title: NetLand: quantitative modeling and visualization of Waddington's epigenetic landscape using probabilistic potential.
abstract: CONCLUSIONS
  Waddington's epigenetic landscape is a powerful metaphor for cellular dynamics driven by gene regulatory networks (GRNs). Its quantitative modeling and visualization, however, remains a challenge, especially when there are more than two genes in the network. A software tool for Waddington's landscape has not been available in the literature. We present NetLand, an open-source software tool for modeling and simulating the kinetic dynamics of GRNs, and visualizing the corresponding Waddington's epigenetic landscape in three dimensions without restriction on the number of genes in a GRN. With an interactive and graphical user interface, NetLand can facilitate the knowledge discovery and experimental design in the study of cell fate regulation (e.g. stem cell differentiation and reprogramming).
  
  
  METHODS
  NetLand can run under operating systems including Windows, Linux and OS X. The executive files and source code of NetLand as well as a user manual, example models etc. can be downloaded from http://netland-ntu.github.io/NetLand/ .
  
  
  BACKGROUND
  zhengjie@ntu.edu.sg.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Biomedical Informatics Lab, School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.|Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, Singapore.
authors.forename: Jing
authors.initials: J
authors.lastname: Guo
authors.affiliation: Biomedical Informatics Lab, School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.
authors.forename: Feng
authors.initials: F
authors.lastname: Lin
authors.affiliation: Biomedical Informatics Lab, School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.
authors.forename: Xiaomeng
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Bioinformatics Institute, Agency for Science, Technology, and Research (A*STAR), Singapore, Singapore.
authors.forename: Vivek
authors.initials: V
authors.lastname: Tanavde
authors.affiliation: Biomedical Informatics Lab, School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.|Genome Institute of Singapore, A*STAR, Singapore, Singapore.|Complexity Institute, Nanyang Technological University, Singapore, Singapore.
authors.forename: Jie
authors.initials: J
authors.lastname: Zheng
mesh_terms: D000818:Animals; D002454:Cell Differentiation / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D044127:Epigenesis, Genetic; D053263:Gene Regulatory Networks; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D012984:Software; D013234:Stem Cells / Q000378:metabolism / Q000502:physiology