IEEE Transactions on NanoBioscience (IEEE T NANOBIOSCI )

Publisher: IEEE Engineering in Medicine and Biology Society, Institute of Electrical and Electronics Engineers


This transaction reports on original, innovative and interdisciplinary work on all aspects of molecular systems, cellular systems, and tissues - including molecular electronics.

Impact factor 1.77

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    IEEE transactions on nanobioscience
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Institute of Electrical and Electronics Engineers

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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: We analyzed tubulin proteins using Resonant Recognition Model to predict possible electromagnetic resonances in tubulin and microtubules. These electromagnetic resonances are proposed to be caused by charge transfer through protein molecule. The frequencies of these electromagnetic resonances depend on charge velocity. Using different velocities of charge transfer, we predicted resonant frequencies in different frequency ranges from KHz to THz. We also proposed that these resonant frequencies could be relevant for taxol binding as well as to possible role of microtubules as macromolecular computer.
    IEEE Transactions on NanoBioscience 12/2014;
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    ABSTRACT: Human Telomerase Reverse Transcriptase (hTERT) gene is expressed in all types of cancers, and it is considered as unique biomarker for early detection, monitoring and prognosis of different cancers. Routinely, the main techniques for detection of hTERT gene expression are based on enzymatic amplifications which need specified equipments, expert personnel and high cost and time. With regarding to the clinical importance of analysis of hTERT gene expression, we have developed a rapid, simple and low cost method which detects hTERT RNA target in 5 μl reaction scale using gold nanoprobes. The method is based on the inhibition of nanoparticle aggregation in the presence of MgCl2 and it can be used as a basic technique for development of clinical scale gold nanoprobe nanobiodiagnostics for detection of hTERT gene expression with a limit of detection at fmol/μl concentrations.
    IEEE Transactions on NanoBioscience 11/2014;
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    ABSTRACT: Complementary DNA (cDNA) microarray is a well-established tool for simultaneously studying the expression level of thousands of genes. Segmentation of microarray images is one of the main stages in a microarray experiment. However, it remains an arduous and challenging task due to the poor quality of images. Images suffer from noise, artifacts, and uneven background, while spots depicted on images can be poorly contrasted and deformed. In this paper, an original approach for the segmentation of cDNA microarray images is proposed. First, a preprocessing stage is applied in order to reduce the noise levels of the microarray image. Then, the grow-cut algorithm is applied separately to each spot location, employing an automated seed selection procedure, in order to locate the pixels belonging to spots. Application on datasets containing synthetic and real microarray images shows that the proposed algorithm performs better than other previously proposed methods. Moreover, in order to exploit the independence of the segmentation task for each separate spot location, both a multithreaded CPU and a graphics processing unit (GPU) implementation were evaluated.
    IEEE Transactions on NanoBioscience 11/2014;
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    ABSTRACT: In the present analytic thinking, we have modeled the governing equations of a two dimensional peristaltic transport of a Hyperbolic tangent nanofluid in the presence of a heat source/sink with the combined effects of thermal radiation and inclined magnetic field in a tapered asymmetric channel. The propagation of waves on the non-uniform walls to have different amplitudes and phase but the same wave speed is produced the tapered asymmetric channel. The equations of dimensionless temperature and nanoparticle concentration are solved analytically under assumptions of long wavelength and low Reynolds number. The governing equations of momentum of a hyperbolic tangent nanofluid for the tapered asymmetric channel have also been solved analytically using the regular perturbation method. The expression for average rise in pressure has been figured using numerical integrations. The effects of various physical parameters entering into the problem are discussed numerically and graphically. The phenomenon of trapping is also investigated. Furthermore, the received results show that the maximum pressure rise gets increased in case of non-Newtonian fluid when equated with Newtonian fluid.
    IEEE Transactions on NanoBioscience 10/2014;
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    ABSTRACT: Diffusion-based molecular communication (DMC) is a promising technique for nanonetworks. The main objective of this paper is to evaluate the error performance of DMC employing pulse-based modulation scheme. We derive closedform expressions for error probability using energy detection and amplitude detection techniques. The error performance model accounts for diffusion noise and Inter Symbol Interference (ISI) effects.We compare the performance of both detection techniques along with investigating the effect of different parameters on error performance. We also evaluate the channel capacity of pulse modulated DMC.
    IEEE Transactions on NanoBioscience 10/2014;
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    ABSTRACT: In this paper, DNA algorithms are proposed to perform eight operations of relational algebra (calculus), which include Cartesian product, union, set difference, selection, projection, intersection, join, and division, on bio-molecular relational databases.
    IEEE Transactions on NanoBioscience 10/2014;
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    ABSTRACT: Bacterial conjugation-based nanonetwork has been recently proposed as a novel molecular communication paradigm, in which the bacteria act as carriers. This is the foundational work proposing the phenomenon of collision which occurs in the form of multi-conjugation of multiple carrier bacteria at the side of receiver nanodevice. We show the effect of this conjugation-based collision on the maximum achievable throughput of the network, using a simple graph-theoretic approach, namely, Maximum Weight Bipartite Matching. One of the several interesting results that emerges concerns the maximum achievable throughput, which is bounded by ( n p ) in case of homogeneous nodes, where n and p refer to the total number of nodes, and the vertical layers in the network, respectively.
    IEEE Transactions on NanoBioscience 10/2014;
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    ABSTRACT: In this paper, we demonstrate an electrical detection technique based on solution processed Zinc Oxide nanosphere for ultra-low level detection of Bovine Serum Albumin (BSA). Our sensor device works on the basis of the variation of conductance of the ZnO nanosphere with different concentration of BSA. The morphological and structural characterizations of ZnO nanosphere were carried out by Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM) and X-Ray diffraction (XRD). Circular Dichroism (CD) spectroscopy was performed to investigate the chemical interaction between the BSA and Zinc Oxide nanosphere. Optical detection was performed using Absorbance and Fourier transform infrared spectroscopy (FTIR) studies. Our device exhibits sensitivity 0.126 nA/pM, lower limit of detection (LOD) 10pM and the fast response time around 5 sec, confirming the highest sensitivity for BSA detection achieved so far. Sensing mechanism is governed on the basis of the charge transfer phenomenon between BSA and ZnO. All measurements were carried out at 1V bias for low power operation.
    IEEE Transactions on NanoBioscience 09/2014;
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    ABSTRACT: Protein structural classes information is beneficial for secondary and tertiary structure prediction, protein folds prediction, and protein function analysis. Thus, predicting protein structural classes is of vital importance. In recent years, several computational methods have been developed for low-sequence-similarity (25% - 40%) protein structural classes prediction. However, the reported prediction accuracies are actually not satisfactory. Aiming to further improve the prediction accuracies, we propose three different feature extraction methods and construct a comprehensive feature set that captures both sequence and structure information. By applying a random forest (RF) classifier to the feature set, we further develop a novel method for structural classes prediction. We test the proposed method on three benchmark datasets (25PDB, 640, and 1189) with low sequence similarity, and obtain the overall prediction accuracies of 93.5%, 92.6%, and 93.4%, respectively. Compared with six competing methods, the accuracies we achieved are 3.4%, 6.2%, and 8.7% higher than that achieved by the best-performing methods, showing the superiority of our method. Moreover, due to the limitation of the size of the three benchmark datasets, we further test the proposed method on three updated large-scale datasets with different sequence similarity (40%, 30%, and 25%). The proposed method achieves above 90% accuracies for all the three datasets, consistency with the accuracies on the above three benchmark datasets. Experimental results suggest our method as an effective and promising tool for structural classes prediction. Currently, a webserver that implements the proposed method is available on
    IEEE Transactions on NanoBioscience 09/2014;
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    ABSTRACT: Primers plays important role in Polymerase Chain Reaction (PCR) experiments, thus it is necessary to select characteristic primers. Unfortunately, manual primer design manners are time-consuming and easy to get human negligence because many PCR constraints must be considered simultaneously. Automatic programs for primer design were developed urgently. In this study, the Teaching-Learning-Based Optimization (TLBO), a robust and free of algorithm-specific parameters method, is applied to screen primers conformed primer constraints. The optimal primer frequency (OPF) based on three known melting temperature formulas is estimated by 500 runs for primer design in each different number of generations. We selected optimal primers from fifty random nucleotide sequences of Homo sapiens at NCBI. The results indicate that the SantaLucia's formula is better coupled with the method to get higher optimal primer frequency and shorter CPU-time than the Wallace's formula and the Bolton and McCarthy's formula. Through the regression analysis, we also find the generations are significantly associated with the optimal primer frequency. The results are helpful for developing the novel TLBO-based computational method to design feasible primers.
    IEEE Transactions on NanoBioscience 09/2014;
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    ABSTRACT: Molecular Communication is an emerging and promising communication paradigm for several multidisciplinary domains like bio-medical, industry and military. Differently to the traditional communication paradigm, the information is encoded on the molecules, that are then used as carriers of information. Novel approaches related to this new communication paradigm have been proposed, mainly focusing on architectural aspects and categorization of potential applications. So far, security and privacy aspects related to the molecular communication systems have not been investigated at all and represent an open question that need to be addressed. The main motivation of this paper lies on providing some first insights about security and privacy aspects of molecular communication systems, by highlighting the open issues and challenges and above all by outlining some specific directions of potential solutions. We start with a general presentation of attacks in traditional telecommunication systems, and then we describe the main features of the molecular communication paradigm. This structure will allow to highlight that the existing cryptographic methods and security approaches are not suitable at all for these new communication systems. Specific issues and challenges will be considered that need ad-hoc solutions. We will discuss directions in terms of potential solutions by trying to highlight the main advantages and potential drawbacks for each direction considered. We will try to answer to the main questions: 1) why this solution can be exploited in the molecular communication field to safeguard the system and its reliability; 2) which are the main issues related to the specific approach.
    IEEE Transactions on NanoBioscience 09/2014; 13(3):167-168.
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    ABSTRACT: This paper investigates the exponential stability problem of switched stochastic genetic regulatory networks (GRNs) with time-varying delays. Two types of switched systems are studied respectively: one is the stochastic switched delayed GRNs with only stable subsystems and the other is the stochastic switched delayed GRNs with both stable and unstable subsystems. By using switching analysis techniques and the modified Halanay differential inequality, new criteria are developed for the exponential stability of switched stochastic GRNs with time-varying delays. Finally, an example is given to illustrate the main results.
    IEEE Transactions on NanoBioscience 09/2014; 13(3):336-342.
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    ABSTRACT: To coordinate their behavior and virulence and to synchronize attacks against their hosts, bacteria communicate by continuously producing signaling molecules (called autoinducers) and continuously monitoring the concentration of these molecules. This communication is controlled by biological circuits called quorum sensing (QS) circuits. Recently QS circuits and have been recognized as an alternative target for controlling bacterial virulence and infections without the use of antibiotics. Pseudomonas aeruginosa is a Gram-negative bacterium that infects insects, plants, animals and humans and can cause acute infections. This bacterium has three interconnected QS circuits that form a very complex and versatile QS system, the operation of which is still under investigation. Here we use Boolean networks to model the complete QS system of Pseudomonas aeruginosa and we simulate and analyze its operation in both synchronous and asynchronous modes. The state space of the QS system is constructed and it turned out to be very large, hierarchical, modular and scale-free. Furthermore, we developed a simulation tool that can simulate gene knock-outs and study their effect on the regulons controlled by the three QS circuits. The model and tools we developed will give to life scientists a deeper insight to this complex QS system.
    IEEE Transactions on NanoBioscience 08/2014; 13(3):1-7.
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    ABSTRACT: We report the extracellular biosynthesis of gold nanoparticles (AuNPs) using a fungus Fusarium acuminatum. Mycosynthesis of Au-NPs was carried out by challenging the fungal cells filtrate with HAuCl4 solution (1mM), as nanoparticles synthesizing enzyme secrete extracellularly by the fungi. The AuNPs were characterized with the help of UV-Visible spectrophotometer, Fourier Transform Infrared spectroscopy, Zeta Potential, X-ray diffraction (XRD) and Transmission electron microscopy (TEM). We observed absorbance peak in between 520 nm-550 nm corresponding to the surface plasmon absorbance of the gold nanoparticles. The nanoparticles synthesised in the present investigation were found to be capped by proteins. XRD results showed that the distinctive formation of crystalline gold nanoparticles in the solution. The spherical and polydispersed AuNPs in the range 8 to 28 nm with average size of 17 nm were observed by TEM analysis. We also standardised the parameters like the effect of pH, temperature and salt concentration on the biosynthesis of gold nanoparticles. It was found that acidic pH, 1mM salt concentration and 370C temperature were found to be optimum for the synthesis of Au-NPs. Therefore, the present study introduces the easy, better and cheaper method for biosynthesis of AuNPs.
    IEEE Transactions on NanoBioscience 08/2014;