Update README.md

README.md

@@ -227,7 +227,8 @@ Select the suitable preprocessing methods from the "preprocess.py" module.
 
 
 ### data-curation.py
-This file curates, i.e., merges datasets, selects most reliable values among multiple occurences, and adds 2D descriptors from 9 different standardized datasets that are obtained after the pre-processing step.
+This file curates, i.e., merges datasets, selects most reliable values among multiple occurences, 
+and adds 2D descriptors from 9 different standardized datasets that are obtained after the pre-processing step.
 
 inputs:
 
@@ -260,19 +261,32 @@ Prediction
 The original AqSoDB dataset does not define splits, so here we have used the `Realistic Split` method described
 in [(Martin et al., 2018)](https://doi.org/10.1021/acs.jcim.7b00166).
 
-### License
-MIT License
-
-Copyright (c) 2019 Murat Cihan Sorkun
-
-Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), 
-to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, 
-and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, 
-WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+### Citation
+TY  - JOUR
+AU  - Sorkun, Murat Cihan
+AU  - Khetan, Abhishek
+AU  - Er, S√ºleyman
+PY  - 2019
+DA  - 2019/08/08
+TI  - AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds
+JO  - Scientific Data
+SP  - 143
+VL  - 6
+IS  - 1
+AB  - Water is a ubiquitous solvent in chemistry and life. 
+It is therefore no surprise that the aqueous solubility of compounds has a key role in various domains, 
+including but not limited to drug discovery, paint, coating, and battery materials design. 
+Measurement and prediction of aqueous solubility is a complex and prevailing challenge in chemistry. 
+For the latter, different data-driven prediction models have recently been developed to augment the physics-based modeling approaches. 
+To construct accurate data-driven estimation models, it is essential that the underlying experimental calibration data used by these models is of high fidelity and quality.
+Existing solubility datasets show variance in the chemical space of compounds covered, measurement methods, experimental conditions, 
+but also in the non-standard representations, size, and accessibility of data. 
+To address this problem, we generated a new database of compounds, AqSolDB, by merging a total of nine different aqueous solubility datasets, 
+curating the merged data, standardizing and validating the compound representation formats, marking with reliability labels, and providing 2D descriptors of compounds as a Supplementary Resource.
+SN  - 2052-4463
+UR  - https://doi.org/10.1038/s41597-019-0151-1
+DO  - 10.1038/s41597-019-0151-1
+ID  - Sorkun2019
+ER  - 
 ```