Chemogenomic-DTI-Prediction-Methods

About this repository

This repository has been initially established to hold the source code used for conducting the experiments explained in the following paper:

Computational Prediction of Drug-Target Interactions using Chemogenomic Approaches: An Empirical Survey [2018]
Briefings in Bioinformatics
Ali Ezzat, Min Wu, Xiao-Li Li, Chee-Keong Kwoh

This repository consists of two folders:

"1. Main": contains the source code that was used to generate the cross validation results displayed in the main text. The prediction methods that were compared in the main text belong to the category of similarity-based methods.
"2. Feature-based Methods": contains the source code that was used to generate the results displayed in the supplementary text accompanying the publication. The prediction methods involved belong to the category of feature-based methods.

The source code is entirely written in the MATLAB programming language. In the future, it is our intention to regularly add source codes for more DTI prediction algorithms, especially those that were not released in their respective papers. Stay tuned!

Alternative Online Source Codes for DTI Prediction Algorithms

The list below consists of other links containing source codes that have been made available online along with their corresponding publications (sorted in chronological order):

Algorithm	Source Code	Publication
Jacob et al.	Source Code
SVM-based BLM	Source Code	Publication
RLS-avg & RLS-kron	Source Code	Publication
KBMF2K	Source Code	Publication
DT-Hybrid	Source Code	Publication
RLS-WNN	Source Code	Publication
MHL1SVM	Source Code	Publication
Nanni et al.	Source Code	Publication
semEP	Source Code	Publication
PSL	Source Code	Publication
PUCPI	Source Code	Publication
GIFT	Source Code	Publication
KronRLS-MKL	Source Code	Publication
Coelho et al.	Source Code	Publication
RLS-KF	Source Code	Publication
NRLMF	Source Code	Publication
DTINet	Source Code	Publication
DeepWalk	Source Code	Publication
DeepDTIs	Source Code	Publication
DNILMF	Source Code	Publication
GRMF	Source Code	Publication

Web Servers

Following is a list of online DTI prediction servers:

Databases

Below is a list of databases that have previously been used in efforts pertaining to drug-target interaction prediction and, more generally, drug discovery. This list was compiled with the help of this paper.

For more data sources that are used in drug discovery in general (and not just DTI prediction), please refer to Table 2 of the following paper:

Toward better drug repositioning: prioritizing and integrating existing methods into efficient pipelines [2014]
Drug Discovery Today
Guangxu Jin, Stephen T.C. Wong

Datasets

Listed below are datasets that have been compiled by other researchers and used in DTI prediction efforts.

Dataset	Link	Publication
Yamanishi et al., 2008	Download Link	Publication
Yamanishi et al., 2010	Download Link	Publication
Tabei et al., 2012	Download Link	Publication
Tabei et al., 2013	Download Link	Publication
Xiao et al., 2013a	Download Link	Publication
Xiao et al., 2013b	Download Link	Publication
Min et al., 2013	Download Link	Publication
Fan et al., 2014	Download Link	Publication
Nanni et al., 2014	Download Link	Publication
Ezzat et al., 2016	Download Link	Publication
Cheng et al., 2016	Download Link	Publication
Nascimento et al., 2016	Download Link	Publication
Coelho et al., 2016	Download Link	Publication
Li at al., 2016	Download Link	Publication
Zong et al., 2017	Download Link	Publication
Wen at al., 2017	Download Link	Publication

Surveys

Following are a list of surveys on DTI prediction that have been published over the years. Note that some of these surveys contain alternative source codes for the DTI prediction algorithms being surveyed.

Similarity-based machine learning methods for predicting drug-target interactions - a brief review [2013]
Briefings in Bioinformatics
Hao Ding, Ichigaku Takigawa, Hiroshi Mamitsuka, Shanfeng Zhu

Toward more realistic drug–target interaction predictions [2014]
Briefings in Bioinformatics
Tapio Pahikkala, Antti Airola, Sami Pietilä, Sushil Shakyawar, Agnieszka Szwajda, Jing Tang, Tero Aittokallio

Drug-target interaction prediction via chemogenomic space - learning-based methods [2014]
Expert Opinion on Drug Metabolism & Toxicology
Zaynab Mousavian, Ali Masoudi-Nejad

Drug–target interaction prediction: databases, web servers and computational models [2016]
Briefings in Bioinformatics
Xing Chen, Chenggang Clarence Yan, Xiaotian Zhang, Xu Zhang, Feng Dai, Jian Yin, Yongdong Zhang

Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review [2017]
The AAPS Journal, Springer
Tiejun Cheng, Ming Hao, Takako Takeda, Stephen H. Bryant, Yanli Wang

Open-source chemogenomic data-driven algorithms for predicting drug–target interactions [2018]
Briefings in Bioinformatics
Ming Hao, Stephen H. Bryant, Yanli Wang