Interactive and coordinated visualization approaches for biological data analysis.
Brief Bioinform
; 20(4): 1513-1523, 2019 07 19.
Article
en En
| MEDLINE
| ID: mdl-29590305
ABSTRACT
The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Biología Computacional
/
Análisis de Datos
Tipo de estudio:
Prognostic_studies
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Brief Bioinform
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
Año:
2019
Tipo del documento:
Article