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The role of visualization and 3-D printing in biological data mining.

Weiss TL, Zieselman A, Hill DP, Diamond SG, Shen L, Saykin AJ, Moore JH, Alzheimer’s Disease Neuroimaging Initiati - BioData Min (2015)

Bottom Line: A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming.It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results.The synergy or interaction effects of multiple genetic variants were represented through a color gradient of the physical connections between nodes.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Institute for Quantitative Biomedical Sciences, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755 USA.

ABSTRACT

Background: Biological data mining is a powerful tool that can provide a wealth of information about patterns of genetic and genomic biomarkers of health and disease. A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming. It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results. More specifically, we propose that 3-D printing has an important role to play as a visualization technology in biological data mining. We provide here a brief review of 3-D printing along with a case study to illustrate how it might be used in a research setting.

Results: We present as a case study a genetic interaction network associated with grey matter density, an endophenotype for late onset Alzheimer's disease, as a physical model constructed with a 3-D printer. The synergy or interaction effects of multiple genetic variants were represented through a color gradient of the physical connections between nodes. The digital gene-gene interaction network was then 3-D printed to generate a physical network model.

Conclusions: The physical 3-D gene-gene interaction network provided an easily manipulated, intuitive and creative way to visualize the synergistic relationships between the genetic variants and grey matter density in patients with late onset Alzheimer's disease. We discuss the advantages and disadvantages of this novel method of biological data mining visualization.

No MeSH data available.


Related in: MedlinePlus

A genetic interaction network of Alzheimer’s disease as well as its base which contains SNP name labels and color key. The green edges in the network indicate stronger synergistic interactions
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Fig1: A genetic interaction network of Alzheimer’s disease as well as its base which contains SNP name labels and color key. The green edges in the network indicate stronger synergistic interactions

Mentions: The first step in 3-D printing an object from a visualization is to convert the graphics file to the appropriate format that can be read by the printer. This is not always straightforward and we encountered some technical issues. First, the original SNPAttractor software doubled the face of intersection between the cylindrical connections and the nodes, resulting in files that were uninterruptable by the 3-D printer. Adjustments were made to the SNPAttractor code, and the edited files were uploaded successfully into the 3-D printer programs ZEdit and ZPrint and used to print a physical gene-gene interaction network using the ZPrint650 printer from 3D Systems, Inc. The process took the 3-D printer 10 hours. The final physical product can be seen in Fig. 1. The 3-D printed nodes are white cubes as opposed to the digital network’s black spherical nodes, and the printed connections are rectangular instead of cylindrical. The coloring of the connections on the digital versus physical model are identical, however, as the color represents the spectrum of possible node synergies (SNP interactions), ranging from the strongest synergy, represented by the color green, to the weakest synergy, represented by red. The 3-D printed network is roughly 12x12 cm, although the spokes provide an additional centimeter or two depending on orientation. It is important to note that no special support structures were needed for printing this network due the inherent strength of the printing material that was used. Indeed, it is no common to print objects using strong plastics and even metals. Because the SNP name could not fit on the surface of the nodes, each node was labeled with a number that corresponds with the SNP rs number. The number is printed on each face of the cube, so that the network can have multiple correct orientations and can be viewed from any angle. In addition to printing the genetic network, a base was printed to function as both a resting area for the structure and a key, where node number may be matched with SNP name and the synergy color scale may be referenced. The network is very light, slightly rough to touch, and can be picked up and handled with ease. It can be placed back on its base in numerous sturdy positions.Fig. 1


The role of visualization and 3-D printing in biological data mining.

Weiss TL, Zieselman A, Hill DP, Diamond SG, Shen L, Saykin AJ, Moore JH, Alzheimer’s Disease Neuroimaging Initiati - BioData Min (2015)

A genetic interaction network of Alzheimer’s disease as well as its base which contains SNP name labels and color key. The green edges in the network indicate stronger synergistic interactions
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4526295&req=5

Fig1: A genetic interaction network of Alzheimer’s disease as well as its base which contains SNP name labels and color key. The green edges in the network indicate stronger synergistic interactions
Mentions: The first step in 3-D printing an object from a visualization is to convert the graphics file to the appropriate format that can be read by the printer. This is not always straightforward and we encountered some technical issues. First, the original SNPAttractor software doubled the face of intersection between the cylindrical connections and the nodes, resulting in files that were uninterruptable by the 3-D printer. Adjustments were made to the SNPAttractor code, and the edited files were uploaded successfully into the 3-D printer programs ZEdit and ZPrint and used to print a physical gene-gene interaction network using the ZPrint650 printer from 3D Systems, Inc. The process took the 3-D printer 10 hours. The final physical product can be seen in Fig. 1. The 3-D printed nodes are white cubes as opposed to the digital network’s black spherical nodes, and the printed connections are rectangular instead of cylindrical. The coloring of the connections on the digital versus physical model are identical, however, as the color represents the spectrum of possible node synergies (SNP interactions), ranging from the strongest synergy, represented by the color green, to the weakest synergy, represented by red. The 3-D printed network is roughly 12x12 cm, although the spokes provide an additional centimeter or two depending on orientation. It is important to note that no special support structures were needed for printing this network due the inherent strength of the printing material that was used. Indeed, it is no common to print objects using strong plastics and even metals. Because the SNP name could not fit on the surface of the nodes, each node was labeled with a number that corresponds with the SNP rs number. The number is printed on each face of the cube, so that the network can have multiple correct orientations and can be viewed from any angle. In addition to printing the genetic network, a base was printed to function as both a resting area for the structure and a key, where node number may be matched with SNP name and the synergy color scale may be referenced. The network is very light, slightly rough to touch, and can be picked up and handled with ease. It can be placed back on its base in numerous sturdy positions.Fig. 1

Bottom Line: A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming.It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results.The synergy or interaction effects of multiple genetic variants were represented through a color gradient of the physical connections between nodes.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Institute for Quantitative Biomedical Sciences, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755 USA.

ABSTRACT

Background: Biological data mining is a powerful tool that can provide a wealth of information about patterns of genetic and genomic biomarkers of health and disease. A potential disadvantage of data mining is volume and complexity of the results that can often be overwhelming. It is our working hypothesis that visualization methods can greatly enhance our ability to make sense of data mining results. More specifically, we propose that 3-D printing has an important role to play as a visualization technology in biological data mining. We provide here a brief review of 3-D printing along with a case study to illustrate how it might be used in a research setting.

Results: We present as a case study a genetic interaction network associated with grey matter density, an endophenotype for late onset Alzheimer's disease, as a physical model constructed with a 3-D printer. The synergy or interaction effects of multiple genetic variants were represented through a color gradient of the physical connections between nodes. The digital gene-gene interaction network was then 3-D printed to generate a physical network model.

Conclusions: The physical 3-D gene-gene interaction network provided an easily manipulated, intuitive and creative way to visualize the synergistic relationships between the genetic variants and grey matter density in patients with late onset Alzheimer's disease. We discuss the advantages and disadvantages of this novel method of biological data mining visualization.

No MeSH data available.


Related in: MedlinePlus