Search results for: Dietary protein
490 Effects of Dietary Protein and Lipid Levels on Growth and Body Composition of Juvenile Fancy Carp, Cyprinus carpio var. Koi
Authors: Jin Choi, Zahra Aminikhoei, Yi-Oh Kim, Sang-Min Lee
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A feeding experiment was conducted to determine the optimum dietary protein and lipid levels for juvenile fancy carp. Eight experimental diets were formulated to contain four protein levels (200, 300, 400 and 500 g kg-1) with two lipid levels (70 and 140 g kg-1). Triplicate groups of fish (initial weight, 12.1±0.2 g fish-1) were hand-fed the diets to apparent satiation for 8 weeks. Fish growth performance, feed utilization and feed intake were significantly (P<0.0001) affected by dietary protein level, but not by dietary lipid level (P>0.05). Weight gain and feed efficiency ratio tended to increase as dietary protein level increased up to 400 and 500 g kg-1, respectively. Daily feed intake of fish decreased with increasing dietary protein level and that of fish fed diet contained 500 g kg-1 protein was significantly lower than other fish groups. The protein efficiency ratio of fish fed 400 and 500 g kg-1 protein was lower than that of fish fed 200 and 300 g kg-1 protein. Moisture, crude protein and crude lipid contents of muscle and liver were significantly affected by dietary protein, but not by dietary lipid level (P>0.05). The increase in dietary lipid level resulted in an increase in linoleic acid in liver and muscle paralleled with a decrease in n-3 highly unsaturated fatty acids content in muscle of fish. In considering these results, it was concluded that the diet containing 400 g kg-1 protein with 70 g kg-1 lipid level is optimal for growth and efficient feed utilization of juvenile fancy carp.
Keywords: Fancy carp, Dietary protein, Dietary lipid, Fatty acid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2541489 Effect of Dietary α-Cellulose Levels on the Growth Parameters of Nile Tilapia Oreochromis niloticus Fingerlings
Authors: Keri Alhadi Ighwela, Aziz Bin Ahmad, A. B. Abol-Munafi
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Three purified diets were formulated using fish meal, soya bean, wheat flour, palm oil, minerals and maltose. The carbohydrate in the diets was increased from 5 to 15% by changing the cellulose content to study the effect of dietary carbohydrate level on the growth parameters of Nile tilapia Oreochromis niloticus. The protein and the lipid contents were kept constant in all the diets. The results showed that, weight gain, protein efficiency ratio, net protein utilisation and hepatosomatic index of fish fed the diet containing 15% cellulose were the lowest among all groups. Addition, the fish fed the diet containing 5% cellulose had the best specific growth rate, and food conversion ratio. While, there was no effect of the dietary cellulose levels on condition factor and survival rate. These results indicate that Nile tilapia fingerlings are able to utilize dietary cellulose does not exceed 10% in their feed for optimum growth.Keywords: Dietary cellulose, growth parameters, Nile Tilapia Oreochromis niloticus, purified diets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4689488 Protein-Protein Interaction Detection Based on Substring Sensitivity Measure
Authors: Nazar Zaki, Safaai Deris, Hany Alashwal
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Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.
Keywords: Protein-Protein Interaction, support vector machine, feature extraction, pairwise alignment, Smith-Waterman score.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1925487 Effect of Dietary Chromium Yeast on Thigh Meat Quality of Broiler Chicks in Heat Stress Condition
Authors: Majid Toghyani, Abbas Ali Gheisari, Ali Khodami, Mehdi Toghyani, Mohammad Mohammadrezaei, Ramin Bahadoran
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This experiment was conducted to investigate the effect of different levels of dietary chromium yeast (Cr-yeast) on thigh meat quality of broiler chicks reared under heat stress condition. Two hundred and forty Ross male chickens in heat stress condition (33±3°C) were allocated to five treatments in a completely randomized design. Treatments were supplemented with 0 (control), 200, 400, 800 and 1200 μg kg-1 Cr in the form of Cr yeast. Twelve chicks from each treatment were slaughtered at 42 d, to evaluate moisture, protein, lipid, pH and lipid oxidation of thigh meat. Protein, moisture, lipid and pH of thigh meat were not affected by supplemental Cr. Thigh meat lipid tended to decrease in broilers received 1200 μg kg-1. Storage time increased lipid oxidation of meat (P<0.01). Lipid oxidation of thigh muscle for two days of storage were affected by supplemental Cr and decreased (P<0.05). Results of this study showed that dietary Cr-yeast supplementation improved the thigh meat quality of broiler chicks in heat stress condition.Keywords: Broiler, Heat stress, Chromium yeast, Thigh meat quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2257486 The Diet Adherence in Cardiovascular Disease Risk Factors Patients in the North of Iran Based on the Mediterranean Diet Adherence
Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahboobeh Gholipour, Moona Naghshbandi
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Background and objectives: Before any nutritional intervention, it is necessary to have the prospect of eating habits of people with cardiovascular risk factors. In this study, we assessed the adherence of healthy diet based on Mediterranean dietary pattern and related factors in adults in the north of Iran. Methods: This study was conducted on 550 men and women with cardiovascular risk factors that referred to Heshmat hospital in Rasht, northern Iran. Information was collected by interview and reading medical history and measuring anthropometric indexes. The Mediterranean Diet Adherence Screener was used for assessing dietary adherence, this screener was modified according to religious beliefs and culture of Iran. Results: The mean age of participants was 58±0.38 years. The mean of body mass index was 27±0.01 kg/m2, and the mean of waist circumference was 98±0.2 cm. The mean of dietary adherence was 5.76±0.07. 45% of participants had low adherence, and just 4% had suitable adherence. The mean of dietary adherence in men was significantly higher than women (p=0. 07). Participants in rural area and high educational participants insignificantly had an unsuitable dietary Adherence. There was no significant association between some cardiovascular disease risk factors and dietary adherence. Conclusion: Education to different group about dietary intake correction and using a Mediterranean dietary pattern that is similar to dietary intake in the north of Iran, for controlling cardiovascular disease is necessary.
Keywords: Dietary adherence, Mediterranean dietary pattern, cardiovascular disease, north of Iran.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 974485 An Algebra for Protein Structure Data
Authors: Yanchao Wang, Rajshekhar Sunderraman
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This paper presents an algebraic approach to optimize queries in domain-specific database management system for protein structure data. The approach involves the introduction of several protein structure specific algebraic operators to query the complex data stored in an object-oriented database system. The Protein Algebra provides an extensible set of high-level Genomic Data Types and Protein Data Types along with a comprehensive collection of appropriate genomic and protein functions. The paper also presents a query translator that converts high-level query specifications in algebra into low-level query specifications in Protein-QL, a query language designed to query protein structure data. The query transformation process uses a Protein Ontology that serves the purpose of a dictionary.Keywords: Domain-Specific Data Management, Protein Algebra, Protein Ontology, Protein Structure Data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1530484 One-Class Support Vector Machines for Protein-Protein Interactions Prediction
Authors: Hany Alashwal, Safaai Deris, Razib M. Othman
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Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.Keywords: Bioinformatics, Protein-protein interactions, One-Class Support Vector Machines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1978483 Comparison of Domain and Hydrophobicity Features for the Prediction of Protein-Protein Interactions using Support Vector Machines
Authors: Hany Alashwal, Safaai Deris, Razib M. Othman
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The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.
Keywords: Bioinformatics, protein-protein interactions, support vector machines, protein features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1907482 Predicting Protein Function using Decision Tree
Authors: Manpreet Singh, Parminder Kaur Wadhwa, Surinder Kaur
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The drug discovery process starts with protein identification because proteins are responsible for many functions required for maintenance of life. Protein identification further needs determination of protein function. Proposed method develops a classifier for human protein function prediction. The model uses decision tree for classification process. The protein function is predicted on the basis of matched sequence derived features per each protein function. The research work includes the development of a tool which determines sequence derived features by analyzing different parameters. The other sequence derived features are determined using various web based tools.Keywords: Sequence Derived Features, decision tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1939481 Optimization of Protein Hydrolysate Production Process from Jatropha curcas Cake
Authors: Waraporn Apiwatanapiwat, Pilanee Vaithanomsat, Phanu Somkliang, Taweesiri Malapant
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This was the first document revealing the investigation of protein hydrolysate production optimization from J. curcas cake. Proximate analysis of raw material showed 18.98% protein, 5.31% ash, 8.52% moisture and 12.18% lipid. The appropriate protein hydrolysate production process began with grinding the J. curcas cake into small pieces. Then it was suspended in 2.5% sodium hydroxide solution with ratio between solution/ J. curcas cake at 80:1 (v/w). The hydrolysis reaction was controlled at temperature 50 °C in water bath for 45 minutes. After that, the supernatant (protein hydrolysate) was separated using centrifuge at 8000g for 30 minutes. The maximum yield of resulting protein hydrolysate was 73.27 % with 7.34% moisture, 71.69% total protein, 7.12% lipid, 2.49% ash. The product was also capable of well dissolving in water.Keywords: Production, protein hydrolysate, Jatropha curcas cake, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1941480 Predicting Dietary Practice Behavior among Type 2 Diabetics Using the Theory of Planned Behavior and Mixed Methods Design
Authors: D.O. Omondi, M.K. Walingo, G.M. Mbagaya, L.O.A. Othuon
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This study applied the Theory of Planned Behavior model in predicting dietary behavior among Type 2 diabetics in a Kenyan environment. The study was conducted for three months within the diabetic clinic at Kisii Hospital in Nyanza Province in Kenya and adopted sequential mixed methods design combing both qualitative and quantitative phases. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The results based on the common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within dietary behavior {χ2 = 223.3, df = 77, p = .02, χ2/df = 2.9, n=237; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)}. This implies that the Theory of Planned Behavior holds and forms a framework for promoting dietary practice among Type 2 diabetics.Keywords: Dietary practice, Kenya, Theory of PlannedBehavior, Type 2 diabetes, Mixed Methods Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2086479 Effect of Restaurant Fat on Milk Yield and Composition of Dairy Cows Limit-Fed Concentrate Diet with Free Access to Forage
Authors: Mofleh S. Awawdeh
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Ten lactating multiparous Holstein cows were used in a cross-over design with two dietary treatments and 28-d periods (with 14 d as an adaptation) to study the effect of restaurant fat on milk production and composition. Each cow was offered 14.7 kg DM /d of the basal concentrate diet based on barley and corn (crude protein = 17.7%, neutral detergent fiber = 23.5%, and acid detergent fiber = 5.8% of dry matter) with free access to alfalfa. Dietary treatments were arranged as supplying each cow with 0 (CONTROL) or 150 g/day (RF) of restaurant fat. Supplemental RF did not significantly (P > 0.25) affect milk yield, composition, and composition yields, except for milk fat contents. Milk fat contents were depressed (P < 0.05) with supplemental RF. Our results indicate that RF could depress milk fat without affecting milk yield and that the depression in milk fat in response to RF precedes the depression in milk yield.Keywords: Dairy Cows, Restaurant Fat, Lipids.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1583478 Detecting Remote Protein Evolutionary Relationships via String Scoring Method
Authors: Nazar Zaki, Safaai Deris
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The amount of the information being churned out by the field of biology has jumped manifold and now requires the extensive use of computer techniques for the management of this information. The predominance of biological information such as protein sequence similarity in the biological information sea is key information for detecting protein evolutionary relationship. Protein sequence similarity typically implies homology, which in turn may imply structural and functional similarities. In this work, we propose, a learning method for detecting remote protein homology. The proposed method uses a transformation that converts protein sequence into fixed-dimensional representative feature vectors. Each feature vector records the sensitivity of a protein sequence to a set of amino acids substrings generated from the protein sequences of interest. These features are then used in conjunction with support vector machines for the detection of the protein remote homology. The proposed method is tested and evaluated on two different benchmark protein datasets and it-s able to deliver improvements over most of the existing homology detection methods.
Keywords: Protein homology detection; support vectormachine; string kernel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1381477 Effects of Different Dietary Crude Fiber Levels on the Growth Performance of Finishing Su-Shan Pigs
Authors: Li Bixia, Ren Shouwen, Fu Yanfeng, Tu Feng, Xiaoming Fang, Xueming Wang
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The utilization of dietary crude fiber in different breed pigs is not the same. Su-shan pigs are a new breed formed by crossing Taihu pigs and Yorkshire pigs. In order to understand the resistance of Su-shan pigs to dietary crude fiber, 150 Su-shan pigs with 60 kg of average body weight and similar body conditions were allocated to three groups randomly, and there are 50 pigs in each group. The percentages of dietary crude fiber were 8.35%, 9.10%, and 11.39%, respectively. At the end of the experiment, 15 pigs randomly selected from each group were slaughtered. The results showed as follows: average daily gain of the 9.10% group was higher than that of the 8.35% group and the 11.39% group; there was a significant difference between the 9.10% group and the 8.35% group (p < 0.05. Levels of urea nitrogen, total cholesterol and high density lipoprotein in the 9.10% group were significantly higher than those in the 8.35% group and the 11.39% group (p < 0.05). Ratios of meat to fat in the 9.10% group and the 11.39% group were significantly higher than that in the 8.35% group (p < 0.05). Lean percentage of 9.10% group was higher than that of 8.35% group and 11.39% group, but there was no significant difference in three groups (p > 0.05). The weight of small intestine and large intestine in the 11.39% group was higher than that in the 8.35% group, and the 9.10% group and the difference reached a significant level (p < 0.05). In conclusion, increasing dietary crude fiber properly could reduce fat percentage, and improve the ratio of meat to fat of finishing Su-shan pigs. The digestion and metabolism of dietary crude fiber promoted the development of stomach and intestine of finishing Su-shan pig.
Keywords: Su-Shan pigs, dietary crude fiber, growth performance, serum biochemical indexes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 963476 Can Physical Activity and Dietary Fat Intake Influence Body Mass Index in a Cross-sectional Correlational Design?
Authors: D.O. Omondi, L.O.A. Othuon, G.M. Mbagaya
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The purpose of this study was to determine the influence of physical activity and dietary fat intake on Body Mass Index (BMI) of lecturers within a higher learning institutionalized setting. The study adopted a Cross-sectional Correlational Design and included 120 lecturers selected proportionately by simple random sampling techniques from a population of 600 lecturers. Data was collected using questionnaires, which had sections including physical activity checklist adopted from the international physical activity questionnaire (IPAQ), 24-hour food recall, anthropometric measurements mainly weight and height. Analysis involved the use of bivariate correlations and linear regression. A significant inverse association was registered between BMI and duration (in minutes) spent doing moderate intense physical activity per day (r=-0.322, p<0.01). Physical activity also predicted BMI (r2=0.096, F=13.616, β=-3.22, t=-3.69, n=120, P<0.01). However, the association between Body Mass Index and dietary fat was not significant (r=0.038, p>0.05). Physical activity emerged as a more powerful determinant of BMI compared to dietary fat intake.Keywords: Physical activity, dietary fat intake, Body MassIndex, Kenya.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1701475 The Effect of Different Levels of Seed and Extract of Harmal (Peganum harmala L.) on Immune Responses of Broiler Chicks
Authors: M. Toghyani, A. Ghasemi, S. A. Tabeidian
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The present study was carried out to evaluate the effect of different levels of dietary seed and extract of Harmal (Peganum harmala L.) on immunity of broiler chicks. A total of 350 one-day old broiler chicks (Ross 308) were randomly allocated to five dietary treatments with four replicates pen of 14 birds each. Dietary treatments consisted of control, 1 and 2 g/kg Harmal seed in diet, 100 and 200 mg/L Harmal seed extract in water. Broilers received dietary treatments from 1 to 42 d. Two birds from each pen were randomly weighed and sacrificed at 42 d of age, the relative weight of lymphoid organs (bursa of Fabercius and spleen) to live weight were calculated. Antibody titers against Newcastle and influenza viruses and sheep red blood cell were measured at 30 d of age. Results showed that the relative weights of lymphoid organs were not affected by dietary treatments. Furthermore, antibody titer against Newcastle and influenza viruses as well as sheep red blood cell antigen were significantly (P<0.05) enhanced by feeding Harmal seed and extract. In conclusion, the results indicated that dietary inclusion of Harmal seed and extract enhanced immunological responses in broiler chicks.
Keywords: Broiler chicks, Harmal, immunity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2535474 Consumption Pattern and Dietary Practices of Pregnant Women in Odeda Local Government Area of Ogun State
Authors: Ademuyiwa, M. O., Sanni, S. A.
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The importance of maternal nutritional practices during pregnancy cannot be overemphasized. This paper assessed the consumption pattern and dietary practices of 50 pregnant women selected using purposive sampling technique from three health care centres (Primary Health Care Centre, Obantoko; Primary Health Care Centre Alabata; and the General Hospital, Odeda) in Odeda Local Government Area of Ogun State, Nigeria. Structured questionnaire was used to elicit information on socioeconomic status, consumption pattern and dietary practices. Data were analyzed using the Statistical Package for Social Sciences (SPSS, 17). The results indicated that about 58% of the pregnant women were below the age of 30 while 42% were ages 28-40 years. Only 16% had tertiary education while (38%) had secondary education, 52% earn income through petty trading. On food intake, 52% got their energy source from rice on a daily basis, followed by pap (38%) and eko (34%). For protein intake, 36% consumed bean cake on a daily basis while 66% consumed moinmoin 2-3 times a week. Orange (48%) and Green Leafy vegetable (40%) accounted for the mostly consumed fruit and vegetable on daily basis. In terms of animal origin, fish (76%), meat (58%) and eggs (30%) were consumed daily, while chicken and snail were consumed occasionally by 54% and 42%, respectively. Forty-six percent (46%) of the pregnant women eat more than three times daily; while 60% of the women eat outside their homes with 42% respondents eat out lunch and only two percent least eaten out dinner. It is important to increase in awareness campaign to sensitize the pregnant women on the importance of good nutrition especially fruits, vegetables and dairy products.
Keywords: Consumption Pattern, Dietary Practices, Pregnant, Women, Nigeria.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4905473 UTMGO: A Tool for Searching a Group of Semantically Related Gene Ontology Terms and Application to Annotation of Anonymous Protein Sequence
Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias
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Gene Ontology terms have been actively used to annotate various protein sets. SWISS-PROT, TrEMBL, and InterPro are protein databases that are annotated according to the Gene Ontology terms. However, direct implementation of the Gene Ontology terms for annotation of anonymous protein sequences is not easy, especially for species not commonly represented in biological databases. UTMGO is developed as a tool that allows the user to quickly and easily search for a group of semantically related Gene Ontology terms. The applicability of the UTMGO is demonstrated by applying it to annotation of anonymous protein sequence. The extended UTMGO uses the Gene Ontology terms together with protein sequences associated with the terms to perform the annotation task. GOPET, GOtcha, GoFigure, and JAFA are used to compare the performance of the extended UTMGO.Keywords: Anonymous protein sequence, Gene Ontology, Protein sequence annotation, Protein sequence alignment
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1432472 A Bayesian Kernel for the Prediction of Protein- Protein Interactions
Authors: Hany Alashwal, Safaai Deris, Razib M. Othman
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Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.Keywords: Bioinformatics, Protein-protein interactions, Bayesian Kernel, Support Vector Machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2154471 Protein Delivery from Polymeric Nanoparticles
Authors: G. Spada, E. Gavini, P. Giunchedi
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Aim of this work was to compare the efficacy of two loading methods of proteins onto polymeric nanocarriers: adsorption and encapsulation methods. Preliminary studies of protein loading were done using Bovine Serum Albumin (BSA) as model protein. Nanocarriers were prepared starting from polylactic co-glycolic acid (PLGA) polymer; production methods used are two different variants of emulsion evaporation method. Nanoparticles obtained were analyzed in terms of dimensions by Dynamic Light Scattering and Loading Efficiency of BSA by Bradford Assay. Loaded nanoparticles were then submitted to in-vitro protein dissolution test in order to study the effect of the delivery system on the release rate of the protein.Keywords: Drug delivery, nanoparticles, PLGA, proteinadsorption, protein encapsulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2497470 Dietary Habit and Anthropometric Status in Hypertensive Patients Compared to Normotensive Participants in the North of Iran
Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahbobeh Gholipour
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Hypertension is one of the important reasons of morbidity and mortality in countries, including Iran. It has been shown that hypertension is a consequence of the interaction of genetics and environment. Nutrients have important roles in the controlling of blood pressure. We assessed dietary habit and anthropometric status in patients with hypertension in the north of Iran, and that have special dietary habit and according to their culture. This study was conducted on 127 patients with newly recognized hypertension and the 120 normotensive participants. Anthropometric status was measured and demographic characteristics, and medical condition were collected by valid questionnaires and dietary habit assessment was assessed with 3-day food recall (two weekdays and one weekend). The mean age of participants was 58 ± 6.7 years. The mean level of energy intake, saturated fat, vitamin D, potassium, zinc, dietary fiber, vitamin C, calcium, phosphorus, copper and magnesium was significantly lower in the hypertensive group compared to the control (p < 0.05). After adjusting for energy intake, positive association was observe between hypertension and some dietary nutrients including; Cholesterol [OR: 1.1, P: 0.001, B: 0.06], fiber [OR: 1.6, P: 0.001, B: 1.8], vitamin D [OR: 2.6, P: 0.006, B: 0.9] and zinc [OR: 1.4, P: 0.006, B: 0.3] intake. Logistic regression analysis showed that there was not significant association between hypertension, weight and waist circumference. In our study, the mean intake of some nutrients was lower in the hypertensive individuals compared to the normotensive individual. Health training about suitable dietary habits and easier access to vitamin D supplementation in patients with hypertension are cost-effective tools to improve outcomes in Iran.
Keywords: Hypertension, dietary intake, weight, waist circumference, North of Iran.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 724469 Protein Graph Partitioning by Mutually Maximization of cycle-distributions
Authors: Frank Emmert Streib
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The classification of the protein structure is commonly not performed for the whole protein but for structural domains, i.e., compact functional units preserved during evolution. Hence, a first step to a protein structure classification is the separation of the protein into its domains. We approach the problem of protein domain identification by proposing a novel graph theoretical algorithm. We represent the protein structure as an undirected, unweighted and unlabeled graph which nodes correspond the secondary structure elements of the protein. This graph is call the protein graph. The domains are then identified as partitions of the graph corresponding to vertices sets obtained by the maximization of an objective function, which mutually maximizes the cycle distributions found in the partitions of the graph. Our algorithm does not utilize any other kind of information besides the cycle-distribution to find the partitions. If a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. As stop criterion, we calculate numerically a significance level which indicates the stability of the predicted partition against a random rewiring of the protein graph. Hence, our algorithm terminates automatically its iterative application. We present results for one and two domain proteins and compare our results with the manually assigned domains by the SCOP database and differences are discussed.Keywords: Graph partitioning, unweighted graph, protein domains.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1343468 Critical Assessment of Scoring Schemes for Protein-Protein Docking Predictions
Authors: Dhananjay C. Joshi, Jung-Hsin Lin
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Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.
Keywords: protein-protein docking, protein-protein interaction, molecular mechanics energetics, Poisson-Boltzmann calculations
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1791467 Parallezation Protein Sequence Similarity Algorithms using Remote Method Interface
Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain
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One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1893466 Effect of Tomato Pomace and Fibrolytic Enzyme on Egg Production and Egg Quality
Authors: K. Vasupen, S. Wongsuthavas, S. Bureenok, B. Saenmahayak, K. Ampaporn, C. Yuangklang
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This study was designed to determine effect of supplemented tomato pomace and fobrolytic enzyme on egg production and egg quality. A total of 40 CP brown laying hens (95 week old) were used in completely randomized design in 2x2 factorial arrangement with or without enzyme supplementation. Four dietary treatments included: Control (C), Fibrolytic enzyme (FE), 10% Tomato pomace (TP), and Fibrolytic enzyme + 10 % Tomato pomace (FE+TP). Each of the four dietary treatments was fed up to 30 days (10 birds/treatment). Live performance, egg production, egg weight and quality were determined for whole period. Dietary treatments had no effect (P>0.05) on live performance, egg weight, yolk color, and egg production. Therefore, laying hens fed diets with fibrolytic enzyme were significantly (P<0.05) increased yolk weight (17.37 g) as compared to other treatments. Additional of dietary tomato pomace had reduced capital costs for egg production.Keywords: Hen, Tomato Pomace, Fibrolytic Enzyme, Egg Quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1779465 Analysis of Formyl Peptide Receptor 1 Protein Value as an Indicator of Neutrophil Chemotaxis Dysfunction in Aggressive Periodontitis
Authors: Prajna Metta, Yanti Rusyanti, Nunung Rusminah, Bremmy Laksono
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The decrease of neutrophil chemotaxis function may cause increased susceptibility to aggressive periodontitis (AP). Neutrophil chemotaxis is affected by formyl peptide receptor 1 (FPR1), which when activated will respond to bacterial chemotactic peptide formyl methionyl leusyl phenylalanine (FMLP). FPR1 protein value is decreased in response to a wide number of inflammatory stimuli in AP patients. This study was aimed to assess the alteration of FPR1 protein value in AP patients and if FPR1 protein value could be used as an indicator of neutrophil chemotaxis dysfunction in AP. This is a case control study with 20 AP patients and 20 control subjects. Three milliliters of peripheral blood were drawn and analyzed for FPR1 protein value with ELISA. The data were statistically analyzed with Mann-Whitney test (p>0,05). Results showed that the mean value of FPR1 protein value in AP group is 0,353 pg/mL (0,11 to 1,18 pg/mL) and the mean value of FPR1 protein value in control group is 0,296 pg/mL (0,05 to 0,88 pg/mL). P value 0,787 > 0,05 suggested that there is no significant difference of FPR1 protein value in both groups. The present study suggests that FPR1 protein value has no significance alteration in AP patients and could not be used as an indicator of neutrophil chemotaxis dysfunction.
Keywords: Aggressive periodontitis, chemotaxis dysfunction, FPR1 protein value, neutrophil.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 830464 Selection of Pichia kudriavzevii Strain for the Production of Single-Cell Protein from Cassava Processing Waste
Authors: Phakamas Rachamontree, Theerawut Phusantisampan, Natthakorn Woravutthikul, Peerapong Pornwongthong, Malinee Sriariyanun
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A total of 115 yeast strains isolated from local cassava processing wastes were measured for crude protein content. Among these strains, the strain MSY-2 possessed the highest protein concentration (>3.5 mg protein/mL). By using molecular identification tools, it was identified to be a strain of Pichia kudriavzevii based on similarity of D1/D2 domain of 26S rDNA region. In this study, to optimize the protein production by MSY-2 strain, Response Surface Methodology (RSM) was applied. The tested parameters were the carbon content, nitrogen content, and incubation time. Here, the value of regression coefficient (R2) = 0.7194 could be explained by the model which is high to support the significance of the model. Under the optimal condition, the protein content was produced up to 3.77 g per L of the culture and MSY-2 strain contains 66.8 g protein per 100 g of cell dry weight. These results revealed the plausibility of applying the novel strain of yeast in single-cell protein production.Keywords: Single cell protein, response surface methodology, yeast, cassava processing waste.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2666463 Diabetes Mellitus and Food Balance in the Kingdom of Saudi Arabia
Authors: Aljabryn Dalal Hamad
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The present explanatory study concerns with the relation between Diabetes Mellitus and Food Balance in the Kingdom of Saudi Arabia during 2005-2010, using published data. Results illustrated that Saudi citizen daily protein consumption (DPC) during 2005-2007 (g/capita/day) is higher than the average global consumption level of protein with 15.27%, daily fat consumption (DFC) with 24.56% and daily energy consumption (DEC) with 16.93% and increases than recommended level by International Nutrition Organizations (INO) with 56% for protein, 60.49% for fat and 27.37% for energy. On the other hand, DPC per capita in Saudi Arabia decreased during the period 2008-2010 from 88.3 to 82.36 gram/ day. Moreover, DFC per capita in Saudi Arabia decreased during the period 2008-2010 from 3247.90 to 3176.43 Cal/capita/ day, and daily energy consumption (DEC) of Saudi citizen increases than world consumption with 16.93%, whereas increases with 27.37% than INO. Despite this, DPC, DFC and DEC per capita in Saudi Arabia still higher than world mean. On the other side, results illustrated that the number of diabetic patients in Saudi Arabia during the same period (2005-2010). The curve of diabetic patient’s number in Saudi Arabia during 2005-2010 is regular ascending with increasing level ranged between 7.10% in 2005 and 12.44% in 2010. It is essential to devise Saudi National programs to educate the public about the relation of food balances and diabetes so it could be avoided, and provide citizens with healthy dietary balances tables.Keywords: Diabetes Mellitus, Food Balance, Energy, Fat, Protein, Saudi Arabia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1510462 Effects of Functional Protein on Osteoblasts in Rat
Authors: Jie Sun, Guoyou Yin, Xianqing Zhang, Qiusheng She, Zhaohui Xie, Lanying Chen, Anfang Zhao
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To assess the effects of functional protein on osteoblast, Large quantity of high-purity osteoblasts had been cultivated successfully by adopting sequential enzyme digestion. The growth curve of osteoblasts was protracted by cell counting. Proliferation of osteoblasts was assessed by MTT colorimetry. The experimental results show the functional protein can enhance proliferation, the properties of adhesion and discuss the effect of osteopontin on osteoblast.
Keywords: functional protein, osteoblast, MTT
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1232461 Improving Protein-Protein Interaction Prediction by Using Encoding Strategies and Random Indices
Authors: Essam Al-Daoud
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A New features are extracted and compared to improve the prediction of protein-protein interactions. The basic idea is to select and use the best set of features from the Tensor matrices that are produced by the frequency vectors of the protein sequences. Three set of features are compared, the first set is based on the indices that are the most common in the interacting proteins, the second set is based on the indices that tend to be common in the interacting and non-interacting proteins, and the third set is constructed by using random indices. Moreover, three encoding strategies are compared; that are based on the amino asides polarity, structure, and chemical properties. The experimental results indicate that the highest accuracy can be obtained by using random indices with chemical properties encoding strategy and support vector machine.Keywords: protein-protein interactions, random indices, encoding strategies, support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1555