BIO INFORMATICS AND BIO SCIENCE Research 2018-2019

Chanda Panse and Manali Kshirsagar

ABSTRACT

Gene Regulatory Network (GRN) plays an important role in knowing insight of cellular life cycle. It gives information about at which different environmental conditions genes of particular interest get over expressed or under expressed. Modelling of GRN is nothing but finding interactive relationships between genes. Interaction can be positive or negative. For inference of GRN, time series data provided by Microarray technology is used. Key factors to be considered while constructing GRN are scalability, robustness, reliability and maximum detection of true positive interactions between genes. This paper gives detailed technical review of existing methods applied for building of GRN along with scope for future work.

KEYWORDS

Gene Regulatory Network, Microarray, robustness, scalability, reliability

For More Details: https://wireilla.com/papers/ijbb/V3N3/3313ijbb02.pdf

Victoria L. Fox, Mariofana Milanova and Salim Al-Ali

ABSTRACT

This paper presents a morphological active contour ideal for vascular segmentation in biomedical images. The unenhanced images of vessels and background are successfully segmented using a two-step morphological active contour based upon Chan and Vese’s Active Contour without Edges. Using dilation and erosion as an approximation of curve evolution, the contour provides an efficient, simple, and robust alternative to solving partial differential equations used by traditional level-set Active Contour models. The
proposed method is demonstrated with segmented data set images and compared to results garnered from multiphase Active Contour without Edges, morphological watershed, and Fuzzy C-means segmentations.

KEYWORDS

Active Contour, Morphology, Segmentation, Curve Evolution

For More details: https://wireilla.com/papers/ijbb/V3N3/3313ijbb01.pdf

Sundarapandian Vaidyanathan

ABSTRACT

This paper describes the design of sliding mode controller for the global chaos synchronization of identical Rucklidge chaotic systems (Rucklidge, 1992). Rucklidge chaotic system is one of the paradigms of threedimensional chaotic systems. The stability results derived in this paper for the complete synchronization of the identical Rucklidge chaotic systems via sliding mode control are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the sliding mode control method is very effective and convenient to achieve global chaos synchronization of Rucklidge chaotic systems. Numerical simulations are presented to demonstrate the effectiveness of to the synchronization schemes derived in this paper for the identical Rucklidge chaotic systems.

KEYWORDS
Sliding Mode Control, Chaos Synchronization, Chaotic Systems, Rucklidge Systems

For More details: https://wireilla.com/papers/ijbb/V2N1/2112ijbb03.pdf

V.K. Narendira Kumar and B. Srinivasan

ABSTRACT

Electronic passports have known a wide and fast deployment all around the world since the International Civil Aviation Organization the world has adopted standards whereby passports can store biometric identifiers. The use of biometrics for identification has the potential to make the lives easier, and the world people live in a safer place. The purpose of biometric passports is to prevent the illegal entry of traveler into a specific country and limit the use of counterfeit documents by more accurate identification of an individual. This paper analyses the face, fingerprint, palmprint and iris biometric e-passport design. This papers focus on privacy and personal security of bearers of e-passports, the actual security benefit countries obtained by the introduction of e-passports using face, fingerprint, palmprint and iris recognition systems. Researcher analyzed its main cryptographic features; the face fingerprint, palmprint and iris biometrics currently used with e-passports and considered the surrounding procedures. The paper also provides a security analysis of the e-passport using face fingerprint, palmprint and iris biometric that are intended to provide improved security in protecting biometric information of the epassport bearer.

KEYWORDS

E-Passport, Biometrics, Cryptographic, Face, Fingerprint, Palmprint and Iris.

For More Details: https://wireilla.com/papers/ijbb/V2N1/2112ijbb02.pdf

Abdullah Alshehab,Chiu Tung Wu, Nao Kobayashi

ABSTRACT
Intra-body communication (IBC) is a type of Body Area Network (BAN)that utilizes human body as the medium for data transmission. Thelow power requirements of intra-body communication (IBC) as compared to near field electromagnetic waves showed that it can be a suitable solution for Medical Body AreaNetworks (MBANs) in a mobile health care system.In this paper, we investigate the transmission characteristicsof the human body as a conductor of signals byconsidering different datatransmission rates of multi-point to point network in order to reduce overall power consumption of the BAN.Furthermore, we utilize IBC and propose a new scheme to combines Slotted ALOHA, TDMA, and Reservation ALOHA together to increase the throughput and decrease the delay. By using our new hybrid scheme with the movable boundary designed for health status monitoring, we are able to increase the efficiency of data transmission by prioritizing the more critical data from the sensors.

KEYWORDS

Body area network, Intra-body communications, Hybrid communication scheme

For More details: https://wireilla.com/papers/ijbb/V2N1/2112ijbb01.pdf

Indumathy R and Uma Maheswari S

ABSTRACT

Evolutionary search algorithms are becoming an essential advantage in the algorithmic toolbox for solving multi-dimensional optimization problems in a wide range of bioinformatics problems such as Genome fragment assembly which is a NP-hard problem. In computational biology, one of the most challenging problems is to reconstruct the original DNA sequence from a huge number of fragments, each one being numerous hundred base-pairs (bps) long. Recently it has become common for the
researchers to apply the heuristic search algorithms to solve these kinds of complex problems with the help of combinatorial optimization. A genetic algorithm, the most well-known and representative evolutionary search technique has been the subject of the major part of such applications. Despite the fact that there have been different methods available in the literature, researchers are still facing difficulties in choosing the best method that could solve these problems efficiently and effectively. This paper aims to analyses the existing algorithms, evaluate them, point out the faults of these works and specify the emerging trend.

KEYWORDS

Computational Biology, Human Genome Project, Optimization Problem, DNA Fragment
Assembly, Genetic Algorithms

For More Details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb05.pdf

Shekofeh Yaraghi and Mohammad Davarpanah Jazi

ABSTRACT
Gene expression microarray experiments produce datasets with numerous missing expression value, which can significantly affect the performance of statistical and machine learning algorithms. In this paper, we proposed a novel method based on the fuzzy clustering and the shortest path algorithm for measuring the semantic similarity on GO to estimate missing value to microarray gene expression. In this proposed method, missing values are imputed with values generated from cluster centers. Genes similarity in clustering process resolute based on both the GO structure information and, s property. We have applied the proposed method on two datasets with different percentages of missing values. The experimental results indicate that proposed method provides a higher accuracy of missing value estimation because the semantic similarity obtained by sp algorithm better correlates with the expression similarity than other node-based methods.

KEYWORDS

Missing Value; Semantic Similarity; Fuzzy Clustering; Microarray

For More Details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb04.pdf

Sundarapandian Vaidyanathan

ABSTRACT
This paper solves the output regulation problem of Sprott-I chaotic system, which is one of the classical chaotic systems discovered by J.C. Sprott (1994). Explicitly, for the constant tracking problem, new state feedback control laws have been derived for regulating the output of the Sprott-I chaotic system. Our controller design has been carried out using the regulator equations of C.I. Byrnes and A. Isidori (1990). The output regulation of the Sprott-I chaotic system has important applications in many areas of Science and Engineering. Numerical simulations are shown to illustrate the effectiveness of the control schemes proposed in this paper for the output regulation of the Sprott-I chaotic system.

KEYWORDS

Chaos; Feedback Control; Sprott-I System; Nonlinear Control Systems; Output Regulation.

For More details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb03.pdf

Ashish Bhangale, Navneet Manjhi and Jyoti Bharti

ABSTRACT

The gait signature is extracted directly from the evidence gathering process. This is possible by using a Fourier series to describe the motion of the upper leg and apply temporal evidence gathering techniques to extract the moving model from a sequence of images. The improved classification capability of the phase-weighted magnitude information is verified using statistical analysis of the separation of clusters in the feature space. Furthermore, the technique is shown to be able to handle high levels of occlusion, which is of especial importance in gait as the human body is self-occluding. As such, a new technique has been developed to automatically extract and describe a moving articulated shape, the human leg, and shown its potential in gait as a biometric.

KEYWORDS

Fourier series, sequence of images, classification, phase-weighted magnitude, statistical analysis, occulation, articulated shape, biometric, VHT, HVHT, GAVHT, GA, SHT, CCD, FS & HHT

For More details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb02.pdf

S. Qatawneh, A. Alneaimi, Th. Rawashdeh, M. Muhairat, R. Qahwaji and S. Ipson

ABSTRACT

DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding  proteins also perform important roles in many types of cellular activities. In this paper we describe machine learning systems for the prediction of DNA- binding proteins where a Support Vector Machine and a Cascade Correlation Neural Network are optimized and then compared to determine the learning algorithm that achieves the best prediction performance. The information used for classification is derived from characteristics that include overall charge, patch size and amino acids composition. In total 121 DNA- binding proteins and 238 non-binding proteins are used to build and evaluate the system. For SVM using the ANOVA Kernel with Jack-knife evaluation, an accuracy of 86.7% has been achieved with 91.1% for sensitivity and 85.3% for specificity. For CCNN optimized over the entire dataset with Jack knife evaluation we report an accuracy of 75.4%, while the values of specificity and sensitivity achieved
were 72.3% and 82.6%, respectively.

KEYWORDS

DNA-Binding Proteins, Machine Learning, SVM, CCNN, Jack-knife Technique

For more Details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb01.pdf