Northeastern University MATH 7243 - Final Project

Replicating the Work - Genome‑wide investigation of gene‑cancer associations for the prediction of novel therapeutic targets in oncology - https://doi.org/10.1038/s41598-020-67846-1

Group Members: Tanishq Bhatia, Yuyang Cao, Jieying Jin, Jundong Wang, Paul Xi, Jiaming Xu

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Description of files

• There are 32 dimensional features generated by applying Diff2Vec on gene interactions data, obtained from BioGRID database.
  • Diff2Vec: https://github.com/benedekrozemberczki/diff2vec. Since the code is outdated, modifications were applied.
  • BioGRID: https://wiki.thebiogrid.org/doku.php/biogridrest
• There are 3 features related to genes - expression, mutation, and essentiality. Obtained from UCSC Xena portal and DepMap.
  • UCSC Xena: https://xena.ucsc.edu
  • DepMap: https://depmap.org
• The training set was directly aquired from the repository in the literature.
  • CancerTargetPrediction Github: https://github.com/storm-therapeutics/CancerTargetPrediction

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Machine Learning Models Used in Ths Work

• ANN (Tanishq Bhatia)
• SVM (Jieying Jin)
• KNN (Jiaming Xu)
• LDA/QDA (Jundong Wang)
• Logistic Regression (Xueqi Xue)
• Random Forest (Yuyang Cao)

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