546
D. Fourches
22. Young D, Martin D, Venkatapathy R, Harten P (2008) Are the chemical structures in your
QSAR correct? QSAR Comb Sci 27:1337–1345
23. Ekins S, Olechno J, Williams AJ (2013) Dispensing processes impact apparent biological
activity as determined by computational and statistical analyses. PLoS One 8:e62325
24. Prinz F, Schlange T, Asadullah K (2011) Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov 10:712
25. Fourches D, Muratov E, Tropsha A (2010) Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research. J Chem Inf Model
50:1189–1204
26. Baker NC, Hemminger BM (2010) Mining connections between chemicals, proteins, and
diseases extracted from Medline annotations. J Biomed Inform 43:510–519
27. Fourches D, Barnes JC, Day NC, Bradley P, Reed JZ, Tropsha A (2010) Cheminformatics
analysis of assertions mined from literature that describe drug-induced liver injury in different species. Chem Res Toxicol 23:171–183
28. Low Y, Uehara T, Minowa Y et al (2011) Predicting drug-induced hepatotoxicity using
QSAR and toxicogenomics approaches. Chem Res Toxicol 24:1251–1262
29. Low Y, Sedykh AY, Fourches D, Golbraikh A, Whelan M, Rusyn I, Tropsha A (2013) Integrative chemical-biological read-across approach for chemical hazard classification. Chem Res
Toxicol 26:1199–1208
30. Donaldson K, Poland CA (2009) Nanotoxicology: new insights into nanotubes. Nat Nanotechnol 4:708–710
31. Balbus JM, Florini K, Denison RA, Walsh SA (2006) Getting it right the first time: developing nanotechnology while protecting workers, public health, and the environment. Ann N Y
Acad Sci 1076:331–342
32. Hart P (2009) Nanotechnology, synthetic biology, & public opinion. The Woodrow Wilson
International Center For Scholars
33. Bystrzejewska-Piotrowska G, Golimowski J, Urban PL (2009) Nanoparticles: their potential
toxicity, waste and environmental management. Waste Manag 29:2587–2595
34. Jones R (2009) Nanotechnology, energy and markets. Nat Nanotechnol 4:75
35. Lockman PR, Mumper RJ, Khan MA, Allen DD (2002) Nanoparticle technology for drug
delivery across the blood-brain barrier. Drug Dev Ind Pharm 28:1–13
36. Linkov I, Satterstrom FK, Corey LM (2008) Nanotoxicology and nanomedicine: making
hard decisions. Nanomedicine 4:167–171
37. Fourches D, Pu D, Tassa C, Weissleder R, Shaw SY, Mumper RJ, Tropsha A (2010) Quantitative nanostructure-activity relationship modeling. ACS Nano 4:5703–5712
38. Fourches D, Pu D, Tropsha A (2011) Exploring quantitative nanostructure-activity relationships (QNAR) modeling as a tool for predicting biological effects of manufactured nanoparticles. Comb Chem High Throughput Screen 14:217–225
39. Heinzerling L, Klein R, Rarey M (2012) Fast force field-based optimization of protein-ligand
complexes with graphics processor. J Comput Chem 33:2554–2565
40. Fourches D, Tropsha A (2013) Using graph indices for the analysis and comparison of chemical datasets. Mol Inform 32:827–842
41. Rognan D (2013) Towards the next generation of computational chemogenomics tools. Mol
Inform 32:1029–1034
D. Fourches
22. Young D, Martin D, Venkatapathy R, Harten P (2008) Are the chemical structures in your
QSAR correct? QSAR Comb Sci 27:1337–1345
23. Ekins S, Olechno J, Williams AJ (2013) Dispensing processes impact apparent biological
activity as determined by computational and statistical analyses. PLoS One 8:e62325
24. Prinz F, Schlange T, Asadullah K (2011) Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov 10:712
25. Fourches D, Muratov E, Tropsha A (2010) Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research. J Chem Inf Model
50:1189–1204
26. Baker NC, Hemminger BM (2010) Mining connections between chemicals, proteins, and
diseases extracted from Medline annotations. J Biomed Inform 43:510–519
27. Fourches D, Barnes JC, Day NC, Bradley P, Reed JZ, Tropsha A (2010) Cheminformatics
analysis of assertions mined from literature that describe drug-induced liver injury in different species. Chem Res Toxicol 23:171–183
28. Low Y, Uehara T, Minowa Y et al (2011) Predicting drug-induced hepatotoxicity using
QSAR and toxicogenomics approaches. Chem Res Toxicol 24:1251–1262
29. Low Y, Sedykh AY, Fourches D, Golbraikh A, Whelan M, Rusyn I, Tropsha A (2013) Integrative chemical-biological read-across approach for chemical hazard classification. Chem Res
Toxicol 26:1199–1208
30. Donaldson K, Poland CA (2009) Nanotoxicology: new insights into nanotubes. Nat Nanotechnol 4:708–710
31. Balbus JM, Florini K, Denison RA, Walsh SA (2006) Getting it right the first time: developing nanotechnology while protecting workers, public health, and the environment. Ann N Y
Acad Sci 1076:331–342
32. Hart P (2009) Nanotechnology, synthetic biology, & public opinion. The Woodrow Wilson
International Center For Scholars
33. Bystrzejewska-Piotrowska G, Golimowski J, Urban PL (2009) Nanoparticles: their potential
toxicity, waste and environmental management. Waste Manag 29:2587–2595
34. Jones R (2009) Nanotechnology, energy and markets. Nat Nanotechnol 4:75
35. Lockman PR, Mumper RJ, Khan MA, Allen DD (2002) Nanoparticle technology for drug
delivery across the blood-brain barrier. Drug Dev Ind Pharm 28:1–13
36. Linkov I, Satterstrom FK, Corey LM (2008) Nanotoxicology and nanomedicine: making
hard decisions. Nanomedicine 4:167–171
37. Fourches D, Pu D, Tassa C, Weissleder R, Shaw SY, Mumper RJ, Tropsha A (2010) Quantitative nanostructure-activity relationship modeling. ACS Nano 4:5703–5712
38. Fourches D, Pu D, Tropsha A (2011) Exploring quantitative nanostructure-activity relationships (QNAR) modeling as a tool for predicting biological effects of manufactured nanoparticles. Comb Chem High Throughput Screen 14:217–225
39. Heinzerling L, Klein R, Rarey M (2012) Fast force field-based optimization of protein-ligand
complexes with graphics processor. J Comput Chem 33:2554–2565
40. Fourches D, Tropsha A (2013) Using graph indices for the analysis and comparison of chemical datasets. Mol Inform 32:827–842
41. Rognan D (2013) Towards the next generation of computational chemogenomics tools. Mol
Inform 32:1029–1034