-
1
-
-
0034069495
-
Gene ontology: Tool for the unification of biology, the gene ontology consortium
-
M. Ashburner, C. Ball, J. Blake, D. Botstein, H. Butler, J. Cherry, A. Davis, K. Dolinski, S. Dwight, J. Eppig, M. Harris, D. Hill, L. Issel-Tarver, A. Kasarskis, S. Lewis, J. Matese, J. Richardson, M. Ringwald, G. Rubin, and G. Sherlock. Gene ontology: tool for the unification of biology, the gene ontology consortium. Nature Genetics, 25(1):25-29, 2000.
-
(2000)
Nature Genetics
, vol.25
, Issue.1
, pp. 25-29
-
-
Ashburner, M.1
Ball, C.2
Blake, J.3
Botstein, D.4
Butler, H.5
Cherry, J.6
Davis, A.7
Dolinski, K.8
Dwight, S.9
Eppig, J.10
Harris, M.11
Hill, D.12
Issel-Tarver, L.13
Kasarskis, A.14
Lewis, S.15
Matese, J.16
Richardson, J.17
Ringwald, M.18
Rubin, G.19
Sherlock, G.20
more..
-
2
-
-
9444255841
-
A multi-relational decision tree learning algorithm - Implementation and experiments
-
T. Horváth and A. Yamamoto, editors
-
A. Atramentov, H. Leiva, and V. Honavar. A multi-relational decision tree learning algorithm - implementation and experiments. In T. Horváth and A. Yamamoto, editors, Proceedings of the 13th International Conference on Inductive Logic Programming (ILP 2003). Vol. 2835 of Lecture Notes in Artificial Intelligence : Springer-Verlag, pages 38-56, 2003.
-
(2003)
Proceedings of the 13th International Conference on Inductive Logic Programming (ILP 2003). Vol. 2835 of Lecture Notes in Artificial Intelligence: Springer-Verlag
, vol.2835
, pp. 38-56
-
-
Atramentov, A.1
Leiva, H.2
Honavar, V.3
-
8
-
-
0031276011
-
Bayesian network classifiers
-
N. Friedman, D. Geiger, and M. Goldszmidt. Bayesian network classifiers. Mach. Learn., 29(2-3):131-163, 1997.
-
(1997)
Mach. Learn.
, vol.29
, Issue.2-3
, pp. 131-163
-
-
Friedman, N.1
Geiger, D.2
Goldszmidt, M.3
-
10
-
-
0034133769
-
Clustering categorical data: An approach based on dynamical systems
-
D. Gibson, J. M. Kleinberg, and P. Raghavan. Clustering categorical data: An approach based on dynamical systems. VLDB Journal: Very Large Data Bases, 8(3-4):222-236, 2000.
-
(2000)
VLDB Journal: Very Large Data Bases
, vol.8
, Issue.3-4
, pp. 222-236
-
-
Gibson, D.1
Kleinberg, J.M.2
Raghavan, P.3
-
11
-
-
0002479811
-
Exploration of the power of attribute-oriented induction in data mining
-
U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors. AIII Press/MIT Press
-
J. Han and Y. Fu. Exploration of the power of attribute-oriented induction in data mining. 49n U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining. AIII Press/MIT Press, 1996.
-
(1996)
Advances in Knowledge Discovery and Data Mining
-
-
Han, J.1
Fu, Y.2
-
12
-
-
0024082469
-
Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
-
D. Haussler. Quantifying inductive bias: AI learning algorithms and Valiant's learning framework. Artificial intelligence, 36:177-221, 1988.
-
(1988)
Artificial Intelligence
, vol.36
, pp. 177-221
-
-
Haussler, D.1
-
13
-
-
0037083574
-
Automated discovery of concise predictive rules for intrusion detection
-
G. Helmer, J. S. K. Wong, V. G. Honavar, and L. Miller. Automated discovery of concise predictive rules for intrusion detection. J. Syst. Softw., 60(3):165-175, 2002.
-
(2002)
J. Syst. Softw.
, vol.60
, Issue.3
, pp. 165-175
-
-
Helmer, G.1
Wong, J.S.K.2
Honavar, V.G.3
Miller, L.4
-
14
-
-
0003471413
-
Advances in high performance knowledge representation
-
University of Maryland Institute for Advanced Computer Studies Dept. of Computer Science
-
J. Hendler, K. Stoffel, and M. Taylor. Advances in high performance knowledge representation. Technical Report CS-TR-3672, University of Maryland Institute for Advanced Computer Studies Dept. of Computer Science, 1996.
-
(1996)
Technical Report
, vol.CS-TR-3672
-
-
Hendler, J.1
Stoffel, K.2
Taylor, M.3
-
15
-
-
23044521957
-
Applications of data mining to electronic commerce
-
R. Kohavi and F. Provost. Applications of data mining to electronic commerce. Data Min. Knowl. Discov., 5(1-2):5-10, 2001.
-
(2001)
Data Min. Knowl. Discov.
, vol.5
, Issue.1-2
, pp. 5-10
-
-
Kohavi, R.1
Provost, F.2
-
17
-
-
8844261754
-
The role of prior knowledge in inductive learning
-
M. Pazzani and D. Kibler. The role of prior knowledge in inductive learning. Machine Learning, 9:54-97, 1992.
-
(1992)
Machine Learning
, vol.9
, pp. 54-97
-
-
Pazzani, M.1
Kibler, D.2
-
24
-
-
19544392472
-
A target centric ontology for intrusion detection: Using DAML+OIL to classify intrusive behaviors
-
January
-
J. L. Undercoffer, A. Joshi, T. Finin, and J. Pinkston. A Target Centric Ontology for Intrusion Detection: Using DAML+OIL to Classify Intrusive Behaviors. Knowledge Engineering Review, January 2004.
-
(2004)
Knowledge Engineering Review
-
-
Undercoffer, J.L.1
Joshi, A.2
Finin, T.3
Pinkston, J.4
-
25
-
-
0042235504
-
Automated data-driven discovery of motif-based protein function classifiers
-
X. Wang, D. Schroeder, D. Dobbs, and V. G. Honavar. Automated data-driven discovery of motif-based protein function classifiers. Inf. Sci., 155(1-2):1-18, 2003.
-
(2003)
Inf. Sci.
, vol.155
, Issue.1-2
, pp. 1-18
-
-
Wang, X.1
Schroeder, D.2
Dobbs, D.3
Honavar, V.G.4
-
27
-
-
17444429200
-
Identification of surface residues involved in protein-protein interaction - A support vector machine approach
-
A. Abraham, K. Franke, and M. Koppen, editors
-
C. Yan, D. Dobbs, and V. Honavar. Identification of surface residues involved in protein-protein interaction - a support vector machine approach. In A. Abraham, K. Franke, and M. Koppen, editors, Intelligent Systems Design and Applications (ISDA-03), pages 53-62, 2003.
-
(2003)
Intelligent Systems Design and Applications (ISDA-03)
, pp. 53-62
-
-
Yan, C.1
Dobbs, D.2
Honavar, V.3
-
29
-
-
19544364846
-
AVT-NBL: An algorithm for learning compact and accurate naive bayes classifiers from attribute value taxonomies and data
-
To appear
-
J. Zhang and V. Honavar. AVT-NBL: An algorithm for learning compact and accurate naive bayes classifiers from attribute value taxonomies and data. In International Conference on Data Mining (ICDM 2004), 2004. To appear.
-
(2004)
International Conference on Data Mining (ICDM 2004)
-
-
Zhang, J.1
Honavar, V.2
-
30
-
-
62649104314
-
Ontology-driven induction of decision trees at multiple levels of abstraction
-
J. Zhang, A. Silvescu, and V. Honavar. Ontology-driven induction of decision trees at multiple levels of abstraction. In Proceedings of Symposium on Abstraction, Reformulation, and Approximation 2002. Vol. 2371 of Lecture Notes in Artificial Intelligence : Springer-Verlag, 2002.
-
(2002)
Proceedings of Symposium on Abstraction, Reformulation, and Approximation 2002. Vol. 2371 of Lecture Notes in Artificial Intelligence: Springer-Verlag
, vol.2371
-
-
Zhang, J.1
Silvescu, A.2
Honavar, V.3
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