Titlebook: Bioinformatics and Drug Discovery; Richard S. Larson,Tudor I. Oprea Book 2019Latest edition Springer Science+Business Media, LLC, part of

Dedication

graphy

,Theorie der r?umlichen Kerbwirkung,. Similar to data set preprocessing in other fields, there is an initial need to complete data quality evaluation; however, with large heterogeneous clinical data sets, it is important to standardize the data in order to facilitate dimensionality reduction. This is particularly important for clinica

Concerto

https://doi.org/10.1007/978-3-642-53069-2ges in gene expression and signal transduction. L1000 big datasets provide gene expression profiles induced by over 10,000 compounds, shRNAs, and kinase inhibitors using L1000 platform. We developed a systematic compound signature discovery pipeline named csNMF, which covers from raw L1000 data proc

lacrimal-gland

High-Throughput Screening for Drug Combinationsed drugs using a full dose-response matrix scheme using viability as the readout. We provide details of the automation required to run the screen and the informatics required to process data from screening robot and subsequent analysis and visualization of the datasets.

Parley

Post-processing of Large Bioactivity Datathe processing of large bioactivity data and methods for handling these issues in a post-processing scenario. Specifically described are observations from a recent effort (Harris, ., 2017) to post-process massive amounts of bioactivity data from the NIH’s PubChem Bioassay repository (Wang et al., Nucleic Acids Res 42:1075–1082, 2014).

Explosive

Isomeric and Conformational Analysis of Small Drug and Drug-Like Molecules by Ion Mobility-Mass Specs are highlighted and placed in the context of both a separation and characterization perspective. We conclude this chapter with a guided reference protocol for obtaining routine IM-MS spectra on a commercially available uniform-field IM-MS.

Integrate

SOBER

Drug Signature Detection Based on L1000 Genomic and Proteomic Big Dataessing to drug screening and mechanism generation. The discovered compound signatures of breast cancer were consistent with the LINCS KINOMEscan data and were clinically relevant. In this way, the potential mechanisms of compounds’ efficacy are elucidated by our computational model.

角斗士

Coordinate

Die Formzahldiagramme und ihre Handhabung,zed by computationally ranking the closeness between a disease network and a drug’s signaling network. Furthermore, we describe the use of the most perturbed HLA genes to assess the safety risk for immune-mediated adverse reactions such as Stevens-Johnson syndrome/toxic epidermal necrolysis.