A method of in silico analysis of data sets derived from omics data of cells, comprising: informationally coupling a pathway model database to a machine learning system and a pathway analysis engine; wherein the pathway model database stores a plurality of omics data sets comprising omics data of a plurality of distinct diseased cells, respectively, and wherein each data set comprises a plurality of pathway element data; receiving, by the machine learning system, the plurality of data sets; identifying, by the machine learning system, a determinant pathway element in the plurality of data sets that is associated with a status of a treatment parameter of the diseased cells; the determinant pathway element being a treatment resistance associated or a treatment sensitivity associated pathway element data. receiving, by the pathway analysis engine, at least one of the data sets from the diseased cells; modulating in silico, by the pathway analysis engine, the determinant pathway element in the at least one data set to produce a modified data set from the diseased cell, wherein the modified data set includes at least one modified pathway element and the at least one modified pathway element is modified directly on a nucleic acid level or a protein level, or indirectly via a regulatory component; and further wherein modulating in silico comprises: - in silico representing the pathway model via a factor graph model comprising factor nodes and variable evidence nodes; the variable evidence nodes being populated using the derived omics data; - in silico forcing the variable evidence node representing the determinant pathway element of the pathway model in a suppressed state; and - in silico re-inferring the pathway activities for obtaining the modified data set; and identifying, by the machine learning system and using the modified data set, a change in the status of the treatment parameter for the diseased cell. informationally coupling a pathway model database to a machine learning system and a pathway analysis engine; wherein the pathway model database stores a plurality of omics data sets comprising omics data of a plurality of distinct diseased cells, respectively, and wherein each data set comprises a plurality of pathway element data; receiving, by the machine learning system, the plurality of data sets; identifying, by the machine learning system, a determinant pathway element in the plurality of data sets that is associated with a status of a treatment parameter of the diseased cells; the determinant pathway element being a treatment resistance associated or a treatment sensitivity associated pathway element data. receiving, by the pathway analysis engine, at least one of the data sets from the diseased cells; modulating in silico, by the pathway analysis engine, the determinant pathway element in the at least one data set to produce a modified data set from the diseased cell, wherein the modified data set includes at least one modified pathway element and the at least one modified pathway element is modified directly on a nucleic acid level or a protein level, or indirectly via a regulatory component; and further wherein modulating in silico comprises: - in silico representing the pathway model via a factor graph model comprising factor nodes and variable evidence nodes; the variable evidence nodes being populated using the derived omics data; - in silico forcing the variable evidence node representing the determinant pathway element of the pathway model in a suppressed state; and - in silico re-inferring the pathway activities for obtaining the modified data set; and - in silico representing the pathway model via a factor graph model comprising factor nodes and variable evidence nodes; the variable evidence nodes being populated using the derived omics data; - in silico forcing the variable evidence node representing the determinant pathway element of the pathway model in a suppressed state; and - in silico re-inferring the pathway activities for obtaining the modified data set; and identifying, by the machine learning system and using the modified data set, a change in the status of the treatment parameter for the diseased cell.