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IEEE Transactions on Nanobioscience

Ergin Dinc, Ozgur B Akan
In nano-bio networks, multiple transmitter-receiver pairs will operate in the same medium. Both inter-symbol interference and multi-user interference can cause saturation at the receiver side, and this effect may cause an outage. Thus, we propose a tractable framework to calculate the theoretical operating points for fully absorbing receiver.
April 12, 2017: IEEE Transactions on Nanobioscience
Chunmei Feng, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Jiguo Yu
In modern molecular biology, the hotspots and difficulties of this field are identifying characteristic genes from gene expression data. Traditional reconstruction-error- minimization model Principal Component Analysis (PCA) as a matrix decomposition method uses quadratic error function´╝î which is known sensitive to outliers and noise. Hence it is necessary to learn a good PCA method when outliers and noise exist. In this paper, we develop a novel PCA method enforcing P-norm on error function and graph-Laplacian regularization term for matrix decomposition problem, which is called as PgLPCA...
March 31, 2017: IEEE Transactions on Nanobioscience
Hamideh Ramezani, Ozgur B Akan
Understanding the fundamentals of communication among neurons, known as neuro-spike communication, leads to reach bio-inspired nanoscale communication paradigms. In this work, we focus on a part of neuro-spike communication, known as axonal transmission, and propose a realistic model for it. The shape of the spike during axonal transmission varies according to previously applied stimulations to the neuron and these variations affect the amount of information communicated between neurons. Hence, to reach an accurate model for neurospike communication, the memory of axon and its effect on the axonal transmission should be considered, which are not studied in the existing literature...
March 28, 2017: IEEE Transactions on Nanobioscience
Dogu Arifler, Dizem Arifler
For biomedical applications of nanonetworks, employing molecular communication for information transport is advantageous over nano-electromagnetic communication: molecular communication is potentially biocompatible and inherently energy-efficient. Recently, several studies have modeled receivers in diffusion-based molecular communication systems as "perfectly monitoring" or "perfectly absorbing" spheres based on idealized descriptions of chemoreception. In this work, we focus on perfectly absorbing receivers and present methods to improve the accuracy of simulation procedures that are used to analyze these receivers...
March 27, 2017: IEEE Transactions on Nanobioscience
Serghei Mangul, Harry Taegyun Yang, Farhad Hormozdiari, Alex Dainis, Elizabeth Tseng, Euan A Ashley, Alex Zelikovsky, Eleazar Eskin
Sequencing of RNA provides the possibility to study an individual's transcriptome landscape and determine allelic expression ratios. Single-molecule protocols generate multi-kilobase reads longer than most transcripts allowing sequencing of complete haplotype isoforms. This allows partitioning the reads into two parental haplotypes. While the read length of the single-molecule protocols is long, the relatively high error rate limits the ability to accurately detect the genetic variants and assemble them into the haplotype-specific isoforms...
March 17, 2017: IEEE Transactions on Nanobioscience
Siavash Ghavami, Farshad Lahouti
A nano abnormality detection scheme (NADS) in molecular nano-networks is studied. This is motivated by the fact that early detection of diseases such as cancer play a crucial role in their successful treatment. The proposed NADS is in fact a two-tier network of sensor nano-machines (SNMs) in the first tier and a data-gathering node (DGN) at the sink. The SNMs detect the presence of competitor cells (abnormality) by variations in input and/or parameters of a nano-communications channel (NCC). The noise of SNMs as their nature suggest is considered correlated in time and space and herein assumed additive Gaussian...
March 2, 2017: IEEE Transactions on Nanobioscience
Yuan Zhang, Haihong Liu, Fang Yan, Jin Zhou
In this paper, we investigate the oscillatory expression in Escherichia coli mediated by microRNA with time delays and reaction-diffusion terms. First of all, the integrated effects of delays and diffusions are first introduced into the genetic regulatory networks involving microRNAs, and a general model of genetic regulatory networks is then formulated. Secondly, two functional issues on gene regulatory networks, i.e. stability and oscillation of such model, are addressed in detail, and an explicit algorithm determining the properties of periodic oscillation is also presented...
March 1, 2017: IEEE Transactions on Nanobioscience
Michal Marczyk
2D gel electrophoresis is the most commonly used method in biomedicine to separate even thousands of proteins in a complex sample on a single gel. Even though the technique is quite known, there is still a need to find an efficient and reliable method for detection of protein spots on gel image. In this paper a three step algorithm based on mixture of 2D normal distribution functions is introduced to improve the efficiency of spot detection performed by the existing algorithms, namely Pinnacle software and watershed segmentation method...
March 1, 2017: IEEE Transactions on Nanobioscience
Takuya Moriyama, Yuichi Shiraishi, Kenichi Chiba, Rui Yamaguchi, Seiya Imoto, Satoru Miyano
Detection of somatic mutations from tumor and matched normal sequencing data has become a standard approach in cancer research. Although a number of mutation callers have been developed, it is still difficult to detect mutations with low allele frequency even in exome sequencing. We expect that overlapping paired-end read information is effective for this purpose, but no mutation caller has modeled overlapping information statistically in a proper form in exome sequence data. Here, we develop a Bayesian hierarchical method, OVar- Call (https://github...
March 1, 2017: IEEE Transactions on Nanobioscience
Peter Gawthrop
Engineering systems modelling and analysis based on the bond graph approach has been applied to biomolecular systems. In this context, the notion of a Faraday-equivalent chemical potential is introduced which allows chemical potential to be expressed in an analogous manner to electrical volts thus allowing engineering intuition to be applied to biomolecular systems. Redox reactions, and their representation by half-reactions, are key components of biological systems which involve both electrical and chemical domains...
February 24, 2017: IEEE Transactions on Nanobioscience
Yifan Chen, Yu Zhou, Ross Murch, Panagiotis Kosmas
To maximize the effect of treatment and minimize the adverse effect on patients, we propose to optimize nanorobotsassisted targeted drug delivery (TDD) for locoregional treatment of tumor from the perspective of touchable communication channel estimation and waveform design. The drug particles are the information molecules; the loading/injection and unloading of the drug correspond to the transmitting and receiving processes; the concentration-time profile of the drug particles administered corresponds to the signalling pulse...
February 15, 2017: IEEE Transactions on Nanobioscience
Guang Ling, Zhi-Hong Guan, Bin Hu, Qiang Lai, Yonghong Wu
Many biological systems have the conspicuous property to present more than one stable state and diverse rhythmic behaviors. A closed relationship between these complex dynamic behaviors and cyclic genetic structures has been witnessed by pioneering works. In this paper, a typical structure of inhibitory coupled cyclic genetic networks is introduced to further enlighten this mechanism of stability and biological rhythms of living cells. The coupled networks consist two identical cyclic genetic subnetworks, which inhibit each other directly...
February 14, 2017: IEEE Transactions on Nanobioscience
Ryan Eshleman, Rahul Singh
Identifying the temporal progression of a set of biological samples is crucial for comprehending the dynamics of the underlying molecular interactions. It is often also a basic step in data denoising and synchronization. Finally, identifying the progression order is crucial for problems like cell lineage identification, disease progression, tumor classification, and epidemiology and thus impacts the spectrum of disciplines spanning basic biology, drug discovery, and public health. Current methods that attempt solving this problem face difficulty when it is necessary to factor-in complex relationships within the data such as grouping, partial ordering or bifurcating or multifurcating progressions...
February 9, 2017: IEEE Transactions on Nanobioscience
Letu Qingge, Xiaowen Liu, Farong Zhong, Binhai Zhu
In mass spectrometry-based de novo protein sequencing, it is hard to complete the sequence of the whole protein. Motivated by this we study the (one-sided) problem of filling a protein scaffold S with some missing amino acids, given a sequence of contigs none of which is allowed to be altered, with respect to a complete reference protein P of length n, such that the BLOSUM62 score between P and the filled sequence S' is maximized. We show that this problem is polynomial-time solvable in O(n26) time. We also consider the case when the contigs are not of high quality and they are concatenated into an (incomplete) sequence I, where the missing amino acids can be inserted anywhere in I to obtain I', such that the BLOSUM62 score between P and I' is maximized...
February 9, 2017: IEEE Transactions on Nanobioscience
Leyi Wei, Pengwei Xing, Jijun Tang, Quan Zou
Many recent efforts have been made for the development of machine learning based methods for fast and accurate phosphorylation site prediction. Currently, a majority of well-performing methods are based on hybrid information to build prediction models, such as evolutionary information, and disorder information, etc. Unfortunately, this type of methods suffers two major limitations: one is that it would be not much of help for protein phosphorylation site prediction in case of no obvious homology detected; the other is that computing such the complicated information is time-consuming, which probably limits the usage of predictors in practical applications...
January 31, 2017: IEEE Transactions on Nanobioscience
Hesham G Moussa, Ghaleb A Husseini, Nabil Abdel-Jabbar, Salma E Ahmed
The use of echogenic liposomes to deliver chemotherapeutic agents for cancer treatment has gained wide recognition in the last twenty years. Cancerous cells can develop multiple drug resistance (MDR), in part, due to the drop of concentration of chemotherapeutic agents below the therapeutic levels inside the tumor. This suggests that MDR can be reduced by controlling the level of drug release in the diseased area. In this work, a Model Predictive Controller based on Neural Networks is proposed to maintain a constant chemotherapeutic release at the cancer site...
January 30, 2017: IEEE Transactions on Nanobioscience
Emily Flynn, Ileana Streinu
We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple NMR models of the same protein...
January 27, 2017: IEEE Transactions on Nanobioscience
Min Ye, Xiuwei Zhang, Gabriela C Racz, Qijia Jiang, Bernard M E Moret
Modelling the evolution of biological networks is a major challenge. Biological networks are usually represented as graphs; evolutionary events include addition and removal of vertices and edges, but also duplication of vertices and their associated edges. Since duplication is viewed as a primary driver of genomic evolution, recent work has focused on duplication-based models. Missing from these models is any embodiment of modularity, a widely accepted attribute of biological networks. Some models spontaneously generate modular structures, but none is known to maintain and evolve them...
January 19, 2017: IEEE Transactions on Nanobioscience
Malay Bhattacharyya, Soumi Maity, Sanghamitra Bandyopadhyay
Disease dietomics is an emerging area of systems biology that attempts to explore the connections between the dietary habits and diseases. Some of the topical studies highlight that foods might have different impacts over an organism either in progressing a disease (negative association) or in fighting against it (positive association). The association of foods with different diseases can be put together to build a network that might provide a global view of the entire system. Again, such disease-food networks might emerge in a more complex form while considering the disease subtypes individually...
January 16, 2017: IEEE Transactions on Nanobioscience
Akiko Tanaka, Tomoyuki Furubayashi, Hitomi Yamasaki, Katsuko Takano, Mayuko Kawakami, Shunsuke Kimura, Daisuke Inoue, Hidemasa Katsumi, Toshiyasu Sakane, Akira Yamamoto
For nasal drug absorption, powder formulations can be expected to provide many advantages. The first aim of this study was to examine drug absorption following nasal administration of powder formulations in rats. Pharmaceutical excipients are typically added to most powder formulations. The second aim was to investigate the change in nasal drug absorption of powder formulations in the presence of sodium carboxymethyl cellulose (CMC-Na). Model drugs used were norfloxacin (NFX), warfarin (WF), and piroxicam (PXC)...
January 4, 2017: IEEE Transactions on Nanobioscience
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