This is a brief Python implementation of lncRNA-disease association prediction model SVDNVLDA.

The whole object was implected on Python 3.6, and versions of some import packages are:

packageName	version
networkx	2.5.1
numpy	1.19.5
pandas	0.20.3
scikit-learn	0.24.2
scipy	1.5.4
xgboost	1.3.3

and node2vec package was downloaded from https://github.com/eliorc/node2vec

There are five directories in this project：

​ Data Folder : Contains all data used in our experiment.

​ eg: LncDis.csv :Contains all lncRNA-disease association records;

​ AllAsso.csv:Contains all association records used in our experiment

​ SVD Folder: The implementation of SVD on lncRNA-disease association matrix

​ GetMat.py: transform the association records into association matrix

​ SVDImp.py: implete SVD on the matrix and save the linear features of lncRNAs and diseases

​ N2V Folder: The implementation of node2vec on LMDN

​ node2vec_flight.py: implete node2vec on LMDN

​ vecGet.py: fit the original node2vec result to classifiers

​ Sampling Folder: Create the negative samles and conduct the randomly sample

​ Classifier Folder: implete the ultimate classification exhibit the 10-fold cross validation results