Properties and identification of human protein drug targets
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[1] R. Doolittle,et al. A simple method for displaying the hydropathic character of a protein. , 1982, Journal of molecular biology.
[2] T. Keller,et al. A practical view of 'druggability'. , 2006, Current opinion in chemical biology.
[3] William Frawley,et al. Knowledge Discovery in Databases , 1991 .
[4] Hsuan-Tien Lin,et al. Improving Generalization by Data Categorization , 2005, PKDD.
[5] David S. Wishart,et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..
[6] Guoli Wang,et al. PISCES: a protein sequence culling server , 2003, Bioinform..
[7] S. Brunak,et al. Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites. , 2005, Glycobiology.
[8] B. Honig,et al. On the nature of cavities on protein surfaces: Application to the identification of drug‐binding sites , 2006, Proteins.
[9] F. Lombardo,et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.
[10] Michael B. Yaffe,et al. Scansite 2.0: proteome-wide prediction of cell signaling interactions using short sequence motifs , 2003, Nucleic Acids Res..
[11] Søren Brunak,et al. Prediction of human protein function according to Gene Ontology categories , 2003, Bioinform..
[12] J. Peter-Katalinic,et al. Methods in enzymology: O-glycosylation of proteins. , 2005, Methods in enzymology.
[13] Paul Horton,et al. PROTEIN SUBCELLULAR LOCALIZATION PREDICTION WITH WOLF PSORT , 2005 .
[14] S. Brunak,et al. Improved prediction of signal peptides: SignalP 3.0. , 2004, Journal of molecular biology.
[15] Daniel R. Caffrey,et al. Structure-based maximal affinity model predicts small-molecule druggability , 2007, Nature Biotechnology.
[16] P. Hajduk,et al. Predicting protein druggability. , 2005, Drug discovery today.
[17] Geoffrey J. Barton,et al. JPred : a consensus secondary structure prediction server , 1999 .
[18] T. Speed,et al. GOstat: find statistically overrepresented Gene Ontologies within a group of genes. , 2004, Bioinformatics.
[19] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[20] Serge Batalov,et al. The promise of genomics to identify novel therapeutic targets , 2004, Expert opinion on therapeutic targets.
[21] S. Lampel,et al. The druggable genome: an update. , 2005, Drug discovery today.
[22] P. Bork,et al. Drug Target Identification Using Side-Effect Similarity , 2008, Science.
[23] N. Blom,et al. Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. , 1999, Journal of molecular biology.
[24] Peter Imming,et al. Drugs, their targets and the nature and number of drug targets , 2007, Nature Reviews Drug Discovery.
[25] A. Krogh,et al. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. , 2001, Journal of molecular biology.
[26] John C. Wootton,et al. Statistics of Local Complexity in Amino Acid Sequences and Sequence Databases , 1993, Comput. Chem..
[27] Y. Z. Chen,et al. Therapeutic Targets: Progress of Their Exploration and Investigation of Their Characteristics , 2006, Pharmacological Reviews.
[28] Albert Kriegner,et al. Characterization of the drugged human genome. , 2007, Pharmacogenomics.
[29] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[30] John P. Overington,et al. How many drug targets are there? , 2006, Nature Reviews Drug Discovery.
[31] J. Drews. Drug discovery: a historical perspective. , 2000, Science.
[32] A. Hopkins,et al. The druggable genome , 2002, Nature Reviews Drug Discovery.
[33] Paul Horton,et al. Nucleic Acids Research Advance Access published May 21, 2007 WoLF PSORT: protein localization predictor , 2007 .