Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combination of factors that might be affecting the pathway under certain conditions. Currently, a major persisting problem is to cherry pick the combinations based on expert advice, literature survey or guesses for investigation. This entails investment in time, energy and expenses at various levels of research. To address these issues, a search engine design was recently published, which showed promise by revealing existing confirmatory published wet lab results. Additionally and of import, an adaptation of the published engine mined up a range of unexplored/untested/unknown combinations of genetic factors in the cell signaling pathways that were affected by ETC-1922159 enantiomer, a PORCN-WNT inhibitor, after the colorectal cancer cells were treated with the inhibitor drug. Here, the R code of the search engine is explained/provided that will help biologists/oncologists to understand how gene combinations can be ranked. Using this engine they will be able to find combinations which they might want to test in wet lab. Further, they will not have to struggle to search for unknown/unexplored combinations of genes/protiens working in a phenomena. Used packages - SVM Rank by Thorsten Joachims at - https://www.cs.cornell.edu/people/tj/svm_light/svm_rank.html Sensitivity Pacakge in R at - https://cran.r-project.org/web/packages/sensitivity/index.html Note - for ease, i have included these packages so that the search engine pipeline can be run. Please cite the above packages also for publication. How to run the code - The link in the section "identifiers" below, shows the sequence in which the files need to be executed in R.