Druggability |
The property of a druggable molecule (i.e., a biological target) by virtue of which it elicits a favorable clinical response when it contacts a drug-like compound |
Systems Biology |
Study of the complex biological systems using mathematical and computational modeling |
Machine Learning |
Subfield of computer science devoted to the development and utilization of algorithms that can learn from and make predictions on data |
Network Measures |
Numerical attributes used to describe the role and position of every node in a network |
Ensemble algorithms |
Collection of machine learning algorithms in which the final consensus prediction is made using results from each component algorithm |
Support Vector Machines (SVM) |
A model that takes the input training data and maps the data points in space and then tries to find a hyperplane that can be used to distinctly classify the data into their respective classes |
Decision Tree |
Machine learning algorithms based on decision support tools that make use of a graph of conditions and their possible consequences |
Random Forest |
Ensemble learning algorithm that combines results from multiple decision trees and output the consensus predictions |
Closeness Centrality |
Network measure that indicates how close each node is to every other node in the network |
Betweenness Centrality |
Fraction of shortest paths between all nodes passing through the given node |