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Update the dataset summary

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  1. README.md +19 -13
README.md CHANGED
@@ -8,17 +8,20 @@ tags:
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  pretty_name: AggregatorAdvisor
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  size_categories:
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  - 10K<n<100K
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- dataset_summary: >-
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- AggregatorAdvisor identifies molecules that are known to aggregate or may
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- aggregate in biochemical assays based on the chemical similarity to known
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- aggregators, and physical properties. In the default affinity range of 100 nM
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- to 10 μM, if calculated LogP > 3 and Tc ≥ 85%, the user is informed that this
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- compound should be investigated as an aggregator. If either calculated LogP >
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- 3 or Tc > 85%, the user is warned that one of these two contributing criteria
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- are in effect and that controls should be run. If neither of these is true,
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- this is reported, and the user is counseled that controls are always advised.
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- The train and test datasets were created after sanitizing and splitting the
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- original dataset in the paper below.
 
 
 
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  citation: |-
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  @article
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  {Irwin2015, title = {An Aggregation Advisor for Ligand Discovery},
@@ -66,8 +69,11 @@ dataset_info:
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  ---
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  # Aggregator Advisor
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- The [Aggregator Advisor](https://advisor.docking.org/) is a web-tool hosted by the Shoichet Lab at UCSF and used to assess the risk of a compound being an aggregetor.
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- The most current release (2022/06) contains 12645 compounds from 20 sources.
 
 
 
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  The train and test datasets uploaded to our Hugging Face repository have been sanitized and split from the original dataset
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  If you want to try these processes with the original dataset, please follow the instructions in the [Processing Script.py](https://huggingface.co/datasets/maomlab/AggregatorAdvisor/blob/main/Preprocessing%20Script.py) file located in the AggregatorAdvisor.
 
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  pretty_name: AggregatorAdvisor
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  size_categories:
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  - 10K<n<100K
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+ dataset_summary:
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+ 12645 compounds from 20 sources from the AggregatorAdvisor release-2022/06
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+ (https://advisor.docking.org/) that are experimentally determined to aggregate
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+ thereby potentially causing false-positive outcomes in high-throughput drug screening.
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+ dataset_description: >-
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+ Many drug-like molecules phase-separate in aqueous solutions causing false-positives
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+ in in biochemical assays often used for drug screening. The Aggregator Advisor
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+ (https://advisor.docking.org/) is a web-tool hosted by the Shoichet Lab at UCSF
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+ and used to assess the risk of a molecules being an aggregetor, may aggregate in
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+ biochemical assays based on the chemical similarity to known aggregators, and
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+ physical properties. This dataset includes the known aggregator from the
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+ Aggregator Advisor 2022/06 release curated from 20 sources. Since
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+ aggregation is dependent on the hydrophobicity of the compound, the predicted
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+ logP is also computed for each compound.
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  citation: |-
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  @article
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  {Irwin2015, title = {An Aggregation Advisor for Ligand Discovery},
 
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  ---
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  # Aggregator Advisor
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+ The [Aggregator Advisor](https://advisor.docking.org/) is a web-tool hosted
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+ by the Shoichet Lab at UCSF and used to assess the risk of a molecules being
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+ an aggregetor, may aggregate in biochemical assays based on the chemical
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+ similarity to known aggregators, and physical properties. The most current
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+ release (2022/06) contains 12645 known aggregator molecules from 20 sources.
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  The train and test datasets uploaded to our Hugging Face repository have been sanitized and split from the original dataset
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  If you want to try these processes with the original dataset, please follow the instructions in the [Processing Script.py](https://huggingface.co/datasets/maomlab/AggregatorAdvisor/blob/main/Preprocessing%20Script.py) file located in the AggregatorAdvisor.