Information Visualization to Enhance Sensitivity and Selectivity in Biosensing

Abstract

An overview is provided of the various methods for analyzing biosensing data, with emphasis on information visualization approaches such as multidimensional projection techniques. Emphasis is placed on the importance of data analysis methods, with a description of traditional techniques, including the advantages and limitations of linear and non-linear methods to generate layouts that emphasize similarity/dissimilarity relationships among data instances. Particularly important are recent methods that allow processing high-dimensional data, thus taking full advantage of the capabilities of modern equipment. In this area, now referred to as e-science, the choice of appropriate data analysis methods is crucial to enhance the sensitivity and selectivity of sensors and biosensors. Two types of systems deserving attention in this context are electronic noses and electronic tongues, which are made of sensor arrays whose electrical or electrochemical responses are combined to provide “finger print” information for aromas and tastes. Examples will also be given of unprecedented detection of tropical diseases, made possible with the use of multidimensional projection techniques. Furthermore, ways of using these techniques along with other information visualization methods to optimize biosensors will be discussed.

Probing trace levels of prometryn solutions: from test samples in the lab toward real samples with tap water

“…4. Details of multidimensional projection techniques can be found in Paulovich et al [26] and Oliveira et al [27]. Basically, each circle in the plot represents a whole spectrum, and the closer the circles, the more similar the SERS spectra.…”

Detection of trace levels of atrazine using surface-enhanced Raman scattering and information visualization

“…We have also performed a quantitative computational analysis of the SERS spectra using a multidimensional projection technique, whose details are given in Paulovich et al [42] and Oliveira et al [36]. The suitability of SERS to distinguish atrazine solutions demonstrated in Fig.…”

“…For biosensing, in particular, other multidimensional projection techniques have been proven superior to PCA [36], especially in the cases where an optimization procedure is exploited. In these methods that are said to belong to the realms of information visualization, one attempts to project data from a multidimensional space onto a 2D or 3D plot with maximum preservation of similarity relationships.…”

Nanomaterials for Diagnosis: Challenges and Applications in Smart Devices Based on Molecular Recognition

“…Moreover, the amount of data generated in measurements with state-of-the-art equipment is already huge and therefore statistical and computational methods will soon be mandatory for data analysis. 203 This is particularly true for clinical diagnosis owing to the variability inherent in biological samples, especially when imaging is involved.…”

“…The suitable frequencies in Figure 17 were marked with blue boxes to mean that the silhouette coefficient 203 where a i is the average distance between the ith data point and all other points of the same cluster and b i is the minimum distance between the ith data point and the points from the other clusters. The blue boxes mean that all the frequencies selected have a high S c , close to 1.…”