Publications

Cancer Bioinformatics

Book:  

Xu Y, Cui J and J. Dave Puett. Cancer Bioinformatics, Springer, New York, 2014

Book Chapters:  

  1. Voshall, A, Cui J. Functional discovery of small non-coding RNA through computational inference, Chapter 28. In MRW Comprehensive Foodomics. Elsevier. 2020
  2. Cui J.  Bioinformatics Databases and Tools on Dietary microRNA. In The Handbook of Nutrition, Diet and Epigenetics. Edited by Vinood B. Patel and Victor R. Preedy. Springer, 2019
  3. Cui J. Non-coding RNAs as a cause of cancer: evidence from GWAS and reverse genetics. In Cancer and Noncoding RNAs. Edited by Jayprokas Chakrabarti, Sanga Mitra, and Peter Linsley. Elsevier book series Translational Epigenetics, 2017
  4. Cui J. Genomic Data Analysis for Personalized Healthcare. In Healthcare Data Analytics. Edited by Chandan K. Reddy, Charu C. Aggarwal. CRC Press (Data Mining and Knowledge Discovery Series), 2015
  5. Cui J, Xu Y, Puett D. Microarray-Based Transcriptome Profiling of Ovarian Cancer Cells. In Ovarian cancer - Methods and Protocols. Humana Press, doi:10.1007/978-1-62703-547-7, 2013
  6. Cui J, Xu Y, Puett D. Transcriptomic Analysis of Human Ovarian Cancer Cells: Changes Mediated by Luteinizing Hormone Receptor Activation. In Ovarian Cancer -Basic Science Perspective. InTech, edited by Samir A. Farghaly, ISBN 978-953-307-812-0, 418 pages,  doi: 10.5772/1268, February 17, 2012
Papers:     

(* co-first authors; # Corresponding authors)

  1. Azizian S, Cui J#. DeepMiRBP: A Hybrid Model for Predicting MicroRNA-Protein Interactions Based on Transfer Learning and Cosine Similarity. BMC Bioinformatics. 2024. https://www.researchsquare.com/article/rs-4868514/v1.
  2. Madadjim R, An T, Cui J#. MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications. Int. J. Mol. Sci. 2024, 25(7), 3914.
  3. Shu J, Braga CP, Cui J, Adamec J, Zempleni J. Bovine mRNAs in small extracellular vesicles from cow’s milk are not bioavailable in mice and translation products are not detectable in reticulocyte lysates and human U937 cells. ExRNA (in press).
  4. Kok CR, Rose DJ, Cui J, Whisenhunt L, Hutkins R. Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses. BMC Microbiol. 2024 May 25;24(1):183. doi: 10.1186/s12866-024-03344-y. PMID: 38796418; PMCID: PMC11127362.Madadjim R, An T, Cui J#. MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications. Int. J. Mol. Sci. 2024, 25(7), 3914; https://doi.org/10.3390/ijms25073914
  5. Fratantonio D, Munir J, Shu J, Howard H, Baier S, Cui J and Zempleni J. The RNA cargo in small extracellular vesicles from chicken eggs is bioactive in C57BL/6J mice and human peripheral blood mononuclear cells ex vivo. Front Nutr. 2023 Apr 14;10:1162679. 
  6. Sukreet S, Braga CP, Adamec J, Cui J, Zempleni J. The Absorption of Bovine Milk Small Extracellular Vesicles Depends on Galectin-3 and Galactose Ligands in Human Intestinal Cells and C57BL/6J Mice. American Journal of Physiology-Cell Physiology. 2023 Dec 1;325(6):C1421-C1430. 
  7. Madadjim R, Dogan H, Cui J#. Computational learning of small RNA regulation in pancreatic cancer progression. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2022. Las Vegas, USA. December 2022
  8. Hakguder Z, He YC, Chai WW, Cui J#.Smart Diet Management through Food Image and Cooking Recipe Analysis. Workshop of Artificial Intelligence Techniques for BioMedicine and HealthCare (AIBH) at BIBM 2022. Las Vegas, USA. December 2022.
  9. Shao D, Huang L, Wang Y, He K, Cui XT, Wang Y, Ma Q, Cui J#. DeepSec: a deep learning framework for secreted protein discovery in human body fluid. Bioinformatics. 2022 Jan,38(1):228-235. https://doi.org/10.1093/bioinformatics/btab545.
  10. Dogan H, Hakguder Z, Madadjim R, Scott S, Pierobon M, Cui J#. Elucidation of dynamic microRNA regulations in cancer progression using integrative machine learning. Briefings in Bioinformatics. August 2021, https://doi.org/10.1093/bib/bbab270.
  11. Chen X, Liu B, Li X, et al. Identification of anti-inflammatory vesicle-like nanoparticles in honey. J. Extracell. Vesicles 2021;10:e12069. https://doi.org/10.1002/jev2.12069.
  12. Shao D, Huang L, Wang Y, Cui XT, Li YF, Wang Y, Ma Q, Du W, Cui J#, HBFP: a new repository for human body fluid proteome, Database, Volume 2021, 2021, baab065, https://doi.org/10.1093/database/baab065
  13. Sukreet S, Braga CP, An TT, Adamec J, Cui J, Trible B, Zempleni J. Isolation of extracellular vesicles from byproducts of cheesemaking by tangential flow filtration yields heterogeneous fractions of nanoparticles. Journal of Dairy Science 2021;104 (9), 9478-9493
  14. Dogan H, Shu J, Hakguder Z, Xu Z, Cui J#. Elucidation of Molecular Links between Obesity and Cancer through MicroRNA Regulation. BMC Medical Genomics. 13:161 (2020). 
  15. Shao D, Wang Y#, Cui J#Human Body Fluid Proteome: Quantitative Profiling and Computational Prediction. Briefings in Bioinformatics. 2020  https://doi.org/10.1093/bib/bbz160 
  16. Liu HQ, Dogan H, Cui J#. A New Approach to Batch Effect Removal Based on Distribution Matching in Latent Space. IEEE BIBM 2019.
  17. Dogan H, Hakguder Z, Scott S, Cui J#. Unraveling MicroRNA-Gene Regulatory Networks in Breast Cancer with Integrative Directed and Undirected Graphical Models. IEEE BIBM 2019 ERLBD workshop.
  18. Zhou F, Paz H, Shu J, Mahrou Sadri M, Cui J, Fernando S, Zempleni J. Dietary bovine milk exosomes elicit changes in bacterial communities in C57BL/6 mice. American Journal of Physiology-Gastrointestinal and Liver Physiology. OCT 2019. 317(5)https://doi.org/10.1152/ajpgi.00160.2019.
  19. Cao M, Li HQ, Zhao J, Cui J#, Hu GH#. Identification of age- and gender-associated long noncoding RNAs in the human brain with Alzheimer's disease. Neurobiology of Aging. (2019, 81:116-126)
  20. Cui J#, Shu, J. Circulating microRNA trafficking and regulation: computational principles and practice. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbz079 (2019)
  21. Gao T*, Shu J*, Cui J#. A Systematic Approach to RNA-Associated Motif Discovery. BMC genomics 2018 Feb 14;19(1):146.
  22. Hakguder Z, Liao CX, Shu J, Pan KY, Cui J#. Genome-Scale MicroRNA Target Prediction through Clustering with Dirichlet Process Mixture Model. BMC Genomics. 2018 Sep 24;19(Suppl 7):658.
  23. Silva B, Rad Milad, McCabe M, Pan KY, Cui J# (2018). A Mobile-Based Diet Monitoring System For Obesity Management. Journal of Health and Medical Informatics 2018, 9: 307. doi:10.4172/2157-7420.1000307
  24. Leiferman A, Shu J, Grove R, Cui J, Adamec J, Zempleni J (2018). A diet defined by its content of bovine milk exosomes and their RNA cargos has moderate effects on gene expression, amino acid profiles and grip strength in skeletal muscle in C57BL/6 mice. Journal of Nutritional Biochemistry. doi:10.1016/j.jnutbio.2018.06.007.
  25. Aguilar-Lozano A, Baier S, Grove R, Shu J, Giraud D, Mercer K, Cui J, Badger T, Adams S, Adamec J, Andres A, Zempleni J (2018). Concentrations of Purine Metabolites are Elevated in Fluids from Adults and Infants and in Livers From Mice Fed Diets Depleted of Bovine Milk Exosomes and their RNA Cargos. Journal of Nutrition.  2018 Dec 1;148(12):1886-1894. doi: 10.1093/jn/nxy223. 
  26. Hu GK, Liao K, Niu F, Yang L, Dallon B, Callen S, Tian CH, Shu J, Cui J, Sun ZQ, Lyubchenko Y, Ka MH, Chen XM, and Buch S. Astrocyte EV-induced lincRNA-Cox2 regulates microglial phagocytosis: Implications for morphine-mediated potentiation of neurodegeneration. Molecular Therapy - Nucleic Acids. 2018 Sep 29;13:450-463. doi: 10.1016/j.omtn.2018.09.019.
  27. Zhao Q, Sun X, Liu C, Li T, Cui J, Qin C. Expression of the microRNA-143/145 cluster is decreased in hepatitis B virus-associated hepatocellular carcinoma and may serve as a biomarker for tumorigenesis in patients with chronic hepatitis B. Oncol Lett. 2018 May;15(5):6115-6122. doi: 10.3892/ol.2018.8117.
  28. Shu J, Silva B, Cui J#. Dynamic and Modularized MicroRNA Regulation and Its Implication in Human Cancer. Scientific Reports. 13356(2017). doi:10.1038/s41598-017-13470-5
  29. Hakguder Z, Liao CX, Shu J, Cui J#. A New Statistical Model for Genome-Scale MicroRNA Target Prediction. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2017, Kansas City, MO, November 2017. p.101-7. DOI: 10.1109/BIBM.2017.8217633. 
  30. Milad Ghiasi Rad, Aditya Immaneni, Megan McCabe, and Juan Cui#, Glucose-Insulin Stand-Alone Simulation Tool Design and Implementation in OSG. BIBM 2017 BIOSG Workshop.
  31. Shu J, Cui J# (2017). MiRDR-OSG: MicroRNA dynamic regulation analysis utilizing open science grid. BIBM 2017 BIOSG Workshop . doi: 10.1109/BIBM.2017.8217941.
  32. Silva B, Cui J# (2017). A Survey on Automated Food Monitoring and Dietary Management Systems. Journal of Health & Medical Informatics 8: 272. doi: 10.4172/2157-7420.1000272
  33. Xu Z, Duan Q, Cui J, Qiu YM, Jia QD, Wu C, Clarke J. Analysis of Genetic and Non-genetic Factors Influencing Triglycerides-Lowering Drug Effects Based on Paired Observations”. BMC Proc. 2018 Sep 17;12(Suppl 9):46. doi: 10.1186/s12919-018-0153-6.
  34. Zhang HY, Silva B, Cui J#. MiRDis: A Web Tool for Endogenous and Exogenous MicroRNA Discovery Based on Deep Sequencing Data Analysis. Briefings in Bioinformatics. Jan. 2017, page 1-10, doi: 10.1093/bib/bbw140 
  35. Sud N, Zhang HY, Cui J, and Su QZ. ­­­Aberrant Expression of microRNA induced by high fructose diet impairs hepatic energy metabolic signaling. Journal of Nutritional Biochemistry. 43 (2017), pp. 125–131. doi: 10.1016/j.jnutbio.2017.02.003
  36. Han JC, Shu J, Cui J#. A New System For Human MicroRNA Functional Evaluation and Network Construction. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shengzhen, China, 15 - 18 December 2016.
  37. Cui J, Zhou BY, Ross S, Zempleni J. Nutrition, microRNAs and human health. Advances in Nutrition January 2017, vol. 8: 105-112
  38. Shu J, Chiang K, Zempleni J, Cui J#. Computational Characterization of Exogenous MicroRNAs That Can Be Transferred into Human Circulation. PLoS ONE, 11/2015; 10(11):e0140587.
  39. Chiang K, Shu J, Zempleni J, Cui J#. Dietary MicroRNA Database (DMD): An archive database and analytic tool for microRNAs in human foods. PLoS ONE, 2015 June 1; 10(6): e0128089. doi:10.1371/journal.pone.0128089.
  40. Shu J, Chiang K, Zhao DY, Cui J#. Human Absorbable MicroRNA Prediction based on an Ensemble Manifold Ranking Model. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, D.C., 9 - 12 November 2015, 295-300, doi:10.1109/BIBM.2015.7359697
  41. Zempleni J, Baier SR, Howard KM, Cui J. Gene regulation by dietary microRNAs. Can J Physiol Pharmacol, 2015 Dec;93(12):1097-1102. doi: 10.1139/cjpp-2014-0392.
  42. Wang Y, Wang G, Meng D, Huang L, Blanzieri E, Cui J. A Markov Clustering based Link Clustering Method to Identify Overlapping Modules in Protein-protein Interaction Networks. Current Bioinformatics, 2015, 11(2) 221-233.
  43. Cui J, Yin YB, et al. Comprehensive Characterization of Genomic Alterations in Human Gastric Cancer. International Journal of Cancer 2014 Nov 24. doi: 10.1002/ijc.29352.
  44. Beach S, Brody G, Lei GH, Kim S, Cui J, Philibert R. Is serotonin transporter genotype associated with epigenetic susceptibility or vulnerability? Examination of the impact of socioeconomic status risk on African American youth. Development and Psychopathology 26 (2014), 289–304 
  45. Ma Q, Reeves JH, Liberles DA, Yu LL, Chang Z, Zhao J, Cui J, Xu Y, Liu L. A phylogenetic model for understanding the effect of gene duplication on cancer progression. Nucleic Acids Research 2014 Mar; 42(5): 2870-8 
  46. Sun H, Wang HP, Tang KL, Qin G, Cui J, Cao ZW, Liu Qi. iPEAP: integrating multiple omics and genetic data for pathway enrichment analysis. Bioinformatics  2014 Mar 1;30(5):737-9. 
  47. Wang JX, Liang YC, Wang Y, Cui J, Liu M, Du W, Xu Y, Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification, submitted to PLoS ONE, 2013 Nov 12;8(11): e80211
  48. Dong XY, Wang GQ, Zhang GQ, Ni ZH, Suo J, Cui J, Cui A, Xu Y, Li F (2013) The endothelial lipase protein is promising urinary biomarker for diagnosis of gastric cancer. Diagnostic Pathology 8 (1), 45, 2013.
  49. Xu K, Mao XZ, Mehta M, Cui J, Zhang C, Mao FL, Xu Y (2013) Elucidation of How Cancer Cells Avoid Acidosis through Comparative Transcriptomic Data Analysis, PLoS ONE, e71177
  50. Cui J, Mao X, Olman V, Hastings PJ, Xu Y (2012) Hypoxia and miscoupling between reduced energy efficiency and signaling to cell proliferation drive cancer to grow increasingly faster. Journal of Molecular Cell Biology 4: 174-176. 
  51. Cui J, Liang YC, Xu Y (2012) Systems biology in the frontier of cancer research: a report on the Second International Workshop of Cancer Systems Biology. Chin J Cancer. Aug 28. doi: 10.5732/cjc.012.10205.
  52. Su Y, Ni Z, Wang G, Cui J, Wei C, et al. (2012) Aberrant expression of microRNAs in gastric cancer and biological significance of miR-574-3p. International Immunopharmacology 13: 468-475.
  53. Liu Q, Zhou H, Cui J, Cao Z, Xu Y (2012) Reconsideration of in-silico siRNA design based on feature selection: a cross-platform data integration perspective. PLoS ONE 7: e37879.
  54. Xu K, Mao X, Mehta M, Cui J, Zhang C, et al. (2012) A comparative study of gene-expression data of basal cell carcinoma and melanoma reveals new insights about the two cancers. PLoS ONE 7: e30750.
  55. Cui J, Eldredge JB, Xu Y, Puett D (2011) MicroRNA expression and regulation in human ovarian carcinoma cells by luteinizing hormone. PLoS ONE 6.: e21730 
  56. Cui J, Miner BM, Eldredge JB, Warrenfeltz SW, Dam P, et al. (2011) Regulation of gene expression in ovarian cancer cells by luteinizing hormone receptor expression and activation. BMC Cancer 11: 280
  57. Cui J, Chen Y, Chou WC, Sun L, Chen L, et al. (2011) An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucleic Acids Research 39: 1197-1207.
  58. Cui J, Li F, Wang G, Fang X, Puett JD, et al. (2011) Gene-expression signatures can distinguish gastric cancer grades and stages. PLoS ONE 6: e17819 
  59. Gao J*, Cui J*, Wang Y, Dong ZN, Tian YP, et al. (2011) Identification of potential predictors for subtype IgA nephropathy through analyses of blood biochemical indicators. Clinica Chimica Acta 412: 441-445 
  60. Hong CS, Cui J, Ni Z, Su Y, Puett D, et al. (2011) A computational method for prediction of excretory proteins and application to identification of gastric cancer markers in urine. PLoS ONE 6: e16875.
  61. Xu K*, Cui J*, Olman V, Yang Q, Puett D, et al. (2010) A comparative analysis of gene-expression data of multiple cancer types. PLoS ONE 5: e13696.
  62. Zhang X, Cui J, Nilsson D, Gunasekera K, Chanfon A, et al. (2010) The Trypanosoma brucei MitoCarta and its regulation and splicing pattern during development. Nucleic Acids Research 38: 7378-7387.
  63. Liu Q, Cui J, Yang Q, Xu Y (2010) In-silico prediction of blood-secretory human proteins using a ranking algorithm. BMC Bioinformatics 11: 250
  64. Lu Y, Gao Y, Cao Z, Cui J, Dong Z, et al. (2010) A study of health effects of long-distance ocean voyages on seamen using a data classification approach. BMC Med Inform Decis Mak 10: 13 
  65. Diao H, Xiao S, Cui J, Chun J, Xu Y, et al. (2010) Progesterone receptor-mediated up-regulation of transthyretin in preimplantation mouse uterus. Fertility and Sterility 93: 2750-2753.
  66. Jia J, Cui J, Liu X, Han J, Yang S, et al. (2009) Genome-scale search of tumor-specific antigens by collective analysis of mutations, expressions and T-cell recognition. Mol Immunol 46: 1824-1829.
  67. Cui J, Liu Q, Puett D, Xu Y (2008) Computational prediction of human proteins that can be secreted into the bloodstream. Bioinformatics 24: 2370-2375.
  68. Cui J, Han LY, Lin H, Tang ZQ, Ji Z, et al. (2007) Advances in exploration of machine learning methods for predicting functional class and interaction profiles of proteins and peptides irrespective of sequence homology. Current Bioinformatics 2: 95-112.
  69. Tang ZQ, Han LY, Lin HH, Cui J, Jia J, et al. (2007) Derivation of stable microarray cancer-differentiating signatures using consensus scoring of multiple random sampling and gene-ranking consistency evaluation. Cancer Res 67: 9996-10003.
  70. Cui J, Han LY, Lin HH, Zhang HL, Tang ZQ, et al. (2007) Prediction of MHC-binding peptides of flexible lengths from sequence-derived structural and physicochemical properties. Mol Immunol 44: 866-877.
  71. Cui J, Han LY, Li H, Ung CY, Tang ZQ, et al. (2007) Computer prediction of allergen proteins from sequence-derived protein structural and physicochemical properties. Mol Immunol 44: 514-520.
  72. Xie B, Zheng CJ, Han LY, Ong S, Cui J, et al. (2007) PharmGED: pharmacogenetic effect database. Clin Pharmacol Ther 81: 29.
  73. Zheng CJ, Han LY, Xie B, Liew CY, Ong S, et al. (2007) PharmGED: Pharmacogenetic Effect Database. Nucleic Acids Research 35: D794-799.
  74. Cui J, Han LY, Lin HH, Tang ZQ, Jiang L, et al. (2006) MHC-BPS: MHC-binder prediction server for identifying peptides of flexible lengths from sequence-derived physicochemical properties. Immunogenetics 58: 607-613.
  75. Han L, Cui J, Lin H, Ji Z, Cao Z, et al. (2006) Recent progresses in the application of machine learning approach for predicting protein functional class independent of sequence similarity. Proteomics 6: 4023-4037.
  76. Zheng CJ, Han LY, Chen X, Cao ZW, Cui J, et al. (2006) Information of ADME-associated proteins and potential application for pharmacogenetic prediction of drug responses. Current Pharmacogenomics 4: 87-103.
  77. Cui J, Han LY, Cai CZ, Zheng CJ, Ji ZL, et al. (2005) Prediction of functional class of novel bacterial proteins without the use of sequence similarity by a statistical learning method. J Mol Microbiol Biotechnol 9: 86-100
  78. Han LY, Zheng CJ, Lin HH, Cui J, Li H, et al. (2005) Prediction of functional class of novel plant proteins by a statistical learning method. New Phytol 168: 109-121.
  79. Han LY, Cai CZ, Ji ZL, Cao ZW, Cui J, et al. (2004) Predicting functional family of novel enzymes irrespective of sequence similarity: a statistical learning approach. Nucleic Acids Research 32: 6437-6444.