Research Topics
Genomes and Genes | Yu Dong CaiSummaryCountry: China Publications
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Publications
A sequence-based approach for predicting protein disordered regionsTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
Protein Pept Lett 20:243-8. 2013..371 on a rigorous benchmark dataset tested by 5-fold cross-validation and 0.219 on an independent test dataset. Our results suggest that conservation and secondary structure play important roles in intrinsically disordered proteins...
Prediction of lysine ubiquitination with mRMR feature selection and analysisYudong Cai
Institute of Systems Biology, Shanghai University, Shanghai, 200444, People s Republic of China
Amino Acids 42:1387-95. 2012..These findings might provide useful insights for studying the mechanisms of ubiquitination and modulating the ubiquitination pathway, potentially leading to potential therapeutic strategies in the future...
Predicting the network of substrate-enzyme-product triads by combining compound similarity and functional domain compositionLei Chen
College of Information Engineering, Shanghai Maritime University, Shanghai, PR China
BMC Bioinformatics 11:293. 2010....- A novel sequence-based method of predicting protein DNA-binding residues, using a machine learning approachYudong Cai
Institute of System Biology, Shanghai University, Shanghai, 200244, People s Republic of China
Mol Cells 30:99-105. 2010..89%. Our method shows that the amino acid micro-environment is important for DNA binding, and that it is possible to identify the protein-DNA binding sites with it... - A unified 35-gene signature for both subtype classification and survival prediction in diffuse large B-cell lymphomasYu Dong Cai
Institute of Systems Biology, Shanghai University, Shanghai, People s Republic of China
PLoS ONE 5:e12726. 2010..Our results suggest that for some diseases, especially cancer, subtype classification may be used to predict survival, and, conversely, survival prediction features may shed light on subtype features... - Predicting subcellular localization with AdaBoost LearnerYu Huan Jin
Department of Chemistry, College of Sciences, Shanghai University, 99 Shang Da Road, Shanghai, China 200444
Protein Pept Lett 15:286-9. 2008..An online server for predicting subcellular localization of proteins based on AdaBoost classifier was available on http://chemdata.shu. edu.cn/sl12... - Support vector machine for predicting alpha-turn typesYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, China
Peptides 24:629-30. 2003.... - Support Vector Machines for predicting HIV protease cleavage sites in proteinYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, People s Republic of China
J Comput Chem 23:267-74. 2002..The principle of the Support Vector Machine method can also be applied to analyzing the specificity of other multisubsite enzymes... - Using AdaBoost for the prediction of subcellular location of prokaryotic and eukaryotic proteinsBing Niu
School of Materials Science and Engineering, Shanghai University, Shanghai, 200444, China
Mol Divers 12:41-5. 2008..An online web server for predicting subcellular location of prokaryotic and eukaryotic proteins is available at http://chemdata.shu.edu.cn/subcell/ ... - Deciphering the effects of gene deletion on yeast longevity using network and machine learning approachesTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
Biochimie 94:1017-25. 2012..Moreover, it has not escaped our notice that, after some modification, the current model can also be used to study many other phenotype prediction problems from the angle of systems biology... - Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networksTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 5:e10972. 2010..The computational method can also be used as a large-scale tool for annotating the metabolic stability for the avalanche of protein sequences generated in the post-genomic age... - Support vector machines for predicting membrane protein types by using functional domain compositionYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China
Biophys J 84:3257-63. 2003..C. Chou (2001), may become a very useful high-throughput tool in the area of bioinformatics and proteomics... - A knowledge-based method to predict the cooperative relationship between transcription factorsLingyi Lu
Key Lab of Molecular Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai, 200031, China
Mol Divers 14:815-9. 2010..The corresponding online service TFIPS (Transcription Factor Interaction Prediction System) is available on http://pcal.biosino.org/cgi-bin/TFIPS/TFIPS.pl... - Predicting protein oxidation sites with feature selection and analysis approachShen Niu
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P R China
J Biomol Struct Dyn 29:650-8. 2012..Also, the 16 optimal features obtained through this study may provide useful clues and insights for in-depth understanding the action mechanism of protein oxidation... - Using protein-protein interaction network information to predict the subcellular locations of proteins in budding yeastLe Le Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
Protein Pept Lett 19:644-51. 2012..As a user-friendly web-server, Yeast-PLoc is freely accessible at http://yeastloc.biosino.org/... - Prediction and analysis of protein hydroxyproline and hydroxylysineLe Le Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
PLoS ONE 5:e15917. 2010..Hydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites... - Protein sumoylation sites prediction based on two-stage feature selectionLin Lu
Department of Biomedical Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China
Mol Divers 14:81-6. 2010..Based on the feature selection strategy, our prediction system can not only be used for high throughput prediction of sumoylation sites but also as a tool to investigate the mechanism of sumoylation... - Predicting transcriptional activity of multiple site p53 mutants based on hybrid propertiesTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 6:e22940. 2011..Our study has provided a new and promising approach for finding functionally important sites and the relevant features for in-depth study of p53 protein and its action mechanism... - Predicting drug-target interaction networks based on functional groups and biological featuresZhisong He
CAS MPG Partner Institute of Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
PLoS ONE 5:e9603. 2010..As a complement, the in silico prediction methods can provide us with very useful information in a timely manner... - Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction networkBi Qing Li
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 7:e33393. 2012..It has not escaped our notice that the method can be applied to identify the genes of other diseases as well... - Selection of reprogramming factors of induced pluripotent stem cells based on the protein interaction network and functional profilesTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P R China
Protein Pept Lett 19:113-9. 2012..It can be used to select reprogramming factors from millions of possibilities. It is anticipated that the novel approach will become a very useful tool for both basic research and drug development... - Prediction of beta-turns with learning machinesYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, 200233 Shanghai, China
Peptides 24:665-9. 2003..1 and 97.3%, respectively. The results obtained from this study support the conclusion that the residue-coupled effect along a tetrapeptide is important for the formation of a beta-turn... - ECS: an automatic enzyme classifier based on functional domain compositionLingyi Lu
Bioinformatics Center, Key Lab of Molecular Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
Comput Biol Chem 31:226-32. 2007..Moreover, a web-based software Enzyme Classification System (ECS) for identification as well as classification of enzymes can be accessed at: http://pcal.biosino.org/... - Support vector machines for prediction of protein subcellular location by incorporating quasi-sequence-order effectYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China
J Cell Biochem 84:343-8. 2002..Furthermore, tests for correct prediction rates were undertaken with three independent testing datasets containing 2,148 proteins, 2,417 proteins, and 2,494 proteins producing values of 84, 77, and 74%, respectively... - Nearest neighbour algorithm for predicting protein subcellular location by combining functional domain composition and pseudo-amino acid compositionYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China
Biochem Biophys Res Commun 305:407-11. 2003..Very high success rates were observed, suggesting that such a hybrid approach may become a useful high-throughput tool in the area of bioinformatics and proteomics... - Support vector machines for prediction of protein domain structural classYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China
J Theor Biol 221:115-20. 2003.... - Predicting protein structural class with AdaBoost LearnerBing Niu
Department of Chemistry, College of Sciences, Shanghai University, 99 Shang Da Road, Shanghai 200436, China
Protein Pept Lett 13:489-92. 2006..Or at the very least, it will play a complementary role to many of the existing algorithms in this regard... - Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid propertiesLele Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
PLoS ONE 6:e14556. 2011..The information thus obtained would be very useful for both basic research and drug development in a timely manner... - Prediction and analysis of protein palmitoylation sitesLe Le Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
Biochimie 93:489-96. 2011..Meanwhile, the protein disorder region might also play an import role in the post-translational modification. These findings may provide useful insights for revealing the mechanisms of palmitoylation... - Prediction of protein secondary structure content by artificial neural networkYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China
J Comput Chem 24:727-31. 2003..C. Chou [J Protein Chem 1999, 18, 473] was adopted as the input. Self-consistency and independent-dataset tests were used to appraise the performance of the neural network. Results of both tests indicated high performance of the method... - Inter- and intra-chain disulfide bond prediction based on optimal feature selectionShen Niu
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P R China
Protein Pept Lett 20:324-35. 2013.... - Identify catalytic triads of serine hydrolases by support vector machinesYu Dong Cai
Shanghai Research Center of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China
J Theor Biol 228:551-7. 2004..The success rate by jackknife test for the 139 serine hydrolases was 85%, implying that the method is quite promising and may become a useful tool in structural bioinformatics... - Prediction of protein-protein interaction sites by random forest algorithm with mRMR and IFSBi Qing Li
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 7:e43927. 2012..It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction... - Classification of transcription factors using protein primary structureXin Yi Yang
CAS MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
Protein Pept Lett 17:899-908. 2010..A free online classifier is available at http://app3.biosino.org/132dvc/tf/... - An approach to predict transcription factor DNA binding site specificity based upon gene and transcription factor functional categorizationZiliang Qian
CAS MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 19 Yuquan Road, Beijing 100039, China
Bioinformatics 23:2449-54. 2007..We noted that the generally acknowledged information of functional annotations of TFs as well as that of their target genes should provide useful hints in determining TF DNA binding preferences... - Support vector machines for prediction of protein signal sequences and their cleavage sitesYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China
Peptides 24:159-61. 2003..It has not escaped our attention that the new method may also serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the ZIP code protein-sorting system in cells... - Crosstissue coexpression network of agingTao Huang
Department of Ophthalmology, Yangpu District Central Hospital, Shanghai, People s Republic of China
OMICS 15:665-71. 2011..By bridging gene-level and tissue-level research, this study could help identify targets for attenuation of critical aging-related genes, pathways, or networks for antiaging intervention... - Prediction of protein domain with mRMR feature selection and analysisBi Qing Li
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
PLoS ONE 7:e39308. 2012..Finally, it has not escaped our notice that the current approach can also be utilized to study protein signal peptides, B-cell epitopes, HIV protease cleavage sites, among many other important topics in protein science and biomedicine... - Analysis of metabolic pathway using hybrid propertiesLei Chen
College of Information Engineering, Shanghai Maritime University, Shanghai, People s Republic of China
Protein Pept Lett 19:99-107. 2012..26%. It is anticipated that this novel approach and encouraging result may give meaningful illumination to investigate this important topic... - Prediction of deleterious non-synonymous SNPs based on protein interaction network and hybrid propertiesTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 5:e11900. 2010..Our results suggest that the protein interaction context could provide important clues to help better illustrate SAP's functional association. This research will facilitate the post genome-wide association studies... - Application of SVM to predict membrane protein typesYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai 200233, China
J Theor Biol 226:373-6. 2004..12 (1999) 107) and SVM, if effectively complemented with each other, will become a powerful tool for predicting membrane protein types and the other protein attributes as well... - Identification of retinoblastoma related genes with shortest path in a protein-protein interaction networkBi Qing Li
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People s Republic of China
Biochimie 94:1910-7. 2012..This study shows promising results and proves the efficiency of the proposed methods... - Predicting N-terminal acetylation based on feature selection methodYu Dong Cai
Department of Combinatorics and Geometry, CAS MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, People s Republic of China
Biochem Biophys Res Commun 372:862-5. 2008..The software is available upon request... - Support vector machines for predicting rRNA-, RNA-, and DNA-binding proteins from amino acid sequenceYu Dong Cai
Shanghai Research Center of Biotechnology, Chinese Academy of Sciences, China
Biochim Biophys Acta 1648:127-33. 2003..The RNA- and DNA-binding SVMs demonstrate more diverse accuracy, ranging from approximately 76% to approximately 97%. Analysis of the test results suggests the directions of improving the SVMs... - Prediction and analysis of protein methylarginine and methyllysine based on Multisequence featuresLe Le Hu
Institute of Systems Biology, Shanghai University, Shanghai 200444, China Department of Chemistry, College of Sciences, Shanghai University, China
Biopolymers 95:763-71. 2011..These findings may provide valuable information for exploiting the mechanisms of methylation. Our method may serve as a useful tool for biologists to find the potential methylated sites of proteins... - Predicting subcellular location of proteins using integrated-algorithm methodYu Dong Cai
Institute of System Biology, Shanghai University, 99 Shangda Road, 200244 Shanghai, China
Mol Divers 14:551-8. 2010..It can achieve correct rate of 77.83 and 80.56% for the training set and test set, respectively, which is better than all of the 60 algorithms collected in Weka. This predicting software is available upon request... - Prediction of body fluids where proteins are secreted into based on protein interaction networkLe Le Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
PLoS ONE 6:e22989. 2011..These encouraging results indicate that the network-based prediction method is quite promising. It is anticipated that the method will benefit the relevant areas for both basic research and drug development... - Computational analysis of HIV-1 resistance based on gene expression profiles and the virus-host interaction networkTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 6:e17291. 2011..These proteins may be useful targets for AIDS prevention or therapy, as intervention in these pathways could disrupt communication with virus-targeted proteins and HIV-1 infection... - Predicting protein phenotypes based on protein-protein interaction networkLele Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
PLoS ONE 6:e17668. 2011..Besides the high-through phenotype assays, the computational methods are alternative ways to identify the phenotypes of proteins... - HIV-1 protease cleavage site prediction based on amino acid propertyBing Niu
School of Materials Science and Engineering, Shanghai University, 149 Yan Chang Road, Shanghai 200072, People s Republic of China
J Comput Chem 30:33-9. 2009..3% for independent-set test. It is expected that our feature selection scheme can be referred to as a useful assistant technique for finding effective inhibitors of HIV protease, especially for the scientists in this field... - Predict and analyze S-nitrosylation modification sites with the mRMR and IFS approachesBi Qing Li
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Science, Chinese Academy of Science, Shanghai 200031, PR China
J Proteomics 75:1654-65. 2012.... - Cooperativity among short amyloid stretches in long amyloidogenic sequencesLele Hu
Institute of Systems Biology, Shanghai University, Shanghai, People s Republic of China
PLoS ONE 7:e39369. 2012..Our study revealed that genome-wide amyloid segments are not only dependent on short high propensity stretches, but also on nearby residues... - Predicting membrane protein types with bragging learnerBing Niu
School of Materials Science and Engineering, Shanghai University, Shanghai, People s Republic of China
Protein Pept Lett 15:590-4. 2008..An online membrane protein type prediction web server developed in our lab is available at http://chemdata.shu.edu.cn/protein/protein.jsp... - Classification and analysis of regulatory pathways using graph property, biochemical and physicochemical property, and functional propertyTao Huang
Institute of Systems Biology, Shanghai University, Shanghai, People s Republic of China
PLoS ONE 6:e25297. 2011..It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area... - Prediction of compounds' biological function (metabolic pathways) based on functional group compositionYu Dong Cai
CAS MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
Mol Divers 12:131-7. 2008..The overall prediction rate reached 73.3%, indicating that functional group composition of compounds was really related to their biological metabolic functions... - Prediction of pharmacological and xenobiotic responses to drugs based on time course gene expression profilesTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 4:e8126. 2009..9%. Our method can be used for pharmacological and xenobiotic responses prediction of new compounds and accelerate drug development... - Prediction of protein cleavage site with feature selection by random forestBi Qing Li
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences Chinese Academy of Sciences, Shanghai, PR China
PLoS ONE 7:e45854. 2012..It is shown that our method makes much more reliable predictions in terms of the overall prediction accuracy. In addition, this predictor allows the use of a wide range of proteinases... - Predicting Anatomical Therapeutic Chemical (ATC) classification of drugs by integrating chemical-chemical interactions and similaritiesLei Chen
College of Information Engineering, Shanghai Maritime University, Shanghai, China
PLoS ONE 7:e35254. 2012.... - Predicting biological functions of compounds based on chemical-chemical interactionsLe Le Hu
Institute of Systems Biology, Shanghai University, Shanghai, China
PLoS ONE 6:e29491. 2011.... - Analysis and prediction of translation rate based on sequence and functional features of the mRNATao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 6:e16036. 2011..Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale... - Analysis of protein pathway networks using hybrid propertiesLei Chen
College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
Molecules 15:8177-92. 2010..88%. It is anticipated that, this novel approach and encouraging result, although preliminary yet, may stimulate extensive investigations into this important topic... - Using compound similarity and functional domain composition for prediction of drug-target interaction networksLei Chen
College of Information Engineering, Shanghai Maritime University, China
Med Chem 6:388-95. 2010..23%, 94.74%, 97.80%, and 97.51%, respectively, indicating that compound similarity and functional domain composition are very effective to predict drug-target interaction networks... - Prediction of protein-protein interactions based on feature selection and data balancingLiang Liu
Department of Chemistry, College of Sciences, Shanghai University, Shanghai, People s Republic of China
Protein Pept Lett 20:336-45. 2013..8369 with sensitivity of 0.7356. The predictor, developed by this research for the prediction of the fruit fly PPI-nesses, is available for public use at http://chemdata.shu.edu.cn/ppip... - Prediction of antimicrobial peptides based on sequence alignment and feature selection methodsPing Wang
Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
PLoS ONE 6:e18476. 2011..For the convenience of most experimental scientists who want to use the prediction method without the interest to follow the mathematical details, a user-friendly web-server is provided at http://amp.biosino.org/... - Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinomaTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 7:e34460. 2012..It may also provide useful insights for in-depth study of the biological mechanisms of HCV-induced cirrhosis and hepatocellular carcinoma... - Dysfunctions associated with methylation, microRNA expression and gene expression in lung cancerTao Huang
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People s Republic of China
PLoS ONE 7:e43441. 2012..Our results provide a systematic view of the functional alterations during tumorigenesis that may help to elucidate the mechanisms of lung cancer and lead to improved treatments for patients... - Support vector machines for predicting the specificity of GalNAc-transferaseYu Dong Cai
Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, 200233, Shanghai, China
Peptides 23:205-8. 2002..9%, respectively. Furthermore, the prediction of the independent testing dataset (30 oligopeptides) was tested, the rate reaches 76.67%...