Research Topics
| Predrag RadivojacSummaryAffiliation: Indiana University Country: USA Publications
Research Grants
| Collaborators
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Detail Information
Publications
Analysis of AML genes in dysregulated molecular networksEunjung Lee
Department of Bio and Brain Engineering, KAIST, Daejeon 305 701, South Korea
BMC Bioinformatics 10:S2. 2009..Recently, molecular interaction networks have been incorporated to predict disease genes, but most of those methods do not utilize invaluable disease-specific information available in mRNA expression profiles of patient samples...- Length-dependent prediction of protein intrinsic disorderKang Peng
Center for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA
BMC Bioinformatics 7:208. 2006..However, these predictors are less successful on short disordered regions (< or =30 residues). A probable cause is a length-dependent amino acid compositions and sequence properties of disordered regions... - Computational methods for identification of functional residues in protein structuresFuxiao Xin
School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA
Curr Protein Pept Sci 12:456-69. 2011..We examine four different problems in order to perform a comparison between several recently proposed methods and, finally, conclude by identifying limitations and future challenges in this field... - An integrated approach to inferring gene-disease associations in humansPredrag Radivojac
School of Informatics, Indiana University, Bloomington, Indiana 47408, USA
Proteins 72:1030-7. 2008..Availability: www.phenopred.org... - Prediction of intrinsic disorder and its use in functional proteomicsVladimir N Uversky
School of Medicine, Indiana University, Indianapolis, USA
Methods Mol Biol 408:69-92. 2007..A method is provided to utilize intrinsic disorder knowledge to gain structural and functional information related to individual proteins, protein groups, families, classes, and even entire proteomes... - Structure-based kernels for the prediction of catalytic residues and their involvement in human inherited diseaseFuxiao Xin
School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA
Bioinformatics 26:1975-82. 2010..Our analysis suggests that both mechanisms are actively involved in human inherited disease. AVAILABILITY AND IMPLEMENTATION: Source code for the structural kernel is available at www.informatics.indiana.edu/predrag/... - Combinatorial libraries of synthetic peptides as a model for shotgun proteomicsBrian C Bohrer
Department of Chemistry, Indiana University, Bloomington, Indiana 47405, USA
Anal Chem 82:6559-68. 2010..Furthermore, they are uniquely suited to delineate the physical properties that influence identification of peptides, which provides a foundation for optimizing the study of samples with less defined heterogeneity... - Intrinsic disorder and functional proteomicsPredrag Radivojac
School of Informatics, Indiana University, Bloomington, Indiana, USA
Biophys J 92:1439-56. 2007..The future of the prediction of protein disorder and the future uses of such predictions in functional proteomics comprise the last section of this article... - Influence of sequence changes and environment on intrinsically disordered proteinsAmrita Mohan
School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America
PLoS Comput Biol 5:e1000497. 2009..Our study also raises general questions regarding protein evolution and the regulation of protein structure, dynamics, and function via variations in cellular and environmental conditions... - A bayesian approach to protein inference problem in shotgun proteomicsYong Fuga Li
School of Informatics, Indiana University, Bloomington, IN 47408, USA
J Comput Biol 16:1183-93. 2009..We propose a rigorious probabilistic model for protein inference and provide practical algoritmic solutions to this problem. We used a complex synthetic protein mixture to test our method and obtained promising results... - The importance of peptide detectability for protein identification, quantification, and experiment design in MS/MS proteomicsYong Fuga Li
Department of Chemistry, School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States
J Proteome Res 9:6288-97. 2010..Finally, our study summarizes a theoretical framework for peptide/protein identification and label-free quantification... - Automated inference of molecular mechanisms of disease from amino acid substitutionsBiao Li
School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA
Bioinformatics 25:2744-50. 2009..Although these methods are useful in practice, and accurate for their intended purpose, they are not well suited for providing probabilistic estimates of the underlying disease mechanism... - Identification, analysis, and prediction of protein ubiquitination sitesPredrag Radivojac
School of Informatics, Indiana University, Bloomington, Indiana 47408, USA
Proteins 78:365-80. 2010..We show that gain and loss of predicted ubiquitination sites may likely represent a molecular mechanism behind a number of disease-associatedmutations. UbPred is available at http://www.ubpred.org... - On the accuracy and limits of peptide fragmentation spectrum predictionSujun Li
School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA
Anal Chem 83:790-6. 2011.... - From protein-disease associations to disease informaticsMehmet M Dalkilic
School of Informatics, Indiana University, Bloomington, IN 47408, USA
Front Biosci 13:3391-407. 2008..In such an approach, major data collection is yet to be done and comprehensive computational models are yet to be developed... - Testing the ortholog conjecture with comparative functional genomic data from mammalsNathan L Nehrt
School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA
PLoS Comput Biol 7:e1002073. 2011..We conclude that the most important factor in the evolution of function is not amino acid sequence, but rather the cellular context in which proteins act... - Intrinsic disorder in pathogenic and non-pathogenic microbes: discovering and analyzing the unfoldomes of early-branching eukaryotesAmrita Mohan
School of Informatics, Indiana University, Bloomington, IN 47401, USA
Mol Biosyst 4:328-40. 2008..It also provides new insights into the evolution of intrinsic disorder in the context of adapting to a parasitic lifestyle and lays the foundation for further work on the subject... - Gain and loss of phosphorylation sites in human cancerPredrag Radivojac
School of Informatics, Indiana University, 901 East Tenth Street, Bloomington, IN 47408, USA
Bioinformatics 24:i241-7. 2008.... - Fast and accurate identification of semi-tryptic peptides in shotgun proteomicsPedro Alves
School of Informatics, Bloomington, IN, USA
Bioinformatics 24:102-9. 2008..By applying this method to identification of semi-tryptic peptides, we show that a significant number of such peptides can be identified within a searching time comparable to that of tryptic peptide identification... - Uncovering protein interaction in abstracts and text using a novel linear model and word proximity networksAlaa Abi-Haidar
School of Informatics, Indiana University, Bloomington, IN 47405, USA
Genome Biol 9:S11. 2008..Our approach to the full-text subtasks (protein pair and passage identification) includes a feature expansion method based on word proximity networks... - Analysis of protein function and its prediction from amino acid sequenceWyatt T Clark
School of Informatics and Computing, Indiana University, Bloomington, Indiana 47405, USA
Proteins 79:2086-96. 2011..informatics.indiana.edu/predrag) outperforms standard methods such as transfer by global or local SID as well as GOtcha, a method that incorporates the structure of GO... - Analysis of molecular recognition features (MoRFs)Amrita Mohan
School of Informatics, Indiana University, Bloomington, IN 47408, USA
J Mol Biol 362:1043-59. 2006..The results of this study will advance the understanding of protein-protein interactions and help towards the future development of useful protein-protein binding site predictors... - Calmodulin signaling: analysis and prediction of a disorder-dependent molecular recognitionPredrag Radivojac
School of Informatics, Indiana University, Bloomington, Indiana, USA
Proteins 63:398-410. 2006..These findings add to the growing list of examples in which intrinsically disordered protein regions are indicated to provide the basis for cell signaling and regulation... - A computational approach toward label-free protein quantification using predicted peptide detectabilityHaixu Tang
School of Informatics, Indiana University, Bloomington, IN, USA
Bioinformatics 22:e481-8. 2006..Triplicate analysis of a biological sample showed that these MDIP values are consistent among the three data sets... - Intrinsic disorder is a common feature of hub proteins from four eukaryotic interactomesChad Haynes
Laboratory of Statistical Genetics, The Rockefeller University, New York, New York, USA
PLoS Comput Biol 2:e100. 2006..The results of this study demonstrate that intrinsic structural disorder is a distinctive and common characteristic of eukaryotic hub proteins, and that disorder may serve as a determinant of protein interactivity... - Two Sample Logo: a graphical representation of the differences between two sets of sequence alignmentsVladimir Vacic
Computer Science and Engineering Department, University of California Riverside, CA, USA
Bioinformatics 22:1536-7. 2006..Two Sample Logo extends WebLogo, a widely-used sequence logo generator. The source code is distributed under the MIT Open Source license agreement and is available for download free of charge... - Evaluation of features for catalytic residue prediction in novel foldsEunseog Youn
Center for Computational Biology and Bioinformatics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
Protein Sci 16:216-26. 2007..We then applied the method to 2781 coordinate files from the structural genomics target pipeline and identified both highly ranked and highly clustered groups of predicted catalytic residues... - Exploiting heterogeneous sequence properties improves prediction of protein disorderZoran Obradovic
Center for Information Science and Technology, Temple University, Philadelphia, Pennsylvania 19122, USA
Proteins 61:176-82. 2005..As the results of the CASP6 experiment showed, this new predictor has achieved the highest accuracy yet and significantly improved performance on short disordered regions, while maintaining high performance on long disordered regions... - Optimizing long intrinsic disorder predictors with protein evolutionary informationKang Peng
Center for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA
J Bioinform Comput Biol 3:35-60. 2005..6 +/- 1.3%) and VL2 (80.9 +/- 1.4%). The new disorder predictors with the corresponding datasets are freely accessible through the web server at http://www.ist.temple.edu/disprot... - Characterization of molecular recognition features, MoRFs, and their binding partnersVladimir Vacic
Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, USA
J Proteome Res 6:2351-66. 2007..Implications of these findings for the development of MoRF-partner interaction predictors are discussed. In addition, structural changes upon MoRF-to-partner complex formation were examined for several illustrative examples... - Classification and knowledge discovery in protein databasesPredrag Radivojac
Center for Information Science and Technology, Temple University, USA
J Biomed Inform 37:224-39. 2004..In our experiments, training classifiers specialized to the class distributions of each cluster resulted in a further decrease in classification error... - Protein flexibility and intrinsic disorderPredrag Radivojac
Center for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA
Protein Sci 13:71-80. 2004....
Research Grants
- Computational approaches to protein identification and quantification using MS/MSPredrag Radivojac; Fiscal Year: 2010..Such studies that might entail disease diagnosis, disease progression, or effects of treatment, will enhance understanding of diseases and hasten the development of effective treatments and cures. ..