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Items: 18


The best models of metabolism.

Voit EO.

Wiley Interdiscip Rev Syst Biol Med. 2017 Nov;9(6). doi: 10.1002/wsbm.1391. Epub 2017 May 19. Review.


Implementation and comparison of kernel-based learning methods to predict metabolic networks.

Roche-Lima A.

Netw Model Anal Health Inform Bioinform. 2016;5:26. Epub 2016 Jul 15.


The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems.

Reafee W, Salim N, Khan A.

PLoS One. 2016 May 6;11(5):e0154848. doi: 10.1371/journal.pone.0154848. eCollection 2016.


Systematically Prioritizing Functional Differentially Methylated Regions (fDMRs) by Integrating Multi-omics Data in Colorectal Cancer.

Fan H, Zhao H, Pang L, Liu L, Zhang G, Yu F, Liu T, Xu C, Xiao Y, Li X.

Sci Rep. 2015 Aug 4;5:12789. doi: 10.1038/srep12789.


Classifying pairs with trees for supervised biological network inference.

Schrynemackers M, Wehenkel L, Babu MM, Geurts P.

Mol Biosyst. 2015 Aug;11(8):2116-25. doi: 10.1039/c5mb00174a.


Metabolic network prediction through pairwise rational kernels.

Roche-Lima A, Domaratzki M, Fristensky B.

BMC Bioinformatics. 2014 Sep 26;15:318. doi: 10.1186/1471-2105-15-318.


On protocols and measures for the validation of supervised methods for the inference of biological networks.

Schrynemackers M, Küffner R, Geurts P.

Front Genet. 2013 Dec 3;4:262. doi: 10.3389/fgene.2013.00262. Review.


A negative selection heuristic to predict new transcriptional targets.

Cerulo L, Paduano V, Zoppoli P, Ceccarelli M.

BMC Bioinformatics. 2013;14 Suppl 1:S3. doi: 10.1186/1471-2105-14-S1-S3. Epub 2013 Jan 14.


An efficient algorithm for de novo predictions of biochemical pathways between chemical compounds.

Nakamura M, Hachiya T, Saito Y, Sato K, Sakakibara Y.

BMC Bioinformatics. 2012;13 Suppl 17:S8. doi: 10.1186/1471-2105-13-S17-S8. Epub 2012 Dec 13.


GENIES: gene network inference engine based on supervised analysis.

Kotera M, Yamanishi Y, Moriya Y, Kanehisa M, Goto S.

Nucleic Acids Res. 2012 Jul;40(Web Server issue):W162-7. doi: 10.1093/nar/gks459. Epub 2012 May 18.


Discovering novel subsystems using comparative genomics.

Ferrer L, Shearer AG, Karp PD.

Bioinformatics. 2011 Sep 15;27(18):2478-85. doi: 10.1093/bioinformatics/btr428. Epub 2011 Jul 19.


Non-homologous isofunctional enzymes: a systematic analysis of alternative solutions in enzyme evolution.

Omelchenko MV, Galperin MY, Wolf YI, Koonin EV.

Biol Direct. 2010 Apr 30;5:31. doi: 10.1186/1745-6150-5-31.


Machine learning methods for metabolic pathway prediction.

Dale JM, Popescu L, Karp PD.

BMC Bioinformatics. 2010 Jan 8;11:15. doi: 10.1186/1471-2105-11-15.


Computational Systems Bioinformatics and Bioimaging for Pathway Analysis and Drug Screening.

Zhou X, Wong ST.

Proc IEEE Inst Electr Electron Eng. 2008 Aug 1;96(8):1310-1331.


Training set expansion: an approach to improving the reconstruction of biological networks from limited and uneven reliable interactions.

Yip KY, Gerstein M.

Bioinformatics. 2009 Jan 15;25(2):243-50. doi: 10.1093/bioinformatics/btn602. Epub 2008 Nov 17.


Inferring biological networks with output kernel trees.

Geurts P, Touleimat N, Dutreix M, d'Alché-Buc F.

BMC Bioinformatics. 2007 May 3;8 Suppl 2:S4.


A network perspective on the topological importance of enzymes and their phylogenetic conservation.

Liu WC, Lin WH, Davis AJ, Jordán F, Yang HT, Hwang MJ.

BMC Bioinformatics. 2007 Apr 11;8:121.


Identifying metabolic enzymes with multiple types of association evidence.

Kharchenko P, Chen L, Freund Y, Vitkup D, Church GM.

BMC Bioinformatics. 2006 Mar 29;7:177.

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