title: Progress in visual representations of chemical space.
abstract: BACKGROUND
  The concept of 'chemical space' reveals itself in two forms: the discrete set of all possible molecules, and multi-dimensional descriptor space encompassing all the possible molecules. Approaches based on this concept are widely used for the analysis and enumeration of compound databases, library design, and structure-activity relationships (SAR) and landscape studies. Visual representations of chemical space differ in their applicability domains and features and require expert knowledge for choosing the right tool for a particular problem.
  
  
  METHODS
  In this review, the authors present recent advances in visualization of the chemical space in the framework of current general understanding of this topic. Attention is given to such methods as van Krevelen diagrams, descriptor plots, principal components analysis (PCA), self-organizing maps (SOM), generative topographic mapping (GTM), graph and network-based approaches. Notable application examples are provided.
  
  
  CONCLUSIONS
  With the growth of computational power, representations of large datasets are becoming more and more common instruments in the toolboxes of chemoinformaticians. Every scientist in the field can find the method of choice for a particular task. However, there is no universal reference representation of the chemical space currently available and expert knowledge is required.
authors.affiliation: Lomonosov Moscow State University, Department of Chemistry , Moscow 119991 , Russia +7 495 939 16 20 ; +7 495 939 02 90 ; zefirov@org.chem.msu.ru.
authors.forename: Dmitry I
authors.initials: DI
authors.lastname: Osolodkin
authors.forename: Eugene V
authors.initials: EV
authors.lastname: Radchenko
authors.forename: Alexey A
authors.initials: AA
authors.lastname: Orlov
authors.forename: Andrey E
authors.initials: AE
authors.lastname: Voronkov
authors.forename: Vladimir A
authors.initials: VA
authors.lastname: Palyulin
authors.forename: Nikolay S
authors.initials: NS
authors.lastname: Zefirov
mesh_terms: D062126:Databases, Chemical; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D008956:Models, Chemical; D025341:Principal Component Analysis; D054852:Small Molecule Libraries; D013329:Structure-Activity Relationship
chemical_list: D054852:Small Molecule Libraries
keywords: big data; chemical space; chemoinformatics; data mining; visualization