-
2
-
-
0037079054
-
Computational systems biology
-
doi:10.1038/nature01254. PubMed: 12432404
-
Kitano H (2002) Computational systems biology. Nature 420: 206-210. doi:10.1038/nature01254. PubMed: 12432404.
-
(2002)
Nature
, vol.420
, pp. 206-210
-
-
Kitano, H.1
-
3
-
-
5044227742
-
The evolution of molecular biology into systems biology
-
doi:10.1038/nbt1020. PubMed: 15470464
-
Westerhoff HV, Palsson BO (2004) The evolution of molecular biology into systems biology. Nat Biotechnol 22: 1249-1252. doi:10.1038/nbt1020. PubMed: 15470464.
-
(2004)
Nat Biotechnol
, vol.22
, pp. 1249-1252
-
-
Westerhoff, H.V.1
Palsson, B.O.2
-
4
-
-
84862510972
-
Large-scale prediction and testing of drug activity on side-effect targets
-
PubMed: 22722194
-
Lounkine E, Keiser MJ, Whitebread S, Mikhailov D, Hamon J et al. (2012) Large-scale prediction and testing of drug activity on side-effect targets. Nature 486: 361-367. PubMed: 22722194.
-
(2012)
Nature
, vol.486
, pp. 361-367
-
-
Lounkine, E.1
Keiser, M.J.2
Whitebread, S.3
Mikhailov, D.4
Hamon, J.5
-
5
-
-
77956477049
-
Drug profiling: Knowing where it hits
-
doi:10.1016/j.drudis.2010.06.006. PubMed: 20601095
-
Merino A, Bronowska AK, Jackson DB, Cahill DJ (2010) Drug profiling: knowing where it hits. Drug Discov Today 15: 749-756. doi:10.1016/j.drudis.2010. 06.006. PubMed: 20601095.
-
(2010)
Drug Discov Today
, vol.15
, pp. 749-756
-
-
Merino, A.1
Bronowska, A.K.2
Jackson, D.B.3
Cahill, D.J.4
-
6
-
-
79956124247
-
An active role for machine learning in drug development
-
doi:10.1038/nchembio.576. PubMed: 21587249
-
Murphy RF (2011) An active role for machine learning in drug development. Nat Chem Biol 7: 327-330. doi:10.1038/nchembio.576. PubMed: 21587249.
-
(2011)
Nat Chem Biol
, vol.7
, pp. 327-330
-
-
Murphy, R.F.1
-
8
-
-
9444277556
-
PAC Bounds for Multi-armed Bandit and Markov Decision Processes
-
J KivinenR Sloan. Springer Berlin / Heidelberg
-
Even-Dar E, Mannor S, Mansour Y (2002) PAC Bounds for Multi-armed Bandit and Markov Decision Processes. In: J KivinenR Sloan. Computational Learning Theory. Springer Berlin / Heidelberg. pp. 193-209.
-
(2002)
Computational Learning Theory
, pp. 193-209
-
-
Even-Dar, E.1
Mannor, S.2
Mansour, Y.3
-
9
-
-
1242285091
-
Active Sampling for Class Probability Estimation and Ranking
-
doi: 10.1023/B:MACH.0000011806.12374.c3
-
Saar-Tsechansky M, Provost F (2004) Active Sampling for Class Probability Estimation and Ranking. Mach Learn 54: 153-178. doi: 10.1023/B:MACH.0000011806. 12374.c3.
-
(2004)
Mach Learn
, vol.54
, pp. 153-178
-
-
Saar-Tsechansky, M.1
Provost, F.2
-
11
-
-
70349671213
-
Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning
-
PubMed: 19756158
-
Danziger SA, Baronio R, Ho L, Hall L, Salmon K et al. (2009) Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning. PLoS Comput Biol 5: e1000498. PubMed: 19756158.
-
(2009)
PLoS Comput Biol
, vol.5
-
-
Danziger, S.A.1
Baronio, R.2
Ho, L.3
Hall, L.4
Salmon, K.5
-
12
-
-
0037365194
-
Active learning with support vector machines in the drug discovery process
-
doi:10.1021/ci025620t. PubMed: 12653536
-
Warmuth MK, Liao J, Rätsch G, Mathieson M, Putta S et al. (2003) Active learning with support vector machines in the drug discovery process. J Chem Inf Comput Sci 43: 667-673. doi:10.1021/ci025620t. PubMed: 12653536.
-
(2003)
J Chem Inf Comput Sci
, vol.43
, pp. 667-673
-
-
Warmuth, M.K.1
Liao, J.2
Rätsch, G.3
Mathieson, M.4
Putta, S.5
-
13
-
-
44449101219
-
Virtual screening system for finding structurally diverse hits by active learning
-
doi:10.1021/ci700085q. PubMed: 18351729
-
Fujiwara Y, Yamashita Y, Osoda T, Asogawa M, Fukushima C et al. (2008) Virtual screening system for finding structurally diverse hits by active learning. J Chem Inf Model 48: 930-940. doi:10.1021/ci700085q. PubMed: 18351729.
-
(2008)
J Chem Inf Model
, vol.48
, pp. 930-940
-
-
Fujiwara, Y.1
Yamashita, Y.2
Osoda, T.3
Asogawa, M.4
Fukushima, C.5
-
14
-
-
10044229345
-
Active learning with support vector machine applied to gene expression data for cancer classification
-
doi:10.1021/ci049810a. PubMed: 15554662
-
Liu Y (2004) Active learning with support vector machine applied to gene expression data for cancer classification. J Chem Inf Comput Sci 44: 1936-1941. doi:10.1021/ci049810a. PubMed: 15554662.
-
(2004)
J Chem Inf Comput Sci
, vol.44
, pp. 1936-1941
-
-
Liu, Y.1
-
15
-
-
75149162532
-
Active learning for human protein-protein interaction prediction
-
doi:10.1186/1471-2105-11-S1-S57. PubMed: 20122232
-
Mohamed TP, Carbonell JG, Ganapathiraju MK (2010) Active learning for human protein-protein interaction prediction. BMC Bioinformatics 11 Suppl 1: S57. doi:10.1186/1471-2105-11-S1-S57. PubMed: 20122232.
-
(2010)
BMC Bioinformatics
, vol.11
, Issue.SUPPL. 1
-
-
Mohamed, T.P.1
Carbonell, J.G.2
Ganapathiraju, M.K.3
-
17
-
-
30344450270
-
An Extensible SAT-solver
-
E GiunchigliaA Tacchella. Springer Berlin Heidelberg
-
Eén N, Sörensson N (2004) An Extensible SAT-solver. In: E GiunchigliaA Tacchella. Theory and Applications of Satisfiability Testing: Springer Berlin Heidelberg. pp. 502-518
-
(2004)
Theory and Applications of Satisfiability Testing
, pp. 502-518
-
-
Eén, N.1
Sörensson, N.2
-
19
-
-
33749335282
-
The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease
-
doi: 10.1126/science.1132939. PubMed: 17008526
-
Lamb J, Crawford ED, Peck D, Modell JW, Blat IC et al. (2006) The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease. Science 313: 1929-1935. doi: 10.1126/science.1132939. PubMed: 17008526.
-
(2006)
Science
, vol.313
, pp. 1929-1935
-
-
Lamb, J.1
Crawford, E.D.2
Peck, D.3
Modell, J.W.4
Blat, I.C.5
-
20
-
-
84892371238
-
-
Broad Institute
-
(2013) Connectivity Map. Broad Institute.
-
(2013)
Connectivity Map
-
-
-
21
-
-
78249285918
-
Lower Bounds on Learning Random Structures with Statistical Queries
-
M HutterF StephanV VovkT Zeugmann. Springer Berlin / Heidelberg
-
Angluin D, Eisenstat D, Kontorovich L, Reyzin L (2010) Lower Bounds on Learning Random Structures with Statistical Queries. In: M HutterF StephanV VovkT Zeugmann. Algorithmic Learning Theory. Springer Berlin / Heidelberg. pp. 194-208.
-
(2010)
Algorithmic Learning Theory
, pp. 194-208
-
-
Angluin, D.1
Eisenstat, D.2
Kontorovich, L.3
Reyzin, L.4
-
22
-
-
0242712751
-
Global Optimization and Constraint Satisfaction: The Branch-and-Reduce Approach
-
Sahinidis NV (2003) Global Optimization and Constraint Satisfaction: The Branch-and-Reduce Approach. Lect Notes. Comp Sci 2861: 1-16.
-
(2003)
Lect Notes. Comp Sci
, vol.2861
, pp. 1-16
-
-
Sahinidis, N.V.1
-
23
-
-
0346856929
-
Characterizing selection bias using experimental data
-
doi:10.2307/2999630
-
Heckman J, Ichimura H, Smith J, Todd P (1998) Characterizing selection bias using experimental data. Econometrica 66: 1017-1098. doi:10.2307/2999630.
-
(1998)
Econometrica
, vol.66
, pp. 1017-1098
-
-
Heckman, J.1
Ichimura, H.2
Smith, J.3
Todd, P.4
-
24
-
-
71049116435
-
Exact Matrix Completion via Convex
-
doi:10.1007/s10208-009-9045-5
-
Candes EJ, Recht B (2009) Exact Matrix Completion via Convex. Optimization - Found Comput Math 9: 717-772. doi:10.1007/s10208-009-9045-5.
-
(2009)
Optimization - Found Comput Math
, vol.9
, pp. 717-772
-
-
Candes, E.J.1
Recht, B.2
-
25
-
-
3242717928
-
Recovering the missing components in a large noisy low-rank matrix: Application to SFM
-
doi: 10.1109/TPAMI.2004.52
-
Chen P, Suter D (2004) Recovering the missing components in a large noisy low-rank matrix: application to SFM. Pattern Analysis and Machine Intelligence, IEEE Transactions On 26: 1051-1063. doi: 10.1109/TPAMI.2004.52.
-
(2004)
Pattern Analysis and Machine Intelligence, IEEE Transactions on
, vol.26
, pp. 1051-1063
-
-
Chen, P.1
Suter, D.2
-
26
-
-
0034339545
-
Multiple imputation for missing data: A cautionary tale
-
doi: 10.1177/0049124100028003003
-
Allison P (2000) Multiple imputation for missing data: A cautionary tale. Sociological Methods and Research 28: 301-309. doi: 10.1177/ 0049124100028003003.
-
(2000)
Sociological Methods and Research
, vol.28
, pp. 301-309
-
-
Allison, P.1
-
27
-
-
0017133178
-
Inference and missing data
-
doi:10.1093/biomet/63.3.581
-
Rubin DB (1976) Inference and missing data. Biometrika 63: 581-592. doi:10.1093/biomet/63.3.581.
-
(1976)
Biometrika
, vol.63
, pp. 581-592
-
-
Rubin, D.B.1
|