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BioAssay: AID 588208

Literature-mined public compounds from Lowe et al phospholipidosis modelling dataset

Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably identified by electron microscopy of cells revealing the presence of lamellar inclusion bodies. The development of phospholipidosis can cause a delay in the drug development process, and the more ..
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 Tested Compounds
 Tested Compounds
All(183)
 
 
Unspecified(183)
 
 
 Tested Substances
 Tested Substances
All(192)
 
 
Unspecified(192)
 
 
AID: 588208
Data Source: ChEMBL (736762)
Depositor Category: Literature, Extracted
BioAssay Version:
Deposit Date: 2011-09-18
Modify Date: 2013-11-17

Data Table ( Complete ):           All
Tested Compounds:
Description:
Title: Predicting phospholipidosis using machine learning.

Abstract: Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably identified by electron microscopy of cells revealing the presence of lamellar inclusion bodies. The development of phospholipidosis can cause a delay in the drug development process, and the importance of computational approaches to the problem has been well documented. Previous work on predictive methods for phospholipidosis showed that state of the art machine learning methods produced the best results. Here we extend this work by looking at a larger data set mined from the literature. We find that circular fingerprints lead to better models than either E-Dragon descriptors or a combination of the two. We also observe very similar performance in general between Random Forest and Support Vector Machine models.
(PMID: 20799726)
Comment
Putative Target:

ChEMBL Target ID: 103779
Target Type: PHENOTYPE
Pref Name: Phospholipidosis
Confidence: Target assigned is non-molecular
Relationship Type: Non-molecular target assigned
Categorized Comment
ChEMBL Assay Type: ADMET

ChEMBL Assay Data Source: Scientific Literature

Result Definitions
TIDNameDescriptionHistogramTypeUnit
OutcomeThe BioAssay activity outcomeOutcome
1Phospholipidosis activity commentPhospholipidosis activity commentString
2Phospholipidosis standard flagPhospholipidosis standard flagInteger
3Phospholipidosis qualifierPhospholipidosis qualifierString
4Phospholipidosis published valuePhospholipidosis published valueFloat
5Phospholipidosis standard valuePhospholipidosis standard valueFloat

Data Table (Concise)
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