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Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future.

Pavlopoulos GA, Malliarakis D, Papanikolaou N, Theodosiou T, Enright AJ, Iliopoulos I - Gigascience (2015)

Bottom Line: "Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information.We briefly comment on many visualization and analysis tools and the purposes that they serve.We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics & Computational Biology Laboratory, Division of Basic Sciences, University of Crete, Medical School, 70013 Heraklion, Crete Greece.

ABSTRACT
"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

No MeSH data available.


Related in: MedlinePlus

Multivariate analyses and visualization. a Timeline of the emergence of relevant technologies and concepts. b Visualization of k-means partitional clustering algorithm. c 3D visualization of a principal component analysis. d Visualization of gene-expression measures across time using parallel coordinates. e Visualization of gene-expression clustering across time. f 2D hierarchical clustering to visualize gene expressions against several time points or conditions. g Hypothetical integration of analyses and expression heatmaps and the control of objects by VR devices
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Fig5: Multivariate analyses and visualization. a Timeline of the emergence of relevant technologies and concepts. b Visualization of k-means partitional clustering algorithm. c 3D visualization of a principal component analysis. d Visualization of gene-expression measures across time using parallel coordinates. e Visualization of gene-expression clustering across time. f 2D hierarchical clustering to visualize gene expressions against several time points or conditions. g Hypothetical integration of analyses and expression heatmaps and the control of objects by VR devices

Mentions: Microarrays [112] and RNA sequencing [87] are the two main high-throughput techniques for measuring expression levels of large numbers of genes simultaneously. Both methods are revolutionary as one can simultaneously monitor the effects of certain treatments, diseases and developmental stages on gene expression across time (Fig. 5a) and for multiple transcript isoforms. Although microarrays and RNAseq technologies are comparable to each other [113], the latter tends to dominate, especially as sequencing technologies have improved, and there now are robust statistics to model the particular noise characteristics of RNAseq, particularly for low expression [114]. Microarrays are still cheaper and in some contexts may be more convenient as their analysis is still simpler and requires less computing infrastructure.Fig. 5


Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future.

Pavlopoulos GA, Malliarakis D, Papanikolaou N, Theodosiou T, Enright AJ, Iliopoulos I - Gigascience (2015)

Multivariate analyses and visualization. a Timeline of the emergence of relevant technologies and concepts. b Visualization of k-means partitional clustering algorithm. c 3D visualization of a principal component analysis. d Visualization of gene-expression measures across time using parallel coordinates. e Visualization of gene-expression clustering across time. f 2D hierarchical clustering to visualize gene expressions against several time points or conditions. g Hypothetical integration of analyses and expression heatmaps and the control of objects by VR devices
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4548842&req=5

Fig5: Multivariate analyses and visualization. a Timeline of the emergence of relevant technologies and concepts. b Visualization of k-means partitional clustering algorithm. c 3D visualization of a principal component analysis. d Visualization of gene-expression measures across time using parallel coordinates. e Visualization of gene-expression clustering across time. f 2D hierarchical clustering to visualize gene expressions against several time points or conditions. g Hypothetical integration of analyses and expression heatmaps and the control of objects by VR devices
Mentions: Microarrays [112] and RNA sequencing [87] are the two main high-throughput techniques for measuring expression levels of large numbers of genes simultaneously. Both methods are revolutionary as one can simultaneously monitor the effects of certain treatments, diseases and developmental stages on gene expression across time (Fig. 5a) and for multiple transcript isoforms. Although microarrays and RNAseq technologies are comparable to each other [113], the latter tends to dominate, especially as sequencing technologies have improved, and there now are robust statistics to model the particular noise characteristics of RNAseq, particularly for low expression [114]. Microarrays are still cheaper and in some contexts may be more convenient as their analysis is still simpler and requires less computing infrastructure.Fig. 5

Bottom Line: "Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information.We briefly comment on many visualization and analysis tools and the purposes that they serve.We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics & Computational Biology Laboratory, Division of Basic Sciences, University of Crete, Medical School, 70013 Heraklion, Crete Greece.

ABSTRACT
"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

No MeSH data available.


Related in: MedlinePlus