A citation-based method for searching scientific literature

David Rogers, Mathew Hahn. J Chem Inf Model 2010
Times Cited: 2616







List of co-cited articles
371 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Criteria for the Research Institute for Fragrance Materials, Inc. (RIFM) safety evaluation process for fragrance ingredients.
A M Api, D Belsito, M Bruze, P Cadby, P Calow, M L Dagli, W Dekant, G Ellis, A D Fryer, M Fukayama,[...]. Food Chem Toxicol 2015
38

Integrating habits and practices data for soaps, cosmetics and air care products into an existing aggregate exposure model.
D Comiskey, A M Api, C Barrett, G Ellis, C McNamara, C O'Mahony, S H Robison, J Rose, B Safford, B Smith,[...]. Regul Toxicol Pharmacol 2017
38

An in silico skin absorption model for fragrance materials.
Jie Shen, Lambros Kromidas, Terry Schultz, Sneha Bhatia. Food Chem Toxicol 2014
805
38


Use of an aggregate exposure model to estimate consumer exposure to fragrance ingredients in personal care and cosmetic products.
B Safford, A M Api, C Barratt, D Comiskey, E J Daly, G Ellis, C McNamara, C O'Mahony, S Robison, B Smith,[...]. Regul Toxicol Pharmacol 2015
38


A strategy for structuring and reporting a read-across prediction of toxicity.
T W Schultz, P Amcoff, E Berggren, F Gautier, M Klaric, D J Knight, C Mahony, M Schwarz, A White, M T D Cronin. Regul Toxicol Pharmacol 2015
805
38

Application of the expanded Creme RIFM consumer exposure model to fragrance ingredients in cosmetic, personal care and air care products.
B Safford, A M Api, C Barratt, D Comiskey, G Ellis, C McNamara, C O'Mahony, S Robison, J Rose, B Smith,[...]. Regul Toxicol Pharmacol 2017
38

CAESAR models for developmental toxicity.
Antonio Cassano, Alberto Manganaro, Todd Martin, Douglas Young, Nadège Piclin, Marco Pintore, Davide Bigoni, Emilio Benfenati. Chem Cent J 2010
843
38

Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization.
David W Roberts, Grace Patlewicz, Petra S Kern, Frank Gerberick, Ian Kimber, Rebecca J Dearman, Cindy A Ryan, David A Basketter, Aynur O Aptula. Chem Res Toxicol 2007
35

Application of the threshold of toxicological concern (TTC) to the safety evaluation of cosmetic ingredients.
R Kroes, A G Renwick, V Feron, C L Galli, M Gibney, H Greim, R H Guy, J C Lhuguenot, J J M van de Sandt. Food Chem Toxicol 2007
979
34

Correlation of chemical structure with reproductive and developmental toxicity as it relates to the use of the threshold of toxicological concern.
Michael C Laufersweiler, Bernard Gadagbui, Irene M Baskerville-Abraham, Andrew Maier, Alison Willis, Anthony R Scialli, Gregory J Carr, Susan P Felter, Karen Blackburn, George Daston. Regul Toxicol Pharmacol 2012
883
34

Novel database for exposure to fragrance ingredients in cosmetics and personal care products.
D Comiskey, A M Api, C Barratt, E J Daly, G Ellis, C McNamara, C O'Mahony, S H Robison, B Safford, B Smith,[...]. Regul Toxicol Pharmacol 2015
29

Fragrance Skin Sensitization Evaluation and Human Testing: 30-Year Experience.
Mihwa Na, Gretchen Ritacco, Devin O'Brien, Maura Lavelle, Anne Marie Api, David Basketter. Dermatitis 2021
206
29

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.
Rafael Gómez-Bombarelli, Jennifer N Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D Hirzel, Ryan P Adams, Alán Aspuru-Guzik. ACS Cent Sci 2018
676
14

Comparison of Cramer classification between Toxtree, the OECD QSAR Toolbox and expert judgment.
Sneha Bhatia, Terry Schultz, David Roberts, Jie Shen, Lambros Kromidas, Anne Marie Api. Regul Toxicol Pharmacol 2015
317
14

Estimation of toxic hazard--a decision tree approach.
G M Cramer, R A Ford, R L Hall. Food Cosmet Toxicol 1978
682
14

Reoptimization of MDL keys for use in drug discovery.
Joseph L Durant, Burton A Leland, Douglas R Henry, James G Nourse. J Chem Inf Comput Sci 2002
617
13

ChEMBL: towards direct deposition of bioassay data.
David Mendez, Anna Gaulton, A Patrícia Bento, Jon Chambers, Marleen De Veij, Eloy Félix, María Paula Magariños, Juan F Mosquera, Prudence Mutowo, Michal Nowotka,[...]. Nucleic Acids Res 2019
500
9

MoleculeNet: a benchmark for molecular machine learning.
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S Pappu, Karl Leswing, Vijay Pande. Chem Sci 2017
489
9

The ChEMBL database in 2017.
Anna Gaulton, Anne Hersey, Michał Nowotka, A Patrícia Bento, Jon Chambers, David Mendez, Prudence Mutowo, Francis Atkinson, Louisa J Bellis, Elena Cibrián-Uhalte,[...]. Nucleic Acids Res 2017
984
9

ZINC 15--Ligand Discovery for Everyone.
Teague Sterling, John J Irwin. J Chem Inf Model 2015
8

Analyzing Learned Molecular Representations for Property Prediction.
Kevin Yang, Kyle Swanson, Wengong Jin, Connor Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea,[...]. J Chem Inf Model 2019
241
8

Molecular de-novo design through deep reinforcement learning.
Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen. J Cheminform 2017
295
8

Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps.
Mihir S Date, Devin O'Brien, Danielle J Botelho, Terry W Schultz, Daniel C Liebler, Trevor M Penning, Daniel T Salvito. Chem Res Toxicol 2020
64
12

Deep reinforcement learning for de novo drug design.
Mariya Popova, Olexandr Isayev, Alexander Tropsha. Sci Adv 2018
320
7


DrugBank 5.0: a major update to the DrugBank database for 2018.
David S Wishart, Yannick D Feunang, An C Guo, Elvis J Lo, Ana Marcu, Jason R Grant, Tanvir Sajed, Daniel Johnson, Carin Li, Zinat Sayeeda,[...]. Nucleic Acids Res 2018
7

Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.
Zhaoping Xiong, Dingyan Wang, Xiaohong Liu, Feisheng Zhong, Xiaozhe Wan, Xutong Li, Zhaojun Li, Xiaomin Luo, Kaixian Chen, Hualiang Jiang,[...]. J Med Chem 2020
115
6

A graph-convolutional neural network model for the prediction of chemical reactivity.
Connor W Coley, Wengong Jin, Luke Rogers, Timothy F Jamison, Tommi S Jaakkola, William H Green, Regina Barzilay, Klavs F Jensen. Chem Sci 2018
158
6

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition.
Sabrina Jaeger, Simone Fulle, Samo Turk. J Chem Inf Model 2018
165
6

Machine learning in chemoinformatics and drug discovery.
Yu-Chen Lo, Stefano E Rensi, Wen Torng, Russ B Altman. Drug Discov Today 2018
309
6

Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations.
Robin Winter, Floriane Montanari, Frank Noé, Djork-Arné Clevert. Chem Sci 2018
139
6

Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction.
Philippe Schwaller, Teodoro Laino, Théophile Gaudin, Peter Bolgar, Christopher A Hunter, Costas Bekas, Alpha A Lee. ACS Cent Sci 2019
131
6

Mordred: a molecular descriptor calculator.
Hirotomo Moriwaki, Yu-Shi Tian, Norihito Kawashita, Tatsuya Takagi. J Cheminform 2018
215
6

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
6

Molecular fingerprint similarity search in virtual screening.
Adrià Cereto-Massagué, María José Ojeda, Cristina Valls, Miquel Mulero, Santiago Garcia-Vallvé, Gerard Pujadas. Methods 2015
247
5

ZINC20-A Free Ultralarge-Scale Chemical Database for Ligand Discovery.
John J Irwin, Khanh G Tang, Jennifer Young, Chinzorig Dandarchuluun, Benjamin R Wong, Munkhzul Khurelbaatar, Yurii S Moroz, John Mayfield, Roger A Sayle. J Chem Inf Model 2020
90
5

Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.
Connor W Coley, Regina Barzilay, William H Green, Tommi S Jaakkola, Klavs F Jensen. J Chem Inf Model 2017
142
5

Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17.
Lars Ruddigkeit, Ruud van Deursen, Lorenz C Blum, Jean-Louis Reymond. J Chem Inf Model 2012
419
5

Optimization of Molecules via Deep Reinforcement Learning.
Zhenpeng Zhou, Steven Kearnes, Li Li, Richard N Zare, Patrick Riley. Sci Rep 2019
105
5

PubChem in 2021: new data content and improved web interfaces.
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu,[...]. Nucleic Acids Res 2021
725
5

Planning chemical syntheses with deep neural networks and symbolic AI.
Marwin H S Segler, Mike Preuss, Mark P Waller. Nature 2018
454
5

Prediction of Organic Reaction Outcomes Using Machine Learning.
Connor W Coley, Regina Barzilay, Tommi S Jaakkola, William H Green, Klavs F Jensen. ACS Cent Sci 2017
200
5

Extension of the Dermal Sensitisation Threshold (DST) approach to incorporate chemicals classified as reactive.
Robert J Safford, Anne Marie Api, David W Roberts, Jon F Lalko. Regul Toxicol Pharmacol 2015
284
5

Deep learning enables rapid identification of potent DDR1 kinase inhibitors.
Alex Zhavoronkov, Yan A Ivanenkov, Alex Aliper, Mark S Veselov, Vladimir A Aladinskiy, Anastasiya V Aladinskaya, Victor A Terentiev, Daniil A Polykovskiy, Maksim D Kuznetsov, Arip Asadulaev,[...]. Nat Biotechnol 2019
302
5

Open Babel: An open chemical toolbox.
Noel M O'Boyle, Michael Banck, Craig A James, Chris Morley, Tim Vandermeersch, Geoffrey R Hutchison. J Cheminform 2011
5

Fragrance materials in asthma: a pilot study using a surrogate aerosol product.
Dilini Vethanayagam, Harissios Vliagoftis, Dennell Mah, Jeremy Beach, Ladd Smith, Redwan Moqbel. J Asthma 2013
47
10

Simulated inhalation levels of fragrance materials in a surrogate air freshener formulation.
Robert E Rogers, Daniel A Isola, Chwen-Jyh Jeng, Andrea Lefebvre, Ladd W Smith. Environ Sci Technol 2005
66
7

Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.
Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng Cao, Jian Wu, Tingjun Hou. J Cheminform 2021
56
8


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.