-
1
-
-
0034069495
-
Gene ontology: Tool for the unification of biology. The gene ontology consortium
-
Ashburner, M., et al.: Gene ontology: tool for the unification of biology. The gene ontology consortium. Nature Genetics 25, 25-29 (2000)
-
(2000)
Nature Genetics
, vol.25
, pp. 25-29
-
-
Ashburner, M.1
-
2
-
-
77956371081
-
Reaction kernels - structured output prediction approaches for novel enzyme function
-
Astikainen, K., Pitkänen, E., Rousu, J., Holm, L., Szedmák, S.: Reaction kernels - structured output prediction approaches for novel enzyme function. Bioinformatics, 48-55 (2010)
-
(2010)
Bioinformatics
, pp. 48-55
-
-
Astikainen, K.1
Pitkänen, E.2
Rousu, J.3
Holm, L.4
Szedmák, S.5
-
3
-
-
33645323768
-
Hierarchical multi-label prediction of gene function
-
Barutcuoglu, Z., Schapire, R.E., Troyanskaya, O.G.: Hierarchical multi-label prediction of gene function. Bioinformatics 22(7), 830-836 (2006)
-
(2006)
Bioinformatics
, vol.22
, Issue.7
, pp. 830-836
-
-
Barutcuoglu, Z.1
Schapire, R.E.2
Troyanskaya, O.G.3
-
5
-
-
80053440655
-
Multilabel classification on tree- and dag-structured hierarchies
-
Getoor, L., Scheffer, T. (eds.) Omnipress
-
Bi, W., Kwok, J.T.: Multilabel classification on tree- and dag-structured hierarchies. In: Getoor, L., Scheffer, T. (eds.) ICML, pp. 17-24. Omnipress (2011)
-
(2011)
ICML
, pp. 17-24
-
-
Bi, W.1
Kwok, J.T.2
-
7
-
-
62449263911
-
Hierarchical text categorization in a transductive setting
-
Ceci, M.: Hierarchical text categorization in a transductive setting. In: ICDM Workshops, pp. 184-191 (2008)
-
(2008)
ICDM Workshops
, pp. 184-191
-
-
Ceci, M.1
-
8
-
-
33846979476
-
Classifying web documents in a hierarchy of categories: A comprehensive study
-
Ceci, M., Malerba, D.: Classifying web documents in a hierarchy of categories: a comprehensive study. J. Intell. Inf. Syst. 28(1), 37-78 (2007)
-
(2007)
J. Intell. Inf. Syst.
, vol.28
, Issue.1
, pp. 37-78
-
-
Ceci, M.1
Malerba, D.2
-
9
-
-
84863574182
-
A genetic algorithm for hierarchical multi-label classification
-
ACM
-
Cerri, R., Barros, R.C., de Carvalho, A.C.P.L.F.: A genetic algorithm for hierarchical multi-label classification. In: Proc. of the 27th Annual ACM Symposium on Applied Computing, SAC 2012, pp. 250-255. ACM (2012)
-
(2012)
Proc. of the 27th Annual ACM Symposium on Applied Computing, SAC 2012
, pp. 250-255
-
-
Cerri, R.1
Barros, R.C.2
De Carvalho, A.C.P.L.F.3
-
10
-
-
29644434908
-
Incremental algorithms for hierarchical classification
-
Cesa-Bianchi, N., Gentile, C., Zaniboni, L.: Incremental algorithms for hierarchical classification. J. Mach. Learn. Res. 7, 31-54 (2006)
-
(2006)
J. Mach. Learn. Res.
, vol.7
, pp. 31-54
-
-
Cesa-Bianchi, N.1
Gentile, C.2
Zaniboni, L.3
-
12
-
-
0036580169
-
Protein interactions
-
Deane, C.M., Salwiński, Ł., Xenarios, I., Eisenberg, D.: Protein interactions. Molecular & Cellular Proteomics: MCP 1(5), 349-356 (2002)
-
(2002)
Molecular & Cellular Proteomics: MCP
, vol.1
, Issue.5
, pp. 349-356
-
-
Deane, C.M.1
Salwiński, Ł.2
Xenarios, I.3
Eisenberg, D.4
-
13
-
-
0003309977
-
Network Autocorrelation Models: Problems and Prospects
-
Ann Arbor Institute of Mathematical Geography
-
Doreian, P.: Network Autocorrelation Models: Problems and Prospects. In: Spatial Statistics: Past, Present, and Future. Monograph, vol. 12. Ann Arbor Institute of Mathematical Geography (1990)
-
(1990)
Spatial Statistics: Past, Present, and Future. Monograph
, vol.12
-
-
Doreian, P.1
-
14
-
-
65449133627
-
Using ghost edges for classification in sparsely labeled networks
-
Gallagher, B., Tong, H., Eliassi-Rad, T., Faloutsos, C.: Using ghost edges for classification in sparsely labeled networks. In: Proc. 14th ACM SIGKDD Intl. Conf. Knowledge Discovery and Data Mining, pp. 256-264 (2008)
-
(2008)
Proc. 14th ACM SIGKDD Intl. Conf. Knowledge Discovery and Data Mining
, pp. 256-264
-
-
Gallagher, B.1
Tong, H.2
Eliassi-Rad, T.3
Faloutsos, C.4
-
15
-
-
1942450651
-
Linkage and autocorrelation cause feature selection bias in relational learning
-
Morgan Kaufmann
-
Jensen, D., Neville, J.: Linkage and autocorrelation cause feature selection bias in relational learning. In: Proc. 9th Intl. Conf. on Machine Learning, pp. 259-266. Morgan Kaufmann (2002)
-
(2002)
Proc. 9th Intl. Conf. on Machine Learning
, pp. 259-266
-
-
Jensen, D.1
Neville, J.2
-
16
-
-
12244297396
-
Why collective inference improves relational classification
-
Jensen, D., Neville, J., Gallagher, B.: Why collective inference improves relational classification. In: Proc. 10th Intl. Conf. on Knowledge Discovery and Data Mining, pp. 593-598 (2004)
-
(2004)
Proc. 10th Intl. Conf. on Knowledge Discovery and Data Mining
, pp. 593-598
-
-
Jensen, D.1
Neville, J.2
Gallagher, B.3
-
17
-
-
51749110896
-
Integration of relational and hierarchical network information for protein function prediction
-
Jiang, X., Nariai, N., Steffen, M., Kasif, S., Kolaczyk, E.: Integration of relational and hierarchical network information for protein function prediction. BMC Bioinformatics 9(1) (2008)
-
(2008)
BMC Bioinformatics
, vol.9
, Issue.1
-
-
Jiang, X.1
Nariai, N.2
Steffen, M.3
Kasif, S.4
Kolaczyk, E.5
-
18
-
-
84873576763
-
Multi-label collective classification
-
SIAM/Omnipress
-
Kong, X., Shi, X., Yu, P.S.: Multi-label collective classification. In: SDM, pp. 618-629. SIAM/Omnipress (2011)
-
(2011)
SDM
, pp. 618-629
-
-
Kong, X.1
Shi, X.2
Yu, P.S.3
-
19
-
-
34249102504
-
Classification in networked data: A toolkit and a univariate case study
-
Macskassy, S., Provost, F.: Classification in networked data: a toolkit and a univariate case study. Machine Learning 8, 935-983 (2007)
-
(2007)
Machine Learning
, vol.8
, pp. 935-983
-
-
Macskassy, S.1
Provost, F.2
-
20
-
-
36348987716
-
Improving learning in networked data by combining explicit and mined links
-
Macskassy, S.A.: Improving learning in networked data by combining explicit and mined links. In: Proc. 22nd Intl. Conf. on Artificial Intelligence, pp. 590-595 (2007)
-
(2007)
Proc. 22nd Intl. Conf. on Artificial Intelligence
, pp. 590-595
-
-
Macskassy, S.A.1
-
21
-
-
0032893083
-
Mips: A database for protein sequences and complete genomes
-
Mewes, H.W., Heumann, K., Kaps, A., Mayer, K., Pfeiffer, F., Stocker, S., Frishman, D.: Mips: A database for protein sequences and complete genomes. Nucl. Acids Res. 27, 44-48 (1999)
-
(1999)
Nucl. Acids Res.
, vol.27
, pp. 44-48
-
-
Mewes, H.W.1
Heumann, K.2
Kaps, A.3
Mayer, K.4
Pfeiffer, F.5
Stocker, S.6
Frishman, D.7
-
23
-
-
84864539829
-
Predicting the functions of proteins in protein-protein interaction networks from global information
-
Rahmani, H., Blockeel, H., Bender, A.: Predicting the functions of proteins in protein-protein interaction networks from global information. Journal of Machine Learning Research 8, 82-97 (2010)
-
(2010)
Journal of Machine Learning Research
, vol.8
, pp. 82-97
-
-
Rahmani, H.1
Blockeel, H.2
Bender, A.3
-
24
-
-
77952043595
-
An experimental comparison of hierarchical bayes and true path rule ensembles for protein function prediction
-
El Gayar, N., Kittler, J., Roli, F. (eds.) MCS 2010. Springer, Heidelberg
-
Re, M., Valentini, G.: An experimental comparison of hierarchical bayes and true path rule ensembles for protein function prediction. In: El Gayar, N., Kittler, J., Roli, F. (eds.) MCS 2010. LNCS, vol. 5997, pp. 294-303. Springer, Heidelberg (2010)
-
(2010)
LNCS
, vol.5997
, pp. 294-303
-
-
Re, M.1
Valentini, G.2
-
25
-
-
33745768424
-
Kernel-based learning of hierarchical multilabel classification models
-
Rousu, J., Saunders, C., Szedmak, S., Shawe-Taylor, J.: Kernel-based learning of hierarchical multilabel classification models. J. Mach. Learn. Res. 7, 1601-1626 (2006)
-
(2006)
J. Mach. Learn. Res.
, vol.7
, pp. 1601-1626
-
-
Rousu, J.1
Saunders, C.2
Szedmak, S.3
Shawe-Taylor, J.4
-
26
-
-
9144257282
-
The funcat, a functional annotation scheme for systematic classification of proteins from whole genomes
-
Ruepp, et al.: The funcat, a functional annotation scheme for systematic classification of proteins from whole genomes. Nucleic Acids Research 32(18), 5539-5545 (2004)
-
(2004)
Nucleic Acids Research
, vol.32
, Issue.18
, pp. 5539-5545
-
-
Ruepp1
-
27
-
-
53749083869
-
Collective classification in network data
-
Sen, P., Namata, G., Bilgic, M., Getoor, L., Gallagher, B., Eliassi-Rad, T.: Collective classification in network data. AI Magazine 3, 93-106 (2008)
-
(2008)
AI Magazine
, vol.3
, pp. 93-106
-
-
Sen, P.1
Namata, G.2
Bilgic, M.3
Getoor, L.4
Gallagher, B.5
Eliassi-Rad, T.6
-
28
-
-
79961177418
-
Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science
-
Steinhaeuser, K., Chawla, N.V., Ganguly, A.R.: Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science. Statistical Analysis and Data Mining 4(5), 497-511 (2011)
-
(2011)
Statistical Analysis and Data Mining
, vol.4
, Issue.5
, pp. 497-511
-
-
Steinhaeuser, K.1
Chawla, N.V.2
Ganguly, A.R.3
-
29
-
-
84864558206
-
Network regression with predictive clustering trees
-
Stojanova, D., Ceci, M., Appice, A., Džeroski, S.: Network regression with predictive clustering trees. Data Mining and Knowledge Discovery 14 (2012)
-
(2012)
Data Mining and Knowledge Discovery
, vol.14
-
-
Stojanova, D.1
Ceci, M.2
Appice, A.3
Džeroski, S.4
-
31
-
-
52949141834
-
Decision trees for hierarchical multi-label classification
-
Vens, C., Struyf, J., Schietgat, L., Džeroski, S., Blockeel, H.: Decision trees for hierarchical multi-label classification. Machine Learning 73(2), 185-214 (2008)
-
(2008)
Machine Learning
, vol.73
, Issue.2
, pp. 185-214
-
-
Vens, C.1
Struyf, J.2
Schietgat, L.3
Džeroski, S.4
Blockeel, H.5
-
32
-
-
0037161731
-
Comparative assessment of large-scale data sets of protein-protein interactions
-
von Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S.G., Fields, S., Bork, P.: Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417(6887), 399-403 (2002)
-
(2002)
Nature
, vol.417
, Issue.6887
, pp. 399-403
-
-
Von Mering, C.1
Krause, R.2
Snel, B.3
Cornell, M.4
Oliver, S.G.5
Fields, S.6
Bork, P.7
|