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119. J. Hou, T. Wu, R. Cao, J. Cheng. Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13. Proteins, accepted, 2019.


118. H. Song, M. Chen, C. Chen, J. Cui, C.E. Johnson, J. Cheng, X. Wang, R.H. Swerdlow, R. G. DePalma, W. Xia, Z Gu. Proteomic Analysis and Biochemical Correlates of Mitochondrial Dysfunction following Low-Intensity Primary Blast Exposure. Journal of Neurotrauma, in press.


117. C. Olaya, B. Adhikari, G. Raikhy, J. Cheng, and H.R. Pappu. In silico localization of Tospoviridae family-wide conserved residues in nucleocapsid and silencing suppressor proteins of Tomato spotted wilt virus. Virology Journal, in press.


116. Keasar C, McGuffin LJ, Wallner B, Chopra G, Adhikari B, Bhattacharya D, Blake L, Bortot LO, Cao R, Dhanasekaran BK, Dimas I, Faccioli RA, Faraggi E, Ganzynkowicz R, Ghosh S, Ghosh S, Giełdoń A, Golon L, He Y, Heo L, Hou J, Khan M, Khatib F, Khoury GA, Kieslich C, Kim DE, Krupa P, Lee GR, Li H, Li J, Lipska A, Liwo A, Maghrabi AHA, Mirdita M, Mirzaei S, Mozolewska MA, Onel M, Ovchinnikov S, Shah A, Shah U, Sidi T, Sieradzan AK, Ślusarz M, Ślusarz R, Smadbeck J, Tamamis P, Trieber N, Wirecki T, Yin Y, Zhang Y, Bacardit J, Baranowski M, Chapman N, Cooper S, Defelicibus A, Flatten J, Koepnick B, Popović Z, Zaborowski B, Baker D, Cheng J, Czaplewski C, Delbem ACB, Floudas C, Kloczkowski A, Ołdziej S, Levitt M, Scheraga H, Seok C, Söding J, Vishveshwara S, Xu D; Foldit Players consortium, Crivelli SN. An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12. Scientific Reports, 8(1):9939, 2018.


115. B. Adhikari, J. Cheng. CONFOLD2: Improved contact-driven ab initio protein structure modeling. BMC Bioinformatics, accepted, 2017. [at BMC Bioinformatics]


114. B. Adhikari, J. Hou, J. Cheng. DNCON2: Improved protein contact prediction using two-level deep convolutional neural networks. Bioinformatics, accepted.[at Bioinformatics]


113. J. Hou, B. Adhikari, J. Cheng. DeepSF: deep convolutional neural network for mapping protein sequences to folds. Bioinformatics, accepted.[at Bioinformatics]


112. O. Oluwadare, J. Cheng. ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data. BMC Genomics. 18:480, 2017. [at BMC Bioinformatics]


111. X. Rui, J. Wen, A. Quitadamo, J. Cheng, and X. Shi. A deep auto-encoder model for gene expression prediction. BMC Genomics. 18(S9):845, 2017. [at BMC Genomics]


110. B. Adhikari, J. Hou, J. Cheng. Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning. Proteins, accepted, 2017. [at Proteins]


109. H. Li, J. Hou, B. Adhikari, Q. Lyu, J. Cheng. Deep Learning Methods for Protein Torsion Angle Prediction.BMC Bioinformatics. 18:417, 2017. [at BMC Bioinformatics]


108. J. Lingyan, Y. Wan, J. C. Anderson, J. Hou, S.M. Soliman, J. Cheng, S.C. Peck. Genetic Dissection of Arabidopsis MAP Kinase Phosphatase 1 (AtMKP1)-dependent PAMP-induced transcription pathways. Journal of Experimental Botany. Accepted, 2017. [at Journal of Experimental Botany]


107. B. Adhikari, J. Cheng. Improved Protein Structure Reconstruction Using Secondary Structures, Contacts at Higher Distance Thresholds, and Non-Contacts. BMC Bioinformatics. 18(1):380, 2017.[at BMC Bioinformatics]


106. Cao, Z. Zhong, J. Cheng. A Protein Function Prediction Server by Integrating Multiple Sources.International Journal of Computational Intelligence in Bioinformatics and Systems Biology, accepted, 2017.


105. R. Cao, D. Bhattacharya, J. Hou, J. Cheng. DeepQA: Improving the Estimation of Single Protein Model Quality with Deep Belief Networks. BMC Bioinformatics, accepted, 2016. [at BMC Bioinformatics]


104. B. Adhikari, J. Nowotny, D. Bhattacharya, J. Hou, J. Cheng. ConEVA: a Toolbox fr Comprehensive Assessment of Protein Contacts. BMC Bioinformatics, accepted, 2016. [at BMC Bioinformatics]


103. H. Li, Q. Lyu, J. Cheng. A Template-Based Protein Structure Reconstruction Method Using Deep Autoencoder Learning. Journal of Proteomics and Bioinformatics, accepted, 2016. [PDF]


102. T. Trieu, J. Cheng. 3D Genome Structure Modeling by Lorentzian Objective Function. Nucleic Acids Research, accepted, 2016.[at NAR]


101. R. Cao, B. Adhikari, D. Bhattacharya, M. Sun, J. Hou, J. Cheng. QAcon: Single Model Quality Assessment Using Protein Structural and Contact Information with Machine Learning Techniques. Bioinformatics, accepted, 2016. [at PubMed]


100. H. Song, Y. Lu, Z. Qu, V.V. Mossine, M.B. Martin, J. Hou, J. Cui, B.A. Peculis, T.P. Mawhinney, J. Cheng, C.M. Greenlief, K. Fritsche, F.J. Schmidt, R.B. Walter, D.B. Lubahn, G.Y. Sun, Z. Gu. Effects of aged garlic extract and FruArg on gene expression and signaling pathways in lipopolysaccharide-activated microglial cells. Scientific Reports. 6:35323, 2016. [at Scientific Reports]


99. B. Adhikari, T. Tuan, J. Cheng. Chromosome3D: Reconstructing Three-Dimensional Chromosomal Structures from Hi-C Interaction Frequency Data using Distance Geometry Simulated Annealing. BMC Genomics, 17:886, 2016. [at BMC Genomics]


98. Jiang Y, Oron TR, Clark WT, Bankapur AR, D'Andrea D, Lepore R, Funk CS, Kahanda I, Verspoor KM, Ben-Hur A, Koo da CE, Penfold-Brown D, Shasha D, Youngs N, Bonneau R, Lin A, Sahraeian SM, Martelli PL, Profiti G, Casadio R, Cao R, Zhong Z, Cheng J, Altenhoff A, Skunca N, Dessimoz C, Dogan T, Hakala K, Kaewphan S, Mehryary F, Salakoski T, Ginter F, Fang H, Smithers B, Oates M, Gough J, Törönen P, Koskinen P, Holm L, Chen CT, Hsu WL, Bryson K, Cozzetto D, Minneci F, Jones DT, Chapman S, Bkc D, Khan IK, Kihara D, Ofer D, Rappoport N, Stern A, Cibrian-Uhalte E, Denny P, Foulger RE, Hieta R, Legge D, Lovering RC, Magrane M, Melidoni AN, Mutowo-Meullenet P, Pichler K, Shypitsyna A, Li B, Zakeri P, ElShal S, Tranchevent LC, Das S, Dawson NL, Lee D, Lees JG, Sillitoe I, Bhat P, Nepusz T, Romero AE, Sasidharan R, Yang H, Paccanaro A, Gillis J, Sedeño-Cortés AE, Pavlidis P, Feng S, Cejuela JM, Goldberg T, Hamp T, Richter L, Salamov A, Gabaldon T, Marcet-Houben M, Supek F, Gong Q, Ning W, Zhou Y, Tian W, Falda M, Fontana P, Lavezzo E, Toppo S, Ferrari C, Giollo M, Piovesan D, Tosatto SC, Del Pozo A, Fernández JM, Maietta P, Valencia A, Tress ML, Benso A, Di Carlo S, Politano G, Savino A, Rehman HU, Re M, Mesiti M, Valentini G, Bargsten JW, van Dijk AD, Gemovic B, Glisic S, Perovic V, Veljkovic V, Veljkovic N, Almeida-E-Silva DC, Vencio RZ, Sharan M, Vogel J, Kansakar L, Zhang S, Vucetic S, Wang Z, Sternberg MJ, Wass MN, Huntley RP, Martin MJ, O'Donovan C, Robinson PN, Moreau Y, Tramontano A, Babbitt PC, Brenner SE, Linial M, Orengo CA, Rost B, Greene CS, Mooney SD, Friedberg I, Radivojac P. An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biology. 2016. [at Genome Biology]


97. D. Bhattacharya, R. Cao, J. Cheng. UniCon3D: de novo protein structure prediction using united-residue conformational search via stepwise, probabilistic sampling. Bioinformatics, accepted, 2016. [at Bioinformatics]


96. W.R. Folk, A. Smith, H. Song, D. Chuang, J. Cheng, Z. Gu, G. Sun. Does concurrent use of some botanicals interfere with treatment of tuberculosis? Neuromolecular Med., accepted, 2016. [at NeuroMolecular Medicine]


95. B. Gandolfi, S. Alamri, W.G. Darby, B. Adhikari, J.C. Lattimer, R. Malik, C.M. Wade, L.A. Lyons, J. Cheng, J.F. Bateman, P. McIntyre, S.R. Lamande, B. Haase. A novel variant in CAMH is associated with blood type AB in Ragdoll cats. PLoS ONE, accepted, 2016. [at Plos ONE]


94. J. Li, J. Cheng. A Stochastic Point Cloud Sampling Method for Multi-Template Protein Comparative Modeling. Scientific Reports, accepted, 2016. [at PubMed]


93. D. Bhattacharya, J. Nowotny, R. Cao, J. Cheng. 3Drefine: An Interactive Web Server for Efficient Protein Structure Refinement. Nucleic Acids Research, web server issue, accepted, 2016. [at NAR website]


92. R. Cao, J. Cheng. Protein single-model quality assessment by feature-based probability density functions. Scientific Reports, accepted. [at Scientific Reports].


91. M.F. Lensink et al. Prediction of homo- and hetero-protein complexes by ab-initio and template-based docking: a CASP-CAPRI experiment. Proteins, accepted, 2016. [at PubMed].


90. D. Bhattacharya, B. Adhikari, J. Li, J. Cheng. FRAGSION: ultra-fast protein fragment library generation by IOHMM sampling. Bioinformatics, accepted, 2016.


89. S. Cui, T. Ji, J. Li, J. Cheng, J. Qiu. What if we ignore the random effects when analyzing RNA-seq data in a multifactor experiment. Statistical Applications in Genetics and Molecular Biology (SAGMB), accepted, 2016.


88. J. Nowotny, A. Wells, O. Oluwadare, L. Xu, R. Cao, T. Trieu, C. He, J. Cheng. GMOL: an interactive tool for 3D genome structure visualization. Scientific Reports, accepted, 2016.


87. W. Lei, Y. Lu, J. Hou, J. Li, J. Browning, P. Eichen, J. Cheng, D. Lubahn, W. Folk, G. Sun, K. Fritsche. Immunomodulation of innate immune cells by Sutherlandia frutescens: A transcriptomic analyses. FASEB Journal. 29(S1):593.3.


86. T. Tuan, J. Cheng. MOGEN: a tool for reconstructing 3D models of genomes from chromosomal conformation capturing data. Bioinformatics, accepted, doi: 10.1093/bioinformatics/btv754.


85. Y. Lu, N. Starkey, W. Li, J. Li, J. Cheng, W. Folk, D. Lubahn. Inhibition of Hedgehog-signaling driven genes in prostate cancer cells by Sutherlandia frutescens extract. PLoS ONE. 10(12):e0145507.


84. Y. Lu, J. Li, J. Cheng, D.B. Lubahn. Messenger RNA profile analysis deciphers new Esrrb responsive genes in prostate cancer cells. BMC Molecular Biology. 16(1):21, 2015.


83. Y. Lu, J. Li, J. Cheng, D.B. Lubahn. Genes targeted by the Hedgehog-signaling pathway can be regulated by Estrogen related receptor B. BMC Mol Biol.. 16(1):19, 2015.


82. T. Jo, J. Hou, J. Eickholt, J. Cheng. Improving protein fold recognition by deep learning networks. Scientific Reports. 5:17573, 2015.


81. J. Nowotny, S. Ahmed, L. Xu, O. Oluwadare, H. Chen, N. Hensley, T. Trieu, R. Cao, J. Cheng. Iterative reconstruction of three-dimensional models of human chromosomes from chromosomal contact data. BMC Bioinformatics, 16(1):338, 2015.


80. R. Cao, J. Cheng. Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation. BMC Genomics, 16:880, 2015.


79. D. Bhattacharya, J. Cheng. De novo portein conformational sampling using a probabilistic graphical model. Scientific Reports, 5:16332, 2015.


78. J. Li, R. Cao, J. Cheng. A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11. BMC Bioinformatics, 16:337, 2015.


77. J. Hou, D. Zhu, J. Cheng. An overview of bioinformatics methods for modeling biological pathways in yeast. Briefings in Functional Genomics, accepted, 2015.


76. R. Cao, D. Bhattacharya, B. Adhikari, J. Li, J. Cheng. Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11. Proteins, accepted, 2015.


75. R. Cao, J. Cheng. Integrated protein function prediction by mining function associations, sequences, and protein-protein and gene-gene interaction networks. Methods, accepted, 2015.


74. J. Hou, G. Stacey, J. Cheng. Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods. EURASIP Journal on Bioinformatics and Systems Biology, 1:5, 2015.


73. X. Deng, J. Gumm, S. Karki, J. Eickholt, J. Cheng. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions. Int J Mol Sci, 16(7):15384-15404, 2015.


72. J. Li, B. Adhikari, J. Cheng. An Improved Integration of Template-based and Template-Free Protein Structure Modeling Methods and its Assessment in CASP11. Protein Pept. Lett, 22(7):586-93, 2015.


71. B. Adhikari, D. Bhattacharya, R. Cao, J. Cheng. CONFOLD: Residue-Residue Contact-guided ab initio Protein Folding. Proteins, 83(8):1436-1439, 2015.


70. R. Cao, D. Bhattacharya, B. Adhikari, J. Li, J. Cheng. Large-Scale Model Quality Asessment for Improving Protein Tertiary Structure Prediction. 23rd International Conference on Intelligent Systems for Molecular Biology (ISMB), Bioinformatics, 31(12):i116-i123, 2015.


69. J. Li, J. Hou, L. Sun, J.M. Wilkins, Y. Lu, C.E. Niederhuth, B.R. Merideth, T.P. Mawhinney, V. Valeri, C.M. Greenlief, J.C. Walker, W.R. Folk, M. Hannink, D.B. Lubahn, J.A. Birchler, J. Cheng. From Gigabyte to Kilobyte: a Bioinformatics Protocol for Mining Large RNA-Seq Transcriptomics Data. PLoS ONE, 10(4):e0125000, 2015.


68. H. Zhou, Z. Qu, V. Mossine, D. Nknolise, J. Li, Z. Chen, J. Cheng, M, M. Greenlief, T. Mawhinney, P. Brown, K. Fritsche, M. Hannink, D. Lubahn, G. Sun, Z. Gu. Proteomic Analysis of the Effects of Aged Garlic Extract and its FruArg Component on Lipopolysaccharide-induced Neuroinflammatory Response in Microglial Cells. PLoS ONE, accepted, 2014.


67. Q. Qi, J. Li, J. Cheng. Reconstruction of Metabolic Pathways by Combining Probabilistic Graphical Model-based and Knowledge-based Methods. BMC Proceeding, 8(S6):S5, 2014.


66. X. Deng, J. Cheng. Enhancing HMM-Based Protein Profile-Profile Alignment with Structural Features and Evolutionary Coupling Information. BMC Bioinformatics. 15:252, 2014. PMCID: PMC4133609.


65. M. Spencer, J. Eickholt, J. Cheng. A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction. IEEE Transactions on Computational Biology and Bioinformatics. Accepted. NIHMSID: 635792.


64. T. Jo, J. Cheng. Improving Protein Fold Recognition by Random Forest. BMC Bioinformatics. 15(S11):S14, 2014.


63. Z Qu, F. Meng, R. Bomgarden, R. Viner, J. Li, J. Rogers, J. Cheng, C. Greenlief, J. Cui, D. Lubahn, G. Sun, and Z. Gu. Proteomic Quantification and Site-Mapping of S-Nitrosylated Proteins Using Isobaric iodoTMT Reagents. Journal of Proteome Research. 13(7):3200-3211. PMCID: PMC4084841.


62. P. Gong, Z. Madak-Ergogan, J. Li, J. Cheng, C.M. Greenlief, W.G. Helferich, J.A. Katzenellengogen, B.S. Katzenellengogen. Transcriptome analyses reveal gene network regulated by ERalpha and ERbeta that control distinct effects of different botanical estrogens. Nuclear Receptor Signaling. 12:e001, 2014.


61. R. Cao, Z. Wang, Y. Wang, J. Cheng. SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines. BMC Bioinformatics, 15:120, 2014. PMCID: PMC4013430.


60. R. Cao, Z. Wang, J. Cheng. Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment. BMC Structural Biology, 14:13, 2014. PMCID: PMC3996498.


59. G.A. Khoury, A. Liwo, F. Khatib, H. Zhou, G. Chopra, J. Bacardit, L.O. Bortot, R.A. Faccioli, X. Deng, Y. He, P. Krupa, J. Li, M.A. Mozolewska, A.K. Sieradzan, J. Smadbeck, T. Wirecki, S. Cooper, J. Flatten, K. Xu, D. Baker, J. Cheng, A.C.B. Delbem, C.A. Floudas, C. Keasar, M. Levitt, Z. Popovic, H.A. Scheraga, J. Skolnick, S.N. Crivelli, and Foldit Players. WeFold: A Coopetition for Protein Structure Prediction. Proteins. 22(9):1850-1868. PMID: 24677212.


58. Z. Qu, F. Meng, H. Zhou, J. Li, Q. Wang, F. Wei, J. Cheng, C.M. Greenlief, D.B. Lubahn, G.Y. Sun, S. Liu, Z. Gu. NitroDIGE Analysis Reveals Inhibition of Protein S-Nitrosylation by Epigallocatechin Gallates in Lipopolysaccharide-stimulated Microglial Cells. Journal of Neuroinflammation, in press [at Journal of Neuroinflamation].


57. T. Trieu, J. Cheng. Large-scale reconstruction of 3D structures of human chromosomes from chromosomal contact data. Nucleic Acids Research, accepted [at NAR's website].


56. X. Deng, J. Li, J. Cheng. Predicting protein model quality from sequence alignments by support vector machines. Journal of Proteomics and Bioinformatics. 10:S9, 2013. [PDF]


55. L. Sun, A.F. Johnson, J. Li, A.S. Lambdin, J. Cheng, J.A. Birchler. Differential effect of aneuploidy on the X chromosome and genes with sex-biased expression in Drosophila. Proceeding of National Academy of Sciences (P.N.A.S), USA. [at PNAS's web site].


54. M. Zhu, J. Dahmen, G. Stacey, J. Cheng. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcription data. BMC Bioinformatics. 14:278, 2013. PMID: PMC3854569. [Highly accessed].


53. J. Eickholt, J. Cheng. A Study and Extension of DNcon: a Method for Protein Residue-Residue Contact Prediction Using Deep Networks. BMC Bioinformatics. 14(Suppl 14):S12, 2013. PMCID: PMC3850995. [at BMC Bioinformatics' web site].


52. D. Bhattacharya, J. Cheng. i3Drefine Software for Protein 3D Structure Refinement and its Assessment in CASP10. PLoS ONE. 8(7):e69648, 2013. PMCID: PMC3716612. [at PLoS ONE's website]


51. L. Sun, A.F. Johnson, R.C. Donohue, J. Li, J. Cheng, J.A. Birchler. Dosage Compensation and Inverse Effects in Triple X Metafemales of Drosophila. Proceedings of the National Academy of Sciences (PNAS). 110(18):7383-8, 2013. [at PubMed].


50. K.H. Taylor, A. Briley, Z. Wang, J. Cheng, H. Shi, C.W. Caldwell. Aberrant Epigenetic Gene Regulation in Lymphoid Malignancies. Seminars in Hematology. 50(1):38-47, 2013. [at Elsevier's website].


49. J. Eickholt, J. Cheng. DNdisorder: Predicting Protein Disorder Using Boosting and Deep Networks. BMC Bioinformatics. 14:88, 2013. PMCID: PMC3599628. [Highly accessed].


48. J. Li, X. Deng, J. Eickholt, J. Cheng. Designing and Benchmarking the MULTICOM Protein Structure Prediction System. BMC Structural Biology. 13:2, 2013. PMCID: PMC3599124. [Highly accessed].


47. Z. Wang, R. Cao, K. Taylor, A. Briley, C. Caldwell, J. Cheng. The Properties of Genome Conformation and Spatial Gene Interaction and Regulation Networks of Normal and Malignant Human Cell Types. PLoS ONE. 8(3):e58793, 2013. PMCID: PMC3594155. [at PLoS ONE's web site].


46. L. Sun, H.R. Fernandez, R.C. Donohue, J. Li, J. Cheng, J.A. Birchler. Male-Specific Lethal Complex in Drosophila Counteracts the Effect of Histone Acetylation and Does Not Mediate Dosage Compensation. Proceeding of National Academy of Sciences (P.N.A.S.) USA.110(9):E808-17, 2013. [at PNAS's website].


45. P. Radivojac, W. Clark, T.B. Oron, A.M. Schnoes, T. Wittkop, A. Sokolov, K. Graim, C. Funk, K. Verspoor, A. Ben-Hur, G. Pandey, J.M. Yunes, A.S. Talwakar, S. Repo, M.L. Souza, D. Piovesan, R. Casadio, Z. Wang, J. Cheng, H. Fang, J. Gough, P. Koskinen, P. Toronen, J. Nokso-Koivisto, L. Holm, D. Cozzetto, D.W. Buchan, K. Bryson, D.T. Jones, B. Limaye, H. Inamdar, A. Datta, S.K. Manjari, R. Joshi, M. Chitale, D. Kihara, A.M. Lisewski, S. Erdin, E. Venner, O. Lichtarge, R. Rentzsch, H. Yang, A.E. Romero, P. Bhat, A. Paccanaro, T. Hamp, R. Kassner, S. Seemayer, E. Vicedo, C. Schaefer, D. Achten, F. Auer, A. Bohm, T. Braun, M. Hecht, M. Heron, P. Honigschmid, T. Hopf, S. Kaufmann, M. Kiening, D. Krompass, C. Landerer, Y. Mahlich, M. Roos, J. Bjorne, T. Salakoski, A. Wong, H. Shatkay, M.N. Wass, M.J.E. Sternberg, N. Skunca, F. Supek, M. Bosnjak, P. Panov, S. Dzeroski, T. Smuc, Y.A.I. Kourmpetis, A.D.J. van Dijk, C.J.F. ter Braak, Y. Zhou, Q. Gong, X. Dong, W. Tian, M. Falda, P. Fontana, E. Lavezzo, B.D. Camillo, S. Toppo, L. Lan, N. Djuric, Y. Guo, S. Vucetic, A. Bairoch, M. Linial, P.C. Babbitt, S.E. Brenner, C. Orengo, B. Rost, S.D. Mooney, I. Friedberg. A Large-Scale Evaluation of Computational Protein Function Prediction. Nature Methods. 10(13):221-7, 2013. PMCID: PMC3584181. [at Nature Methods' website].


44. Z. Wang, R. Cao, J. Cheng. Three-Level Prediction of Protein Function by Combining Profile-Sequence Search, Profile-Profile Search, and Domain Co-occurrence Networks. BMC Bioinformatics. 14(Suppl 3):S3, 2013. PMCID: PMC3584933. [at BMC Bioinformatics' website].


43. D. Bhattacharya, J. Cheng. 3DRefine: Consistent Protein Structure Refinement by Optimizing Hydrogen Bonding Network and Atomic Level Energy Minimization. Proteins, 81(1):119-31, 2013. PMCID: PMC3634918. [at PubMed]


42. J. Eickholt, J. Cheng. Predicting Protein Residue-Residue Contacts Using Deep Networks and Boosting. Bioinformatics. 28(23):3066-3072, 2012. PMCID: PMC3509494. [at Bioinformatics web site].


41. M. Zhu, X. Deng, T. Joshi, D. Xu, G. Stacey, J. Cheng. Reconstructing Differentially Co-expressed Gene Modules and Regulatory Networks of Soybean Cells. BMC Genomics, 13:434, 2012. PMCID: PMC3563468. [at BMC Genomics web site].


40. J. Cheng, J. Li, Z. Wang, J. Eickholt, X. Deng. The MULTICOM Toolbox for Protein Structure Prediction. BMC Bioinformatics, 13:65, 2012. PMCID: PMC3495398. [Highly accessed]

39. J. Cheng, J. Eickholt, Z. Wang, and X. Deng. Recursive Protein Modeling: a Divide and Conquer Strategy for Protein Structure Prediction and its Case Study in CASP9. Journal of Bioinformatics and Computational Biology, vol. 10, no. 3, 2012. PMCID: PMC3622867.

38. X. Zhang, Z. Wang, X. Zhang, M. Le, J. Sun, D. Xu, J. Cheng, and G. Stacey. Evolutionary Dynamics of Protein Domain Architecture in Plants. BMC Evolutionary Biology, 12:6, 2012. PMCID: PMC3310802.

37. T. Joshi, K. Patil, M.R. Fitzpatrick, L.D. Franklin, Q. Yao, Z. Wang, M. Libault, L. Brechenmacher, B. Valiyodan, X. Wu, J. Cheng, G. Stacey, H. Nguyen, and D. Xu. Soybean Knowledge Base (SoyKB): A Web Resource for Soybean Translational Genomics. BMC Genomics, 13(Suppl 1):S15, 2012. PMCID: PMC3303740.

36. Z. Wang and J. Cheng. An Iterative Self-Refining and Self-Evaluating Approach for Protein Model Quality Estimation. Protein Science, 21(1):142-151, 2012. PMCID: PMC3323789.

35. X. Deng, J. Eickholt, J. Cheng. A Comprehensive Overview of Computational Protein Disorder Prediction Methods. Molecular BioSystems, 8(1):114-121, 2012. PMCID: PMC3633217.

34. J. Eickholt, Z. Wang, J. Cheng. A Conformation Ensemble Approach to Protein Contact Prediction.BMC Structural Biology, 11:38, 2011. PMCID: PMC3200154. [Highly accessed]

33. X. Deng and J. Cheng. MSACompro: Protein Multiple Sequence Alignment Using Predicted Secondary Structure, Solvent Accessibility, and Residue-Residue Contacts. BMC Bioinformatics. 12:472, 2011. PMCID: PMC3299741. [Highly accessed]

32. Z. Wang, J. Eickholt, J. Cheng. APOLLO: A Quality Assessment Service for Single and Multiple Protein Models. Bioinformatics. 27(12):1715-1716, 2011. PMCID: PMC3106203.

31. K. Tanaka, C. Nguyen, M. Libault, J. Cheng, Gary Stacey. Enzymatic Activity of the Soybean Ectro-Apyrase GS52 is Essential for Stimulation of Nodulation. Plant Physiology. 155(4):1988-98, 2011. PMCID: PMC3091080.

30. Z. Wang, X. Zhang, M. Le, D. Xu, G. Stacey, and J. Cheng. A Protein Domain Co-Occurrence Network Approach for Predicting Protein Function and Inferring Species Phylogeny. PLoS ONE. 6(3): e17906, 2011. PMCID: PMC3063783.

29. J. Eickholt, X. Deng, and J. Cheng. DoBo: Protein Domain Boundary Prediction by Integrating Evolutionary Signals and Machine Learning. BMC Bioinformatics. 12:43, 2011. PMCID: PMC3036623. [Highly accessed]

28. M. Libault, L. Brechenmacher, J. Cheng, D. Xu, G. Stacey. Root Hair Systems Biology. Trends in Plant Science. 15(11):641-650, 2010.

27. Z. Wang, J. Eickholt, and J. Cheng. MULTICOM: A Multi-Level Combination Approach to Protein Structure Prediction and its Assessment in CASP8. Bioinformatics. 26(7):882-888, 2010. The MULTICOM system was ranked among the best methods in template-based modeling, template-free modeling, protein model quality assessment, protein contact map prediction, and protein disorder prediction during CASP9, 2010.

26. J. Schmutz, S. Cannon, J. Schlueter, J. Ma, T. Mitros, W. Nelson, D. Hyten, Q. Song, J. Thelen, J. Cheng, D. Xu, U. Hellsten, G. May, Y. Yu, T. Sakurai, T. Umezawa, M. Bhattacharyya, D. Sandhu, B. Valliyodan, E. Lindquist, M. Peto, D. Grant, S. Shu, D. Goodstein, K. Barry, M. Futrell-Griggs, J. Du, Z. Tian, L. Zhu, N. Gill, T. Joshi, M. Libault, A. Sethuraman, X. Zhang, S. Shinozaki, H. Nguyen, R. Wing, P. Cregan, J. Specht, J. Grimwood, D. Rokhsar, G. Stacey, R. Shoemaker and S. Jackson. Genome Sequence of the Palaeopolyploid Soybean . Nature. 463:178-83, 2010.

25. Z. Wang, M. Libault, T. Joshi, B. Valliyodan, H. Nguyen, D. Xu, G. Stacey, and J. Cheng. SoyDB: A Knowledge Database of Soybean Transcription Factors. BMC Plant Biology. 10:14, 2010.

24. G. Lin, Z. Wang, D. Xu, and J. Cheng. Sequence-Based Prediction of Protein Folding Rates Using Contacts, Secondary Structures and Support Vector Machines. BMC Bioinformatics, 11(Suppl 3):S1, 2010.

23. X. Deng, J. Eickholt, and J. Cheng. PreDisorder: Ab Initio Sequence-Based Prediction of Protein Disordered Regions. BMC Bioinformatics, 10:436, 2009.

22. J. Cheng, Z. Wang, A.N. Tegge and J. Eickholt. Prediction of Global and Local Quality of CASP8 Models by MULTICOM series. Proteins, vol. 77, pp. 181-184, 2009. CASP8 invited contribution

21. A.N. Tegge, Z. Wang, J. Eickholt, and J. Cheng. NNcon: Improved Protein Contact Map Prediction Using 2D-Recursive Neural Networks. Nucleic Acids Research , vol. 37, pp. w515-w518, 2009.NNcon was ranked among the best contact map prediction methods in CASP8.

20. E.E. Stagner, D.J. Bouvrette, J. Cheng, and E.C. Bryda. The Polycystic Kidney Disease-related Proteins Bicc1 and SamCystin Interact. Biochemical and Biophysical Researh Communications. 383(1):16-21, 2009.

19. Z. Wang, A. N. Tegge, and J. Cheng. Evaluating the Absolute Quality of a Single Protein Model Using Support Vector Machines and Structural Features. Proteins, vol. 75, no. 3, 638-647, 2009. ModelEvaluator was ranked among the best model evaluation methods in CASP8.

18. J. Cheng. A Multi-Template Combination Algorithm for Protein Comparative Modeling. BMC Structural Biology.8:18, 2008. MULTICOM was ranked among the best template-based and template-free structure prediction methods in CASP8.

17. J. Dai and J. Cheng. HMMEditor: A Visual Editing Tool for Profile Hidden Markov Model. BMC Genomics. 9(S1):S8, 2008.

16. J. Hecker, J. Yang, and J. Cheng. Protein Disorder Prediction at Multiple Levels of Sensitivity and Specificity. BMC Genomics. 9(S1):S9, 2008. PreDisorder was ranked among the best disorder predictors in CASP8.

15. J. Cheng, A. N. Tegge, and P. Baldi. Machine Learning Methods for Protein Structure Prediction. IEEE Reviews in Biomedical Engineering. 1:41-49, 2008.

14. A. Randall, J. Cheng, M. Sweredoski, and P. Baldi. TMBpro: Secondary Structure, Beta-Contact, and Tertiary Structure Prediction of Transmembrane Beta-Barrel Proteins. Bioinformatics, vol. 24, pp. 513-520, 2008.

13. J. Cheng. DOMAC: An Accurate, Hybrid Protein Domain Prediction Server. Nucleic Acids Research, vol. 35, pp. w354-w356, 2007. DOMAC was ranked among the best domain predictors in CASP8

12. J. Cheng and P. Baldi. Improved Residue Contact Prediction Using Support Vector Machines and a Large Feature Set. BMC Bioinformatics. 8:113, 2007. SVMcon is one of the best contact map predictors in CASP7 and CASP8.

11. M. Tress, J. Cheng, P. Baldi, K. Joo, J. Lee, J.H. Seo, J. Lee, D. Baker, D. Chivian, D. Kim, A. Valencia, and I. Ezkurdia. Assessment of Predictions Submitted for the CASP7 Domain Prediction Category. Proteins: Structure, Function and Bioinformatics, vol. 68 (S8):137-151, 2007. [CASP7 Invited Contribution]

10. L. Larson, M. Zhang, N. Beliakova-Bethell, V. Bilanchone, A. Lamsa, K. Nagashima, R. Najdi, K. Kosaka, V. Kovacevic, A. Lamsa, J. Cheng, P. Baldi, G.W. Hatfield, and S. Sandmeyer. Ty3 Capsid Scanning Mutations Reveal Early and Late Functions of the Amino-Terminal Domain. Journal of Virology, vol. 81, pp. 6957-6972, 2007.

9. J. Cheng and P. Baldi. A Machine Learning Information Retrieval Approach to Protein Fold Recognition. Bioinformatics, vol. 22, no. 12, pp. 1456-1463, 2006.FOLDpro and 3Dpro are the No. 2 and No. 3 Servers for High-Accuracy Protein Structure Prediction in the Seventh Edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7).

8. J. Cheng, M. Sweredoski, and P. Baldi. DOMpro: Protein Domain Prediction Using Profiles, Secondary Structure, Relative Solvent Accessibility, and Recursive Neural Networks. Data Mining and Knowledge Discovery, vol. 13, no. 1, pp. 1-10, 2006. FOLDpro-DOMpro is the No. 1 Server for Automated Protein Domain Prediction in CASP7.

7. S. A. Danziger, S. J. Swamidass, J. Zeng, L. R. Dearth, Q. Lu, J. H. Chen, J. Cheng, V. P. Hoang, H. Saigo, R. Luo, P. Baldi, R. K. Brachmann, and R. H. Lathrop. Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants. IEEE Transactions on Computational Biology and Bioinformatics, vol. 3, no. 2, pp. 114-125, 2006.

6. J. Cheng, A. Randall, and P. Baldi. Prediction of Protein Stability Changes for Single-Site Mutations Using Support Vector Machines. Proteins: Structure, Function, Bioinformatics, vol. 62, no. 4, pp. 1125-1132, 2006.

5. J. Cheng, H. Saigo, and P. Baldi. Large-Scale Prediction of Disulphide Bridges Using Kernel Methods, Two-Dimensional Recursive Neural Networks, and Weighted Graph Matching.Proteins: Structure, Function, Bioinformatics, vol 62, no. 3, pp. 617-629, 2006.

4. J. Cheng, M. Sweredoski, and P. Baldi. Accurate Prediction of Protein Disordered Regions by Mining Protein Structure Data, Data Mining and Knowledge Discovery, vol. 11, no. 3, pp. 213-222, 2005. DISpro is No. 2 server in disorder prediction in CASP7 (No. 5 in both human and server predictors).

3. J. Cheng, A. Randall, M. Sweredoski, and P. Baldi, SCRATCH: a Protein Structure and Structural Feature Prediction Server. Nucleic Acids Research, vol. 33 (web server issue), w72-76, 2005.

2. J. Cheng, L. Scharenbroich, P. Baldi, and E. Mjolsness. Sigmoid: Towards a Generative, Scalable, Software Infrastructure for Pathway Bioinformatics and Systems Biology. IEEE Intelligent Systems, vol. 20, no. 3, pp. 68-75, 2005.

1. J. Cheng and P. Baldi. Three-Stage Prediction of Protein Beta-Sheets by Neural Networks, Alignments, and Graph Algorithms. Bioinformatics, vol. 21(Suppl 1), pp. i75-84, 2005. (This is the journal version of Conference paper 2)BETApro is one of the Best Residue Contact Predictors in CASP7 and CASP8.


Conference Papers   Top

13. R. Cao, D. Bhattacharya, B. Adhikari, J. Li, J. Cheng. Large-Scale Model Quality Asessment for Improving Protein Tertiary Structure Prediction.The 23rd International Conference on Intelligent Systems for Molecular Biology (ISMB), Dublin, Ireland, accepted, 2015.

12. Q. Qi, J. Li, J. Cheng. Reconstruction of Metabolic Pathways by Combining Probabilistic Graphical Model-based and Knowledge-based Methods.The Great Lake Bioinformatics Conference, Cincinatti, OH, 2014.

11. D. Bhattacharya, J. Cheng. Protein structure refinement by iterative fragment exchange.ACM Conference on Bioinformatics and Computational Biology (ACM BCB), Washington DC, 2013.

10. B. Adhikari, D. Bhattacharya, X. Deng, J. Li, J. Cheng. A Contact-Assisted Approach to Protein Structure Prediction and Its Assessments in CASP10.The Workshop on Artificial Intelligence and Robotics Methods in Computational Biology of the 27th AAAI Conference, Bellevue, WA, USA, 2013.

9. J. Chen, J. Cheng, A.K. Dunker.Intrinsically Disordered Proteins - A Tutorial.Pacific Symposium on Biocomputing (PSB), Hawaii, 2012.

8. J. Chen, J. Cheng, A.K. Dunker. Intrinsically Disordered Proteins: Analysis, Prediction, Simulation, and Biology. Pacific Symposium on Biocomputing (PSB), Hawaii, 2012.

7. T. Joshi, K. Patil, M.R. Fitzpatrick, L.D. Franklin, Q. Yao, Z. Wang, M. Libault, L. Brechenmacher, B. Valiyodan, X. Wu, J. Cheng, G. Stacey, H. Nguyen, and D. Xu. Soybean Knowledge Base (SoyKB): A Web Resource for Soybean Translational Genomics. The 10th Asia Pacific Bioinformatics Conference (APBC), Melbourne, Australia, 2012.

6. J. Cheng, J. Eickholt, Z. Wang, and X. Deng. Recursive Protein Modeling: a Divide and Conquer Strategy for Protein Structure Prediction and its Case Study in CASP9. Computational Structural Bioinformatics Workshop, Atlanta, Georgia, 2011.

5. G. Lin, Z. Wang, D. Xu, and J. Cheng. Sequence-Based Prediction of Protein Folding Rates Using Contacts, Secondary Structures and Support Vector Machines. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington D.C., 2009.

4. J. Dai and J. Cheng. HMMVE: A Visual Editor for Profile Hidden Markov Model. International Conference on Bioinformatics and Computational Biology (BIOCOMP), Las Vegas, 2007.

3. J. Cheng, Z. Wang, and G. Pollastri. A Neural Network Approach to Ordinal Regression. International Joint Conference on Neural Networks (IJCNN), Hongkong, 2008.

2. J. Cheng and P. Baldi. Three-Stage Prediction of Protein Beta-Sheets by Neural Networks, Alignments, and Graph Algorithms. Proceedings of the 2005 Conference on Intelligent Systems for Molecular Biology (ISMB 2005). Bioinformatics, vol. 21(Suppl 1), pp. i75-84, 2005.

1. P. Baldi, J. Cheng, and A. Vullo. Large-Scale Prediction of Disulphide Bond Connectivity . Advances in Neural Information Processing Systems 17 (NIPS 2004), L. Saul,Y. Weiss, and L. Bottou editors, MIT press, pp.97-104, Cambridge, MA, 2004.


Book Chapters   Top

4. J. Li, D. Bhattacharya, R. Cao, B. Adhikari, X. Deng, J. Eickholt, J. Cheng. The MULTICOM Protein Tertiary Structure Prediction System. 1137:29-41, 2014. PMID: 24573472.

3. X. Deng, J. Cheng. MSACompro: Improving Multiple Protein Sequence Alignment by Predicted Structural Features. 1079:273-283, 2014. PMID: 24170409.

2. B. Compani, T. Su, I. Chang, J. Cheng, K. Shah, T. Whisenant, Y. Dou, A. Bergmann, R. Cheong, L. Bardwell, A. Levchenko, P. Baldi, and E. Mjolsness. A Scalable and Integrative System for Pathway Bioinformatics and Systems Biology. Adv Exp Med Biol. 680:523-534, 2010.

1. A. N. Tegge, Z. Wang, and J. Cheng. Integrative Protein Fold Recognition by Alignments and Machine Learning. in Protein Structure Prediction: Method and Algorithms (editors: H. Rangwala and G. Karypis), Wiley, 2009.


Theses   Top

8. D. Bhattacharya. Computational Optimization Algorithms For Protein Structure Refinement. Master's Thesis. University of Missouri, Columbia.

7. S. Ahmed. Iterative Reconstruction of Three-Dimensional Model of Human Genome from Chromosomal Contact Data. Master's Thesis. University of Missouri, Columbia, 2014.

6. X. Deng. Improved Computational Methods of Protein Sequence Alignment, Model Selection and Tertiary Structure Prediction. PhD Dissertation. University of Missouri, Columbia, 2013.

5. J. Eickholt. Predicting Protein Residue-Residue Contacts and Disorder. PhD Dissertation. University of Missouri, Columbia, 2013.

4. Z. Wang. Revealing the Conformation and Properties of Human Genome, Protein Molecules, and Protein Domain Co-Occurrence Network . PhD Dissertation. University of Missouri, Columbia, 2012.

3. M. Ahmad. MUPRIMER: A Tool for Finding Allele Specific PCR-Primers for Homologous Gene Sequences . Master Thesis. University of Missouri, Columbia, 2009.

2. J. Cheng. Machine Learning Algorithms for Protein Structure Prediction. PhD Dissertation. University of California Irvine, Irvine, CA, 2006.

1. J. Cheng. A Comparative Study of the Similarity Measures of Text Categorization. Master Thesis. Utah State University, Logan, UT, 2001.

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