Titlebook: Computational Methods for Drug Repurposing; Quentin Vanhaelen Book 2019 Springer Science+Business Media, LLC, part of Springer Nature 2019

Charade

Reliability-Based Design Optimizationvel candidate therapeutics and drug repositioning candidates. To elucidate these, we will present two case studies: (1) using transcriptional signature similarity or positive correlation to identify novel small molecules that are similar to an approved drug and (2) identifying candidate therapeutics

知道

Analog Circuits in Weak Inversion, potential repositionings. Out of the 1141 drugs with relevant information on their interactions in DrugBank 4.1, we confirm the predicted properties for 85% of the drugs. The high prediction rate of our methodology suggests that, at least for some of the 15% drugs that seem to be inconsistent with

可忽略

Myosin

https://doi.org/10.1007/978-3-031-23898-7rces of biological information simultaneously. The Kronecker regularized least squares with multiple kernel learning (KronRLS-MKL) is a machine learning algorithm that aims at integrating heterogeneous information sources into a single chemogenomic space to predict new drug-target interactions. This

600

https://doi.org/10.1007/978-3-031-23898-7nent relationships among the millions of relationships suggested to the related researchers for further investigation. The main advantages of Heter-LP are the effective integration of input data, eliminating the need for negative samples, and the use of local and global features together. The main s

extemporaneous

https://doi.org/10.1007/978-3-031-23898-7arities. We used DeepWalk, a deep learning method, to calculate the vertex similarities based on Linked Tripartite Network (LTN), which is a heterogeneous network created from different biomedical-linked datasets. The similarities are further used to feed to the inference methods, drug-based similar