Table of Contents Author Guidelines Submit a Manuscript
Complexity
Volume 2017, Article ID 8917258, 14 pages
https://doi.org/10.1155/2017/8917258
Research Article

Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer

1College of Computer Science, Sichuan University, Chengdu 610065, China
2College of Computer and Information Science, Southwest University, Chongqing 400715, China
3College of Mathematics and Statistics, Southwest University, Chongqing 400715, China
4School of Electronic and Information Engineering, Xi’an Jiaotong University, 28 Xianning West Road, Beilin District, Xi’an 710049, China
5Toxicology Institute, College of Preventive Medicine, Third Military Medical University, 30 Gaotanyan Street, Shapingba District, Chongqing 400038, China
6Department of Environment Health, College of Preventive Medicine, Third Military Medical University, 30 Gaotanyan Street, Shapingba District, Chongqing 400038, China

Correspondence should be addressed to Badong Chen; nc.ude.utjx.liam@dbnehc and Ziyuan Zhou; nc.ude.ummt@uohznauyiz

Received 30 April 2017; Revised 10 July 2017; Accepted 17 August 2017; Published 16 October 2017

Academic Editor: Fang-Xiang Wu

Copyright © 2017 Le Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [9 citations]

The following is the list of published articles that have cited the current article.

  • Zhiwei Cao, Le Zhang, Zuojing Yin, and Hongjie Gao, “Developing an agent-based drug model to investigate the synergistic effects of drug combinations,” Molecules, vol. 22, no. 12, 2017. View at Publisher · View at Google Scholar
  • Le Zhang, Jingsong Zhou, Jun Yu, and Ming Xiao, “Lineage-associated underrepresented permutations (LAUPs) of mammalian genomic sequences based on a Jellyfish-based LAUPs analysis application (JBLA),” Bioinformatics, vol. 34, no. 21, pp. 3624–3630, 2018. View at Publisher · View at Google Scholar
  • Guang-Di Liu, Yu-Chen Li, Wei Zhang, and Le Zhang, “A Brief Review of Artificial Intelligence Applications and Algorithms for Psychiatric Disorders,” Engineering, 2019. View at Publisher · View at Google Scholar
  • Xiangyu Yang, Zhenghao Li, Jingtian Zhao, Tao Ma, Pengchao Li, and Le Zhang, “The Review of Bioinformatics Tool for 3D Plant Genomics Research,” Bioinformatics Research and Applications, vol. 11490, pp. 16–27, 2019. View at Publisher · View at Google Scholar
  • Le Zhang, Wanyu Bai, Na Yuan, and Zhenglin Du, “Comprehensively benchmarking applications for detecting copy number variation,” PLOS Computational Biology, vol. 15, no. 5, pp. e1007069, 2019. View at Publisher · View at Google Scholar
  • Jiyu Fan, Ailing Fu, and Le Zhang, “Progress in molecular docking,” Quantitative Biology, 2019. View at Publisher · View at Google Scholar
  • Jin Li, Ailing Fu, and Le Zhang, “An Overview of Scoring Functions Used for Protein–Ligand Interactions in Molecular Docking,” Interdisciplinary Sciences: Computational Life Sciences, 2019. View at Publisher · View at Google Scholar
  • Xiaonan Zhang, Yonghong Zhang, Donghong Peng, and Zhaoying Liao, “Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China,” Interdisciplinary Sciences: Computational Life Sciences, vol. 11, no. 1, pp. 77–85, 2019. View at Publisher · View at Google Scholar
  • Jiakun Li, Yongtao Yang, Junhua Li, Jian Yang, Le Zhang, Ming Xiao, Song Hong, Jianxin Wang, and Wenbiao Ding, “K-mer Counting: Memory-efficient strategy, parallel computing and field of application for Bioinformatics,” Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, pp. 2561–2567, 2019. View at Publisher · View at Google Scholar