-
1
-
-
34547656228
-
The application of discovery toxicology and pathology towards the design of safer pharmaceutical lead candidates
-
1:CAS:528:DC%2BD2sXotl2qtb4%3D
-
Kramer JA, Sagartz JE, Morris DL (2007) The application of discovery toxicology and pathology towards the design of safer pharmaceutical lead candidates. Nat Rev Drug Discov 6:636-649
-
(2007)
Nat Rev Drug Discov
, vol.6
, pp. 636-649
-
-
Kramer, J.A.1
Sagartz, J.E.2
Morris, D.L.3
-
2
-
-
84877667917
-
Toxicokinetics as a key to the integrated toxicity risk assessment based primarily on non-animal approaches
-
1:CAS:528:DC%2BC38XhtVyjs7bM
-
Coecke S, Pelkonen O, Leite SB, Bernauer U, Bessems JG, Bois FY, Gundert-Remy U, Loizou G, Testai E, Zaldvar JM (2013) Toxicokinetics as a key to the integrated toxicity risk assessment based primarily on non-animal approaches. Toxicol In-vitro 27:1570-1577
-
(2013)
Toxicol In-vitro
, vol.27
, pp. 1570-1577
-
-
Coecke, S.1
Pelkonen, O.2
Leite, S.B.3
Bernauer, U.4
Bessems, J.G.5
Bois, F.Y.6
Gundert-Remy, U.7
Loizou, G.8
Testai, E.9
Zaldvar, J.M.10
-
3
-
-
16544379129
-
Medical device development from prototype to regulatory approval
-
Kaplan AV, Baim DS, Smith JJ, Feigal DA, Simons M, Jefferys D, Thomas JF, Kuntz RE, Leon MB (2004) Medical device development from prototype to regulatory approval. Circulation 109(25):3068-3072
-
(2004)
Circulation
, vol.109
, Issue.25
, pp. 3068-3072
-
-
Kaplan, A.V.1
Baim, D.S.2
Smith, J.J.3
Feigal, D.A.4
Simons, M.5
Jefferys, D.6
Thomas, J.F.7
Kuntz, R.E.8
Leon, M.B.9
-
4
-
-
41549105449
-
Computational toxicology in drug development
-
1:CAS:528:DC%2BD1cXkslart7Y%3D
-
Muster W, Breidenbach A, Fischer H, Kirchner S, Mller L, Phler A (2008) Computational toxicology in drug development. Drug Discov Today 13(7):303-310
-
(2008)
Drug Discov Today
, vol.13
, Issue.7
, pp. 303-310
-
-
Muster, W.1
Breidenbach, A.2
Fischer, H.3
Kirchner, S.4
Mller, L.5
Phler, A.6
-
5
-
-
0042355457
-
In silico prediction of drug toxicity
-
1:CAS:528:DC%2BD3sXmsVGns70%3D
-
Dearden JC (2003) In silico prediction of drug toxicity. J Comput Aided Mol Des 17(2-4):119-127
-
(2003)
J Comput Aided Mol Des
, vol.17
, Issue.2-4
, pp. 119-127
-
-
Dearden, J.C.1
-
6
-
-
84860286854
-
Review of qsar models and software tools for predicting genotoxicity and carcinogenicity
-
Publications Office of the European.Union
-
Serafimova R, Gatnik MF, Worth A (2010) Review of qsar models and software tools for predicting genotoxicity and carcinogenicity. Publications Office of the European Union. JRC Scientific and technical reports
-
(2010)
JRC Scientific and technical reports
-
-
Serafimova, R.1
Gatnik, M.F.2
Worth, A.3
-
8
-
-
0003302467
-
Use of QSARs in international decision-making frameworks to predict health effects of chemical substances
-
1:CAS:528:DC%2BD3sXnt12rtLY%3D
-
Cronin MT, Jaworska JS, Walker JD, Comber MH, Watts CD, Worth AP (2003) Use of QSARs in international decision-making frameworks to predict health effects of chemical substances. Environ Health Perspect 111(10):1391-1401
-
(2003)
Environ Health Perspect
, vol.111
, Issue.10
, pp. 1391-1401
-
-
Cronin, M.T.1
Jaworska, J.S.2
Walker, J.D.3
Comber, M.H.4
Watts, C.D.5
Worth, A.P.6
-
9
-
-
9944253258
-
Animal testing and alternative approaches for the human health risk assessment under the proposed new european chemicals regulation
-
Hfer T, Gerner I, Gundert-Remy U, Liebsch M, Schulte A, Spielmann H, Vogel R, Wettig K (2004) Animal testing and alternative approaches for the human health risk assessment under the proposed new european chemicals regulation. Arch Toxicol 78(10):549-564
-
(2004)
Arch Toxicol
, vol.78
, Issue.10
, pp. 549-564
-
-
Hfer, T.1
Gerner, I.2
Gundert-Remy, U.3
Liebsch, M.4
Schulte, A.5
Spielmann, H.6
Vogel, R.7
Wettig, K.8
-
10
-
-
79961119877
-
In silico toxicology models and databases as FDA Critical Path Initiative toolkits
-
1:CAS:528:DC%2BC3MXnvFenurY%3D
-
Valerio LG Jr (2011) In silico toxicology models and databases as FDA Critical Path Initiative toolkits. Hum Genomics 5(3):200-207
-
(2011)
Hum Genomics
, vol.5
, Issue.3
, pp. 200-207
-
-
Valerio, L.G.1
-
11
-
-
0029445451
-
US EPA regulatory perspectives on the use of QSAR for new and existing chemical evaluations
-
1:CAS:528:DyaK2MXpsVaqt7g%3D
-
Zeeman M, Auer CM, Clements RG, Nabholz JV, Boethling RS (1995) US EPA regulatory perspectives on the use of QSAR for new and existing chemical evaluations. SAR QSAR Environ Res 3(3):179-201
-
(1995)
SAR QSAR Environ Res
, vol.3
, Issue.3
, pp. 179-201
-
-
Zeeman, M.1
Auer, C.M.2
Clements, R.G.3
Nabholz, J.V.4
Boethling, R.S.5
-
13
-
-
85043802329
-
-
Last accessed Apr
-
EPA T.E.S.T. http://www.epa.gov/nrmrl/std/qsar/qsar.html. Last accessed Apr 2014
-
(2014)
EPA T.E.S.T.
-
-
Epa, T.E.S.T.1
-
14
-
-
85073142597
-
The role of QSAR methodology in the regulatory assessment of chemicals
-
Springer NetherlandsChap. 13
-
Worth AP (2010) Recent advances in QSAR studies. Springer Netherlands, pp 367-382. Chap. 13: The role of QSAR methodology in the regulatory assessment of chemicals
-
(2010)
Recent advances in QSAR studies
, pp. 367-382
-
-
Worth, A.P.1
-
15
-
-
0012906771
-
Summary of a workshop on regulatory acceptance of (q) sars for human health and environmental endpoints
-
Jaworska JS, Comber M, Auer C, Van Leeuwen CJ (2003) Summary of a workshop on regulatory acceptance of (q) sars for human health and environmental endpoints. Environ Health Perspect 111(10):1358-1360
-
(2003)
Environ Health Perspect
, vol.111
, Issue.10
, pp. 1358-1360
-
-
Jaworska, J.S.1
Comber, M.2
Auer, C.3
Van Leeuwen, C.J.4
-
16
-
-
84857770428
-
The challenges involved in modeling toxicity data in silico: a review
-
1:CAS:528:DC%2BC38XlvVSqsbg%3D
-
Gleeson MP, Modi S, Bender A, Marchese L, Robinson R, Kirchmair J, Promkatkaew M, Hannongbua S, Glen RC (2012) The challenges involved in modeling toxicity data in silico: a review. Curr Pharm Des 18(9):1266-1291
-
(2012)
Curr Pharm Des
, vol.18
, Issue.9
, pp. 1266-1291
-
-
Gleeson, M.P.1
Modi, S.2
Bender, A.3
Marchese, L.4
Robinson, R.5
Kirchmair, J.6
Promkatkaew, M.7
Hannongbua, S.8
Glen, R.C.9
-
17
-
-
55249098367
-
A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)
-
1:CAS:528:DC%2BD1cXhtlGlsLjL
-
Zhao C, Boriani E, Chana A, Roncaglioni A, Benfenati E (2008) A new hybrid system of QSAR models for predicting bioconcentration factors (BCF). Chemosphere 73(11):1701-1707
-
(2008)
Chemosphere
, vol.73
, Issue.11
, pp. 1701-1707
-
-
Zhao, C.1
Boriani, E.2
Chana, A.3
Roncaglioni, A.4
Benfenati, E.5
-
18
-
-
85043827010
-
-
VEGALast accessed Apr 2013
-
VEGA. http://www.vega-qsar.eu/. Last accessed Apr 2013
-
-
-
-
19
-
-
84876972436
-
Integration of qsar models for bioconcentration suitable for reach
-
Gissi A, Nicolotti O, Carotti A, Gadaleta D, Lombardo A, Benfenat E (2013) Integration of qsar models for bioconcentration suitable for reach. Sci Total Environ 456:325-332
-
(2013)
Sci Total Environ
, vol.456
, pp. 325-332
-
-
Gissi, A.1
Nicolotti, O.2
Carotti, A.3
Gadaleta, D.4
Lombardo, A.5
Benfenat, E.6
-
20
-
-
0025863682
-
Computer prediction of possible toxic action from chemical structure; the DEREK system
-
1:CAS:528:DyaK3MXlslKqs7c%3D
-
Sanderson DM, Earnshaw CG (1991) Computer prediction of possible toxic action from chemical structure; the DEREK system. Hum Exp Toxicol 10(4):261-273
-
(1991)
Hum Exp Toxicol
, vol.10
, Issue.4
, pp. 261-273
-
-
Sanderson, D.M.1
Earnshaw, C.G.2
-
21
-
-
85043812219
-
-
Lhasa DEREKLast accessed Oct 2014
-
Lhasa DEREK. http://www.lhasalimited.org/products/derek-nexus.htm. Last accessed Oct 2014
-
-
-
-
22
-
-
0001010920
-
Leadscope: software for exploring large sets of screening data
-
1:CAS:528:DC%2BD3cXmtlalt7g%3D
-
Roberts G, Myatt GJ, Johnson WP, Cross KP, Blower PE (2000) Leadscope: software for exploring large sets of screening data. J Chem Inf Comput Sci 40(6):1302-1314
-
(2000)
J Chem Inf Comput Sci
, vol.40
, Issue.6
, pp. 1302-1314
-
-
Roberts, G.1
Myatt, G.J.2
Johnson, W.P.3
Cross, K.P.4
Blower, P.E.5
-
23
-
-
85043824196
-
-
MultiCASE Inc
-
MultiCASE Inc. http://multicase.com/
-
-
-
-
24
-
-
85043824243
-
-
Toxtree - Toxic Hazard Estimation by decision tree approach. http://toxtree.sourceforge.net/. Last accessed 2013
-
Toxtree - Toxic Hazard Estimation by decision tree approach. http://toxtree.sourceforge.net/. Last accessed 2013
-
-
-
-
25
-
-
0016685233
-
Methods for detecting carcinogens and mutagens with the salmonella/mammalian-microsome mutagenicity test
-
1:CAS:528:DyaE28XmvFyqtw%3D%3D
-
Ames BN, McCann J, Yamasaki E (1975) Methods for detecting carcinogens and mutagens with the salmonella/mammalian-microsome mutagenicity test. Mutat Res 31:347-364
-
(1975)
Mutat Res
, vol.31
, pp. 347-364
-
-
Ames, B.N.1
McCann, J.2
Yamasaki, E.3
-
26
-
-
0023677902
-
Computer-assisted analysis of interlaboratory ames test variability
-
Benignia R, Giulianib A (1988) Computer-assisted analysis of interlaboratory ames test variability. J Toxicol Environ Health 25:135-148
-
(1988)
J Toxicol Environ Health
, vol.25
, pp. 135-148
-
-
Benignia, R.1
Giulianib, A.2
-
27
-
-
79959434611
-
Comparative evaluation of in silico systems for ames test mutagenicity prediction: scope and limitations
-
1:CAS:528:DC%2BC3MXlsVWjsLc%3D
-
Hillebrecht A, Muster W, Brigo A, Kansy M, Weiser T, Singer T (2011) Comparative evaluation of in silico systems for ames test mutagenicity prediction: scope and limitations. Chem Res Toxicol 24(6):843-854
-
(2011)
Chem Res Toxicol
, vol.24
, Issue.6
, pp. 843-854
-
-
Hillebrecht, A.1
Muster, W.2
Brigo, A.3
Kansy, M.4
Weiser, T.5
Singer, T.6
-
29
-
-
36148935631
-
Comparison of MC4PC and MDL-QSAR rodent carcinogenicity predictions and the enhancement of predictive performance by combining QSAR models
-
1:CAS:528:DC%2BD2sXhtlaht7jO
-
Contrera JF, Kruhlak NL, Matthews EJ, Benz RD (2007) Comparison of MC4PC and MDL-QSAR rodent carcinogenicity predictions and the enhancement of predictive performance by combining QSAR models. Regul Toxicol Pharmacol 49(3):172-182
-
(2007)
Regul Toxicol Pharmacol
, vol.49
, Issue.3
, pp. 172-182
-
-
Contrera, J.F.1
Kruhlak, N.L.2
Matthews, E.J.3
Benz, R.D.4
-
30
-
-
84994906103
-
BioEpisteme - an in silico approach for predicting and understanding the underlying molecular mechanisms contributing to toxicity responses
-
Valencia A (2010) BioEpisteme - an in silico approach for predicting and understanding the underlying molecular mechanisms contributing to toxicity responses. Toxicol Lett 196(S25):1-48. doi:10.1016/j.toxlet.2010.03.117
-
(2010)
Toxicol Lett
, vol.196
, Issue.S25
, pp. 1-48
-
-
Valencia, A.1
-
31
-
-
40949145715
-
Combined use of MC4PC, MDL-QSAR, BioEpisteme, Leadscope PDM, and Derek for Windows software to achieve high-performance, high-confidence, mode of action-based predictions of chemical carcinogenesis in rodents
-
1:CAS:528:DC%2BD1cXjtlertL0%3D
-
Matthews EJ, Kruhlak NL, Benz RD, Contrera JF, Marchant CA, Yang C (2008) Combined use of MC4PC, MDL-QSAR, BioEpisteme, Leadscope PDM, and Derek for Windows software to achieve high-performance, high-confidence, mode of action-based predictions of chemical carcinogenesis in rodents. Toxicol Mech Methods 18(2-3):189-206
-
(2008)
Toxicol Mech Methods
, vol.18
, Issue.2-3
, pp. 189-206
-
-
Matthews, E.J.1
Kruhlak, N.L.2
Benz, R.D.3
Contrera, J.F.4
Marchant, C.A.5
Yang, C.6
-
32
-
-
0037403516
-
Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
-
Kuncheva LI, Whitaker CJ (2003) Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn 51:181-207
-
(2003)
Mach Learn
, vol.51
, pp. 181-207
-
-
Kuncheva, L.I.1
Whitaker, C.J.2
-
33
-
-
20444399504
-
Boosting: an ensemble learning tool for compound classification and QSAR modeling
-
1:CAS:528:DC%2BD2MXjtlGlur8%3D
-
Svetnik V, Wang T, Tong C, Liaw A, Sheridan RP, Song Q (2005) Boosting: an ensemble learning tool for compound classification and QSAR modeling. J Chem Inf Model 45:786-799
-
(2005)
J Chem Inf Model
, vol.45
, pp. 786-799
-
-
Svetnik, V.1
Wang, T.2
Tong, C.3
Liaw, A.4
Sheridan, R.P.5
Song, Q.6
-
34
-
-
2942596534
-
Ensemble machine learning on gene expression data for cancer classification
-
Tan AC, Gilbert D (2003) Ensemble machine learning on gene expression data for cancer classification. Appl Bioinform 2:75-83
-
(2003)
Appl Bioinform
, vol.2
, pp. 75-83
-
-
Tan, A.C.1
Gilbert, D.2
-
35
-
-
35348915328
-
Classifier ensembles: select real-world applications
-
Oza NC, Tumer K (2008) Classifier ensembles: select real-world applications. Inf Fusion 9:4-20
-
(2008)
Inf Fusion
, vol.9
, pp. 4-20
-
-
Oza, N.C.1
Tumer, K.2
-
36
-
-
79958183664
-
Ensemble QSAR: a QSAR method based on conformational ensembles and metric descriptors
-
1:CAS:528:DC%2BC3MXnvFalur4%3D
-
Pissurlenkar RR, Khedkar VM, Iyer RP, Coutinho EC (2011) Ensemble QSAR: a QSAR method based on conformational ensembles and metric descriptors. J Comput Chem 32(10):2204-2218
-
(2011)
J Comput Chem
, vol.32
, Issue.10
, pp. 2204-2218
-
-
Pissurlenkar, R.R.1
Khedkar, V.M.2
Iyer, R.P.3
Coutinho, E.C.4
-
42
-
-
84892854554
-
A weighted voting framework for classifiers ensembles
-
Kuncheva LI, Rodrguez JJ (2014) A weighted voting framework for classifiers ensembles. Knowl Inf Syst 38:259-275
-
(2014)
Knowl Inf Syst
, vol.38
, pp. 259-275
-
-
Kuncheva, L.I.1
Rodrguez, J.J.2
-
43
-
-
85043825620
-
Bayesian ensemble learning of generative models
-
Aalto Univ
-
Valpola H, Honkela A, Karhunen J, Raiko T, Giannakopoulos X, Ilin A, Oja (2001) Bayesian ensemble learning of generative models. Biennial Report of Adaptive Informatics Research Center, Aalto Univ
-
(2001)
Biennial Report of Adaptive Informatics Research Center
-
-
Valpola, H.1
Honkela, A.2
Karhunen, J.3
Raiko, T.4
Giannakopoulos, X.5
Ilin, A.6
-
44
-
-
84880911175
-
-
The MathWorks Inc
-
MATLAB R2012a (2012) The MathWorks Inc
-
(2012)
MATLAB R
-
-
-
45
-
-
80053295024
-
Gramatica P: Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coeffient
-
Chirico N, Gramatica P: Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coeffient. J Chem Inf Model 51(9):2320-2335
-
J Chem Inf Model
, vol.51
, Issue.9
, pp. 2320-2335
-
-
Chirico, N.1
-
46
-
-
84874425276
-
Interpretable, probability-based confidence metric for continuous quantitative structureactivity relationship models
-
1:CAS:528:DC%2BC3sXht1Cit74%3D
-
Keefer CE, Kauffman GW, Gupta RR (2013) Interpretable, probability-based confidence metric for continuous quantitative structureactivity relationship models. J Chem Inf Model 53(2):368-383
-
(2013)
J Chem Inf Model
, vol.53
, Issue.2
, pp. 368-383
-
-
Keefer, C.E.1
Kauffman, G.W.2
Gupta, R.R.3
-
47
-
-
77951050223
-
Evaluation of model predictive ability by external validation techniques
-
1:CAS:528:DC%2BC3cXkslOmtrk%3D
-
Consonni V, Ballabio D, Todeschini R (2010) Evaluation of model predictive ability by external validation techniques. J Chemom 24(3-4):194-201
-
(2010)
J Chemom
, vol.24
, Issue.3-4
, pp. 194-201
-
-
Consonni, V.1
Ballabio, D.2
Todeschini, R.3
-
48
-
-
84973587732
-
A coefficient of agreement for nominal scales
-
Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37-46
-
(1960)
Educ Psychol Meas
, vol.20
, Issue.1
, pp. 37-46
-
-
Cohen, J.1
-
49
-
-
18544372466
-
Understanding interobserver agreement: the kappa statistic
-
Viera AJ, Garrett JM (2005) Understanding interobserver agreement: the kappa statistic. Fam Med 37(5):360-363
-
(2005)
Fam Med
, vol.37
, Issue.5
, pp. 360-363
-
-
Viera, A.J.1
Garrett, J.M.2
-
50
-
-
33846894344
-
Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models
-
Zou KH, OMalley AJ, Mauri L (2007) Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models. Circulation 115(5):654-657
-
(2007)
Circulation
, vol.115
, Issue.5
, pp. 654-657
-
-
Zou, K.H.1
OMalley, A.J.2
Mauri, L.3
|