Volume 19, number 1
Bioinformatics
In silico Analysis of Candidate Genes Involved in Sanfilippo Syndrome5-14
Mehreen Zaka, Mawra Komal, Shagufta Shafique, Shaheen Shahzad
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Sanfilippo syndrome is an autosomal recessive lysosomal storage disorder, caused by the deficiency of enzymes that play an important role in degradation of glycosaminoglycans and also called mucopolysaccharidosis III. Mucopolysaccharidosis is genetic disorder. Here, we searched the candidate genes for Sanfilippo syndrome by using BLAST with the query sequence. As no suitable homology was found against the query sequence we moved towards threading approach. The threading approach was carried out by employing online CPH models and LOMETS tools. Through present research, domains of the proteins were predicted by utilizing the Domain Sweep tools, GNS and two domains were reported. Motif search reported the maximum number of motifs for Type D protein as compared to other types. All four proteins were totally soluble proteins and no transmembrane domains were found. In future, these results and predicted 3D structures can be used for the molecular docking studies, binding activities and protein-protein interactions for all the four types of Sanfilippo syndrome.
In silico Structural and Functional Annotation of Mycoplasma genitalium Hypothetical Protein MG_37715-24
Sudip Paul, Moumoni Saha, Nikhil Chandra Bhoumik, Sattya Narayan Talukdar
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Mycoplasma genitalium, a Gram-positive sexually transmitted pathogen, has been associated with urethritis in men and several inflammatory reproductive tract syndromes in women including cervicitis, pelvic inflammatory disease, and infertility. The complete sequence of the M. genitalium G37 genome revealed that it consists of 94 hypothetical proteins with unknown function in addition to functional proteins. In the present study, the MG_377 hypothetical protein of M. genitalium was selected for analyzing and modeling by different bioinformatics tools and databases. According to primary and secondary structure analyses, MG_377 is a stable hydrophilic protein containing a significant proportion of α-helices; besides, it is a cytoplasmic protein based on subcellular localization predictions. Homology modeling method was applied to generate its 3D structure using SWISS-MODEL server where the template PDB 1ZXJ with 84.4% sequence identity with the hypothetical protein was exploited. Several evaluations of quality assessment and validation parameters specified the generated protein model as reliable with fairly good quality. Functional genomics analysis carried out by InterProScan, Pfam and NCBI-CDD suggested that the hypothetical protein may contain Trigger factor/SurA domain. Moreover, comparative genomics analysis recommended MG_377 as a non-homologous protein essential for the organism. Further experimental validation would help to identify the actual function of MG_377 as well as to confirm the utility of the protein as drug targets.
A Modified Machine Learning Method Used in Protein Prediction in Bioinformatics25-36
Chengduan Wang
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Biological information resources have been growing rapidly with the development of biological science and technology, and the development of computer technology and the Internet has made large scale data storage, processing and transmission possible. Machine learning is often used to learn from experience and get useful information. Protein prediction is a main part of biological information, and many prediction methods have been proposed. However, improving the prediction success rate is always a research goal. In this paper, machine learning techniques are used in bioinformatics for protein prediction, and the support vector machine algorithm is used to develop a new prediction algorithm. This method is combinatorial. Two data sets are used to verify the success rate of the modified algorithm, and the results show that the algorithm has a higher success rate. The modified algorithm can be effectively used in protein prediction.
Employing Power Graph Analysis to Facilitate Modeling Molecular Interaction Networks37-42
Momchil Nenov, Svetoslav Nikolov
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Mathematical modeling is used to explore and understand complex systems ranging from weather patterns to social networks to gene-expression regulatory mechanisms. There is an upper limit to the amount of details that can be reflected in a model imposed by finite computational resources. Thus, there are methods to reduce the complexity of the modeled system to its most significant parameters. We discuss the suitability of clustering techniques, in particular Power Graph Analysis as an intermediate step of modeling.
Bioprocess systems
Uncertainty Estimator based Nonlinear Feedback Control for Tracking Trajectories in a Class of Continuous Bioreactor43-60
Maria Isabel Neria-Gonzále, Ricardo Aguilar-López
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The main goal of this work is presents an alternative design of a class of nonlinear controller for tracking trajectories in a class of continuous bioreactor. It is assumed that the reaction rate of the controlled variable is unknown, therefore an uncertainty estimator is proposed to infer this important term, and the observer is coupled with a class of nonlinear feedback. The considered controller contains a class of continuous sigmoid feedback in order to provide smooth closed-loop response of the considered bioreactor. A kinetic model of a sulfate-reducing system is experimentally corroborated and is employed as a benchmark for further modeling and simulation of the continuous operation. A linear PI controller, a class of sliding-mode controller and the proposed one are compared and it is show that the proposed controller yields the best performance. The closed-loop behavior of the process is analyzed via numerical experiments.
Effect of the Introduction of Chrysanthemum on the Nutritional and Sensory Properties of Cabernet Sauvignon Red Wine61-68
Jun Liu, Feng Ying Li, Jing Chuan Li, Yan Xiang Sun, Rui Feng Han, Ying Zhen Gong
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In this paper we propose a new wine technology where dried chrysanthemum is introduced during the process of fermentation of wine. This technology sets an example of a blend between exotic wine culture and traditional Chinese tea culture. The influence on the chemical and sensory properties of wine due to the addition of different amounts of chrysanthemum at different fermentation periods was studied. In all the wine with added chrysanthemum the content of both polyphenols and flavones obviously increased. The wine of T1 and T2 had a higher content of polyphenols and flavones than others, due to thermomaceration, whereas those in the wine of T2 were the highest, due to the technique of squeezing juice. The sensory quality of T3, without the techniques of thermomaceration and squeezing juice, was optimal, with characteristics such as a ruby color, fuller aroma, and a lighter flowery texture. Therefore, T3 was defined as the optimum of chrysanthemum adding procedures. With the increase of chrysanthemum addition, both flavones content and polyphenols content of the obtained wine first increased, and then decreased.
Biomedical systems
Quality of Care and Services of a Public Hospital: Awareness and Assessment69-78
Abdel-ilah Aziane, Mohamed El Yachioui, Aboubaker El Hessni
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In order to give everyone access to quality care, this study attempts to make quality awareness, highlighting the importance of the implementation of the quality management system in health care facilities. The objective of our work is to make a quality awareness, to analyze the current situation and to provide recommendations. The analysis of the existing situation consists of identifying, describing, and analyzing the key processes implemented, listing the dysfunctions, classifying them, deciding on the corresponding actions and putting in place indicators and dashboards, which will help track improvements. The overall situation of the hospital regarding the requirements of ISO 9001 indicated a respect of about 28% of the requirements of the standard. The state of the premises of the establishment does not indicate a clear organization at the hospital. The hospital environment is a prerequisite to the establishment of a system of quality management that enables you to deploy a clear and shared policy to improve the quality of care and services.
Design and Analysis of Low Cost Electro-dermal Response System Using Texas Instrument's MSP430 Value Line Launchpad79-94
Sumanth Reddy Yeddula, Gleb V. Tcheslavski
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Electro-dermal Response (EDR) is one of the important bioelectric signals used in various applications and research studies in the multitude of disciplines, such as Psychophysiology and other areas of Neuroscience. In present paper, a low cost EDR system is designed using Texas Instrument's MSP430 Value Line Launchpad with a general potential divider circuit as the EDR sensor. Throughout this paper, much emphasis is laid out on developing an inexpensive system that shall be easily affordable while offering quality measurements. The system is well incorporated to have a decently accurate and fast data acquisition system, good communication capability with PC for storage and analysis. The developed prototype was used in performing two experiments related to the effects of Deep Breath and Visual Stimulus on EDR data, which gave substantiating results as per the theory.
Artificial Leg Design and Control Research of a Biped Robot with Heterogeneous Legs Based on PID Control Algorithm95-106
Hualong Xie, Keli Chen, Yuying Yang, Fei Li
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A biped robot with heterogeneous legs (BRHL) is proposed to provide an ideal test-bed for intelligent bionic legs (IBL). To make artificial leg gait better suited to a human, a four-bar mechanism is used as its knee joint, and a pneumatic artificial muscle (PAM) is used as its driving source. The static mathematical model of PAM is established and the mechanical model of a single degree of freedom of a knee joint driven by PAM is analyzed. A control simulation of an artificial leg based on PID control algorithm is carried out and the simulation results indicate that the artificial leg can simulate precisely a normal human walking gait.
Recognition of Osteoporosis Based on Texture Analysis and a Support Vector Machine107-118
Jie Cai, Tian-Xiu Wu, Ke Zhou, Wende Li
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To explore a new approach for osteoporosis recognition with images, a texture analysis was made of 27 bone tissue images (16 of which from a SHAM group, and 11 from an OVX group). Texture features were then extracted through a co-occurrence matrix and a run-length matrix, and the texture features with significant differences between the two groups were chosen and used as the features in the classification course based on a Support Vector Machine (SVM). The results show that there are obvious statistic differences between the SHAM group and the OVX group in terms of texture features. Furthermore, the highest recognition accuracy was achieved at 92.59%. A SVM based on a linear function showed the highest accuracy rate and the lowest error rate in recognition. This new approach can be used to recognize osteoporosis effectively and thus can provide a valuable reference to the clinical application in osteoporosis diagnosis with medical images.

Sponsored by National Science Fund of Bulgaria, Grant No DNP 04-35

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