Search results for: gene name recognition

Authors: Shalu Jain, Anju Bansal, Anup Kumar, Sunita Saxena

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Objectives: The novel TMPRSS2:ERG gene fusion is a common somatic event in prostate cancer that in some studies is linked with a more aggressive disease phenotype. Thus, this study aims to determine whether clinical variables are associated with the presence of TMPRSS2:ERG-fusion gene transcript in Indian patients of prostate cancer. Methods: We evaluated the clinical variables with presence and absence of TMPRSS2:ERG gene fusion in prostate cancer and BPH association of clinical patients. Patients referred for prostate biopsy because of abnormal DRE or/and elevated sPSA were enrolled for this prospective clinical study. TMPRSS2:ERG mRNA copies in samples were quantified using a Taqman chemistry by real time PCR assay in prostate biopsy samples (N=42). The T2:ERG assay detects the gene fusion mRNA isoform TMPRSS2 exon1 to ERG exon4. Results: Histopathology report has confirmed 25 cases as prostate cancer adenocarcinoma (PCa) and 17 patients as benign prostate hyperplasia (BPH). Out of 25 PCa cases, 16 (64%) were T2: ERG fusion positive. All 17 BPH controls were fusion negative. The T2:ERG fusion transcript was exclusively specific for prostate cancer as no case of BPH was detected having T2:ERG fusion, showing 100% specificity. The positive predictive value of fusion marker for prostate cancer is thus 100% and the negative predictive value is 65.3%. The T2:ERG fusion marker is significantly associated with clinical variables like no. of positive cores in prostate biopsy, Gleason score, serum PSA, perineural invasion, perivascular invasion and periprostatic fat involvement. Conclusions: Prostate cancer is a heterogeneous disease that may be defined by molecular subtypes such as the TMPRSS2:ERG fusion. In the present prospective study, the T2:ERG quantitative assay demonstrated high specificity for predicting biopsy outcome; sensitivity was similar to the prevalence of T2:ERG gene fusions in prostate tumors. These data suggest that further improvement in diagnostic accuracy could be achieved using a nomogram that combines T2:ERG with other markers and risk factors for prostate cancer.

Keywords: prostate cancer, genetic rearrangement, TMPRSS2:ERG fusion, clinical variables

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Authors: Zerrin Orbak, Busra Demir

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Osteopetrosis is a rare genetic disease characterized by impaired bone resorption and increased bone sclerosis. Clinical presentation is very different in osteopetrosis. It can be asymptomatic or can be seen with typical symptoms. Here, a case of osteopetrosis was presented when evaluated for nystagmus. She was 10 months old. Parents were second-degree relatives. On physical examination, pigeon chest deformity and horizontal nystagmus were observed. There was a failure of thrive but no fracture. The cardiovascular examination was normal. Cranial, vertebral and long bone roentgenograms revealed characteristic deformities of osteopetrosis and diffuse sclerosis. The diagnosis was confirmed by genetic testing. A Homozygous mutation was detected in the TNFRSF11A gene (c.508A>G p.(Arg170Gly)). RANKL is encoded by the tumor necrosis factor ligand superfamily member 11 (TNFSF11) gene, and the binding to its receptor RANK, encoded by the TNFRSF11A gene, determines the activation of the downstream pathway that drives osteoclast differentiation and activation (51). The complete absence of osteoclasts is the key feature of the osteoclast-poor form of osteopetrosis (46). Patients are characterized by the absence of TRAP-positive osteoclasts in bone biopsies. The osteoclast-poor subtype of osteopetrosis caused by mutations in TNFSF11 gene is ultra-rare in humans. Clinical presentation is usually severe, with onset in early infancy or in fetal life. But here, a case was presented with horizontal nystagmus. A case presented with horizontal nystagmus, which was evaluated by neurology and diagnosed incidentally, was shared.

Keywords: osteopetrosis, nystagmus, bone, osteoclast-poor

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Authors: Alaaeldin Hamdy Ahmed Mohammed

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Introduction: This study examines sports’ fans and non-interested public perception and recognition of the problems that have negative impacts upon the Egyptian sports, particularly football, through caricatures. Eight caricature paintings were designed to express eight problems affecting the Egyptian sports and its development. These paintings were distributed on two groups of the fans and the non-interested public. Methods: The study was limited to eight caricatures representing the eight issues which are: the impact of stopping the sports activity on athletes, the effect of clubs’ disagreement, fanaticism between the members of the ultras of different clubs, the negative impact of the mingling of politics into sports, the negative role of the clubs affects the professionalism of the promising players, the conflict between the national organization responsible for sports, the breaking in of the fans to the playgrounds, the impact of the lack of planning on the national team. The Results: The results showed that both sports fans and those who are not interested in sports recognized the problems that the caricatures refer to and criticizes exaggeration although the rate was higher for the fans. These caricatures contributed also in their recognition of the danger of the negative impact of these problems on the Egyptian sports, particularly football which is the most common at the Egyptian sports fans. Discussion: This finding echoes the conclusion that caricatures are distinctive in the adults’ facial stimuli that are either systematically exaggerated recognition of them.

Keywords: caricature, fans, football, sports

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

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Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

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The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Saurabh Farkya, Govinda Surampudi

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Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

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Authors: Bindu I. Somarajan, Viney Gupta, Gagandeep Kaur Walia, Jasbir Kaur, Sunil Kumar, Shikha Gupta, Abadh K. Chaurasia, Dinesh Gupa, Abhinav Kaushik, Aditi Mehta, Vipin Gupta, Arundhati Sharma

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Background: Juvenile onset primary open angle glaucoma (JOAG), affects individuals under the age of 40 years. Studies on a few families of JOAG, that led to the discovery of the Myocilin gene, reported the disease to have an autosomal dominant pattern of inheritance. However, sporadic forms of JOAG been seen to be more common in some populations. Most pathological homozygous mutations in the CYP1B1 gene associated with JOAG have been seen among sporadic cases. Given the higher prevalence of sporadic JOAG cases in our population, we aimed to look for common mutations E229K and R368H, the two most common variants in the CYP1B1 gene associated with glaucoma. Objective: To determine the frequency and evaluate genotype phenotype correlation of CYP1B1 E229K and R368H mutations in a cohort of 120 sporadic Juvenile open angle glaucoma patients.Methods: Unrelated JOAG patients whose first degree relatives had been examined and found to be unaffected were included in the study. The patients and their parents were screened for E229K and R368H mutations. The phenotypic characteristics were compared between probands with and with out these mutations by SPSS v16. Results: Out of 120 JOAG patients included in the study, the E229K mutation was seen in 9 probands (7.5%) and R368H in 7 (5.8%). The average age of onset of the disease (p=0.3) and the highest untreated IOP (p=0.4) among those carrying mutations was not significantly different from those who did not have these mutations. The proportion of probands with angle dysgenesis among those with E229K and R368H mutations was 70% (11 out of 16) in comparison to 65% (67 out of 104) of those who did not harbour these mutations (p=0.56). Similarly the probands with moderate to high myopia among those with E229K and R368H mutations was 20% (3 out of 16) in comparison to 18% (18 out of 104) of those who did not harbour these mutations(p=0.59). Conclusion: The frequency of E229K and R368H mutations of the CYP1B1 gene is low even among sporadic JOAG patients. Moreover there is no clinical correlation between the presence of these mutations and disease severity

Keywords: CYP1B1, gene, IOP, JOAG, mutation

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Authors: C. Kridtayopas, W. Danvilai, P. Sopannarath, A. Kayan, W. Loongyai

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Both Betong chicken (KU Line) and Thai Native chickens were the high quality of the meat and low carcass fat compared to broiler chickens. The objective of this study was to determine the growth performance, carcass characteristic, meat quality and association of polymorphism in the ApoVLDL-II gene with fat accumulation in the female broiler, Thai Native and Betong (KU line) chickens at 4-14 weeks. The chickens were used and reared under the same environment and management (100 chicks per breed). The results showed that body weight (BW) of broiler chickens was significantly higher than Thai Native and Betong (KU line) chickens (P < 0.01) through all the experiment. At 4-8 weeks of age, feed conversion ratio (FCR) of broiler chickens was significantly better than Thai Native and Betong (KU line) chickens (P < 0.01), then increased at week 8-14. The percentage of breast, abdominal fat and subcutaneous fat of broiler chickens was significantly greater than Thai Native and Betong (KU line) chickens (P < 0.01). However, Thai Native chickens showed the highest percentage of liver (P < 0.01) when compared to other breeds. In addition, the percentage of wing of Thai Native and Betong (KU line) chickens were significantly (P < 0.01) higher than broiler chickens. Meat quality was also determined and found that, pH of breast meat left from slaughter 45 minutes (pH45) and 24 hours (pH24) of broiler was significantly higher than Thai Native and Betong (KU line) (P < 0.01) whereas the percentage of drip loss, thawing loss, cooking loss and shear force was not significantly different between breeds. The polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique was used to genotype the polymorphism in the ApoVLDL-II gene in the broiler, Thai Native and Betong (KU line) chickens. The results found that, the polymorphism in the ApoVLDL-II gene at VLDL6 loci was not associated with fat accumulation in those studied population.

Keywords: ApoVLDL-II gene, Betong (KU line) chickens, broiler chickens, carcass characteristic, growth performance, meat quality, Thai native chickens

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Authors: Vivian A. Panes, Raymond John S. Rebong, Miel Q. Diaz

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Moringa oleifera Lam. is known mainly for its high nutritional value and medicinal properties contributing to its popular reputation as a 'miracle plant' in the tropical climates where it usually grows. The main objective of this study is to discover the genes and gene products involved in abiotic stress-induced activity that may impact the M. oleifera Lam. mature seeds as well as their corresponding functions. In this study, RNA-sequencing and de novo transcriptome assembly were performed using two assemblers, Trinity and Oases, which produced 177,417 and 120,818 contigs respectively. These transcripts were then subjected to various bioinformatics tools such as Blast2GO, UniProt, KEGG, and COG for gene annotation and the analysis of relevant metabolic pathways. Furthermore, FPKM analysis was performed to identify gene expression levels. The sequences were filtered according to the 'response to stress' GO term since this study dealt with stress response. Clustered Orthologous Groups (COG) showed that the highest frequencies of stress response gene functions were those of cytoskeleton which make up approximately 14% and 23% of stress-related sequences under Trinity and Oases respectively, recombination, repair and replication at 11% and 14% respectively, carbohydrate transport and metabolism at 23% and 9% respectively and defense mechanisms 16% and 12% respectively. KEGG pathway analysis determined the most abundant stress-response genes in the phenylpropanoid biosynthesis at counts of 187 and 166 pathways for Oases and Trinity respectively, purine metabolism at 123 and 230 pathways, and biosynthesis of antibiotics at 105 and 102. Unique and cumulative GO term counts revealed that majority of the stress response genes belonged to the category of cellular response to stress at cumulative counts of 1,487 to 2,187 for Oases and Trinity respectively, defense response at 754 and 1,255, and response to heat at 213 and 208, response to water deprivation at 229 and 228, and oxidative stress at 508 and 488. Lastly, FPKM was used to determine the levels of expression of each stress response gene. The most upregulated gene encodes for thiamine thiazole synthase chloroplastic-like enzyme which plays a significant role in DNA damage tolerance. Data analysis implies that M. oleifera stress response genes are directed towards the effects of climate change more than other stresses indicating the potential of M. oleifera for cultivation in harsh environments because it is resistant to climate change, pathogens, and foreign invaders.

Keywords: stress response, genes, Moringa oleifera, transcriptomics

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Authors: Felicia Segeth, Florian G. Klein, Lea Berger, Andreas Kolk, Per S. Holm

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The entry of oncolytic viruses (OVs) into clinical application opens groundbreaking changes in current and future treatment regimens. However, despite their potent anti-cancer activity in vitro, clinical studies revealed limitations of OVs as monotherapy. The same applies to CDK 4/6 inhibitors (CDK4/6i) targeting cell cycle as well as bromodomain and extra-terminal domain inhibitors (BETi) targeting gene expression. In this study, the anti-tumoral effect of XVir-N-31, an YB-1 dependent oncolytic adenovirus, was evaluated in combination with Ribociclib, a CDK4/6i, and JQ1, a BETi. The head and neck squamous cell carcinoma (HNSCC) cell lines Fadu, SAS, and Cal-33 were used. DNA replication and gene expression of XVir-N-31 was measured by RT-qPCR, protein expression by western blotting, and cell lysis by SRB assays. Treatment with CDK4/6i and BETi increased viral gene expression, viral DNA replication, and viral particle formation. The data show that the combination of oncolytic adenovirus XVir-N-31 with CDK4/6i & BETi acts highly synergistic in cancer cell lysis. Furthermore, additional molecular analyses on this subject demonstrate that the positive transcription elongation factor P-TEFb plays a decisive role in this regard, indicating an influence of the combinational therapy on gene transcription control. The combination of CDK4/6i & BETi and XVir-N-31 is an attractive strategy to achieve substantial cancer cell killing and is highly suitable for clinical testing.

Keywords: adenovirus, BET, CDK4/6, HNSCC, P-TEFb, YB-1

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim

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In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

Keywords: accelerometer, activity recognition, directiona cosine matrix filter, gyroscope, Kalman filter, magnetometer

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio

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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.

Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars

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Authors: Partha Protim Majumder, Sajeeb Das, Sharun Akter Khushbu

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Bengali is widely spoken in the world, but Bengali speech recognition has not received much attention. Here, we are conducting the toughest task because it must be performed in a noisy place in our study. Another challenge we overcome is dealing with speeches and collecting data on third genders, and our approach is to recognize the gender in speeches. All of the Bangla speech samples used in this study were short and were taken from real-life situations. We employed the male, female, and third-gender categories of speech. In this study, we derive the feature from the spoken word. We used MFCC(1-20), ZCR,rolloff,spec_cen, RMSE, and chroma_stft. Here, we used the algorithms Gboost, Random Forest, K-Nearest Neighbors (KNN), Decision Tree, Naive Bayes, and Logistic Regression (LR) to assess the performance of recognition metrics, and we got the highest performance from random forest in recognizing the gender of the speeches.

Keywords: MFCC, ZCR, Bengali, LR, RMSE, roll-off, Gboost

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Authors: Sidi Ahmed Maouloud, Cheikh Ba

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Much of West Africa’s cultural heritage is written in the Al-Soudani Arabic script, which was widely used in West Africa before the time of European colonization. This Al-Soudani Arabic script is an African version of the Maghrebi script, in particular, the Al-Mebssout script. However, the local African qualities were incorporated into the Al-Soudani script in a way that gave it a unique African diversity and character. Despite the existence of several Arabic datasets in Oriental script, allowing for the analysis, layout, and recognition of texts written in these calligraphies, many Arabic scripts and written traditions remain understudied. In this paper, we present a dataset of words from Al-Soudani calligraphy scripts. This dataset consists of 100 images selected from three different manuscripts written in Al-Soudani Arabic script by different copyists. The primary source for this database was the libraries of Boston University and Cambridge University. This dataset highlights the unique characteristics of the Al-Soudani Arabic script as well as the new challenges it presents in terms of automatic word recognition of Arabic manuscripts. An HTR system based on a hybrid ANN (CRNN-CTC) is also proposed to test this dataset. SAMRA is a dataset of annotated Arabic manuscript words in the Al-Soudani script that can help researchers automatically recognize and analyze manuscript words written in this script.

Keywords: dataset, CRNN-CTC, handwritten words recognition, Al-Soudani Arabic script, HTR, manuscripts

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Authors: Mudassar Mohiuddin, Zahid Iqbal

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Introduction: Clostridium perfringens is an important pathogen responsible for causing enteric diseases in both human and animals. The bacteria produce several toxins. These toxins play vital role in the pathogenesis of various fatal enteric diseases and are classified into five types, on the basis of the differential production of Alpha, Beta, Epsilon and Iota toxins. In addition to the so-called major toxins, there are other toxins like beta2 toxin, produced by some strains of C. perfringens which may play a role in the pathogenesis of disease. Aim of the study: In this study a multiplex PCR assay was developed and used for detection of cpb2 gene to identify the Beta2 harboring isolates among different types of C. perfringens. Objectives: The primary objective of this study was to identify the prevalence of β2-toxin gene in local isolates of Clostridium perfringens. Methodology: This was an experimental study. Random sampling technique was used. A total of 97 sheep and goats were included in this study. All were Pakistani local breeds. The samples were collected during the period from Sep, 2014 to Mar, 2015 from selected districts of Punjab province (Pakistan). Faecal samples were cultured in cooked meat media. The identification of Clostridium perfringens was made on the basis of biochemical tests. Multiplex PCR was performed to identify the toxin genes. Results: A total of 43 C. perfringens isolates were genotyped using multiplex PCR assay. The gene encoding C. perfringens β2-toxin (cpb2) was present in more than 50% of the isolates genotyped. However, the prevalence of this gene varied between sheep and goat isolates. Conclusion: The present study suggests the high occurrence of C. perfringens b2-toxin (cpb2) in the local isolates of Pakistan. As β2-toxin is present in both healthy and diseased animals, so further studies are suggested to establish the role of β2-toxin in pathogenesis of the clostridial enteric diseases.

Keywords: beta 2 toxin gene, clostridium perfringens, enteric diseases, goats, multiplex PCR, sheep

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Chen Zhang, Fengxue Xin, Jianzhong He

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A unique Clostridium beijerinckii species strain BGS1 was obtained from grass land samples, which is capable of producing 8.43g/L butanol and 3.21 isopropanol from 60g/L glucose while generating 4.68g/L volatile fatty acids (VFAs) from 30g/L xylan. The concentration of isopropanol produced by culture BGS1 is ~15% higher than previously reported wild-type Clostridium beijerinckii under similar conditions. Compared to traditional Acetone-Butanol-Ethanol (ABE) fermentation species, culture BGS1 only generates negligible amount of ethanol and acetone, but produces butanol and isopropanol as biosolvent end-products which are pure alcohols and more economical than ABE. More importantly, culture BGS1 can consume acetone to produce isopropanol, e.g., 1.84g/L isopropanol from 0.81g/L acetone in 60g/L glucose medium containing 6.15g/L acetone. The analysis of BGS1 draft genome annotated by RAST server demonstrates that no ethanol production is caused by the lack of pyruvate decarboxylase gene – related to ethanol production. In addition, an alcohol dehydrogenase (adhe gene) was found in BGS1 which could be a potential gene responsible for isopropanol-generation. This is the first report on Isopropanol-Butanol (IB) fermentation by wild-type Clostridium strain and its application for isopropanol and butanol production.

Keywords: acetone conversion, butanol, clostridium, isopropanol

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Authors: Mayada Mazher, Ahmed Moustafa, Ahmed Abdellatif

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Background: Autophagy is a eukaryotic, highly conserved catabolic process implicated in many pathophysiologies such as wound healing. Autophagy-associated genes serve as a scaffolding platform for signal transduction of macrophage polarization during the inflammatory phase of wound healing and tissue repair process. In the current study, we report a model for the interplay between autophagy-associated genes and macrophages polarization associated genes. Methods: In silico analysis was performed on 249 autophagy-related genes retrieved from the public autophagy database and gene expression data retrieved from Gene Expression Omnibus (GEO); GSE81922 and GSE69607 microarray data macrophages polarization 199 DEGS. An integrated protein-protein interaction network was constructed for autophagy and macrophage gene sets. The gene sets were then used for GO terms pathway enrichment analysis. Common transcription factors for autophagy and macrophages' polarization were identified. Finally, microRNAs enriched in both autophagy and macrophages were predicated. Results: In silico prediction of common transcription factors in DEGs macrophages and autophagy gene sets revealed a new role for the transcription factors, HOMEZ, GABPA, ELK1 and REL, that commonly regulate macrophages associated genes: IL6,IL1M, IL1B, NOS1, SOC3 and autophagy-related genes: Atg12, Rictor, Rb1cc1, Gaparab1, Atg16l1. Conclusions: Autophagy and macrophages' polarization are interdependent cellular processes, and both autophagy-related proteins and macrophages' polarization related proteins coordinate in tissue remodelling via transcription factors and microRNAs regulatory network. The current work highlights a potential new role for transcription factors HOMEZ, GABPA, ELK1 and REL in wound healing.

Keywords: autophagy related proteins, integrated network analysis, macrophages polarization M1 and M2, tissue remodelling

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Authors: Elif Tugce Aksun Tumerkan, Chris Lowe, Hannah Krupa

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Fluorescent proteins are self-sufficient in forming chromophores with a visible wavelength from 3 amino acids sequence within their own polypeptide structure. This chromophore – a molecule that absorbs a photon of light and exhibits an energy transition equal to the energy of the absorbed photon. Fluorescent proteins (FPs) consisted of a chain of 238 amino acid residues and composed of 11 beta strands shaped in a cylinder surrounding an alpha helix structure. A better understanding of the system of the chromospheres and the increasing advance in protein engineering in recent years, the properties of FPs offers the potential for new applications. They have used sensors and probes in molecular biology and cell-based research that giving a chance to observe these FPs tagged cell localization, structural variation and movement. For clarifying functional uses of fluorescent proteins, electrophoretic properties of these proteins are one of the most important parameters. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) analysis is used for determining electrophoretic properties commonly. While there are many techniques are used for determining the functionality of protein-based research, SDS-PAGE analysis can only provide a molecular level assessment of the proteolytic fragments. Before SDS-PAGE analysis, fluorescent proteins need to successfully purified. Due to directly purification of the target, FPs is difficult from the animal, gene expression is commonly used which must be done by transformation with the plasmid. Furthermore, used gel within electrophoresis and staining agents properties have a key role. In this review, the different factors that have the impact on the electrophoretic properties of fluorescent proteins explored. Fluorescent protein separation and purification are the essential steps before electrophoresis that should be done very carefully. For protein purification, gene expression process and following steps have a significant function. For successful gene expression, the properties of selected bacteria for expression, used plasmid are essential. Each bacteria has own characteristics which are very sensitive to gene expression, also used procedure is the important factor for fluorescent protein expression. Another important factors are gel formula and used staining agents. Gel formula has an effect on the specific proteins mobilization and staining with correct agents is a key step for visualization of electrophoretic bands of protein. Visuality of proteins can be changed depending on staining reagents. Apparently, this review has emphasized that gene expression and purification have a stronger effect than electrophoresis protocol and staining agents.

Keywords: cell biology, gene expression, staining agents, SDS-page

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Authors: Kritin K. Verma, Bailey Duhon, Patrick W. Slater

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Objective: To introduce the possible etiological role that the Labyrinthine Venous Vasculature (LVV) has in venous congestion of the cochlear system in Sudden Sensorineural Hearing Loss (SSNHL) patients. Patients: Two patients (62-year-old female, 50-year-old male) presented within twenty-four hours of onset of SSNHL. Intervention: Following failed conservative and salvage techniques, the patients underwent ablation of the labyrinthine venous vasculature ipsilateral to the side of the loss. Main Outcome Measures: Improvement of sudden SSNHL based on an improvement of pure-tone audiometric (PTA) low-tone scoring averages at 250, 500, and 1000 Hz. Word recognition scoring using the NU-6 word list was used to assess quality of life. Results: Case 1 experienced a 51.7 dB increase in low-tone PTA and an increased word recognition scoring of 90%. Case 2 experienced a 33.4 dB increase in low-tone PTA and 60% increase in word recognition score. No major complications noted. Conclusion: Two patients experienced significant improvement in their low-tone PTA and word recognition scoring following the labyrinthine venous vasculature ablation.

Keywords: case report, sudden sensorineural hearing loss, venous congestion, vascular ablation

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Authors: Hamza Iftikhar

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The research study focuses on the transgender community's gender recognition challenges. It is one of the issues for the transgender community, interacting directly with the difficulties of gender identity and the lives of these people who are facing gender disapproval from society. This study investigates the major flaws of the transgender act. The study's goal is to look into the strange implications of self-perceived identity as a policy tool for transgender recognition. This policy tool jeopardises the rights of Pakistan's indigenous gender-variant people as well as the country's legal and social framework. Qualitative research using semi structured interviews will be carried out. This study proposes developing a scheme for mainstreaming gender-variant people on the basis of the Pakistani Constitution, Supreme Court guidelines, and internationally recognised principles of law. This would necessitate a thorough review of current law using a new approach and reference point.

Keywords: transgender act, self perceived identity, gender variant, policy tool

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Authors: R. Majidzadeh Heravi, M. Sankian, H. Kermanshahi, M. R. Nassiri, A. Heravi Moussavi, S. A. Lari, A. R. Varasteh

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The use of probiotics engineered to express specific enzymes has been the subject of considerable attention in poultry industry because of increased nutrient availability and reduced cost of enzyme supplementation. Phytase enzyme is commonly added to poultry feed to improve digestibility and availability of phosphorus from plant sources. To construct a probiotic with potential of phytate degradation, phytase gene (appA) from E. coli was cloned and transformed into two probiotic bacteria Lactobacillus salivarius and Lactococcus lactis. L. salivarous showed plasmid instability, unable to express the gene. The expression of appA gene in L. lactis was analyzed by detecting specific RNA and zymography assay. Phytase enzyme was isolated from cellular extracts of recombinant L. lactis, showing a 46 kDa band upon the SDS-PAGE analysis. Zymogram also confirmed the phytase activity of the 46 kDa band corresponding to the enzyme. An enzyme activity of 4.9U/ml was obtained in cell extracts of L. lactis. The growth of native and recombinant L. lactis was similar in the presence of two concentrations of ox bile.

Keywords: Lactobacillus salivarus, Lactococcuslactis, recombinant, phytase, poultry

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Authors: Elena E. Lyakso, Olga V. Frolova, Yuri N. Matveev, Aleksey S. Grigorev, Alexander S. Nikolaev, Viktor A. Gorodnyi

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The study of the children’s emotional sphere depending on age and psychoneurological state is of great importance for the design of educational programs for children and their social adaptation. Atypical development may be accompanied by violations or specificities of the emotional sphere. To study characteristics of the emotional state reflection in the voice and speech features of children, the perceptual study with the participation of adults and the automatic recognition of speech were conducted. Speech of children with typical development (TD), with Down syndrome (DS), and with autism spectrum disorders (ASD) aged 6-12 years was recorded. To obtain emotional speech in children, model situations were created, including a dialogue between the child and the experimenter containing questions that can cause various emotional states in the child and playing with a standard set of toys. The questions and toys were selected, taking into account the child’s age, developmental characteristics, and speech skills. For the perceptual experiment by adults, test sequences containing speech material of 30 children: TD, DS, and ASD were created. The listeners were 100 adults (age 19.3 ± 2.3 years). The listeners were tasked with determining the children’s emotional state as “comfort – neutral – discomfort” while listening to the test material. Spectrographic analysis of speech signals was conducted. For automatic recognition of the emotional state, 6594 speech files containing speech material of children were prepared. Automatic recognition of three states, “comfort – neutral – discomfort,” was performed using automatically extracted from the set of acoustic features - the Geneva Minimalistic Acoustic Parameter Set (GeMAPS) and the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS). The results showed that the emotional state is worse determined by the speech of TD children (comfort – 58% of correct answers, discomfort – 56%). Listeners better recognized discomfort in children with ASD and DS (78% of answers) than comfort (70% and 67%, respectively, for children with DS and ASD). The neutral state is better recognized by the speech of children with ASD (67%) than by the speech of children with DS (52%) and TD children (54%). According to the automatic recognition data using the acoustic feature set GeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.687; children with DS – 0.725; TD children – 0.641. When using the acoustic feature set eGeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.671; children with DS – 0.717; TD children – 0.631. The use of different models showed similar results, with better recognition of emotional states by the speech of children with DS than by the speech of children with ASD. The state of comfort is automatically determined better by the speech of TD children (precision – 0.546) and children with ASD (0.523), discomfort – children with DS (0.504). The data on the specificities of recognition by adults of the children’s emotional state by their speech may be used in recruitment for working with children with atypical development. Automatic recognition data can be used to create alternative communication systems and automatic human-computer interfaces for social-emotional learning. Acknowledgment: This work was financially supported by the Russian Science Foundation (project 18-18-00063).

Keywords: autism spectrum disorders, automatic recognition of speech, child’s emotional speech, Down syndrome, perceptual experiment

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Authors: Vinod Kumar Gupta, Narendrakumar M. Chaudhari, Suchismitha Iskepalli, Chitra Dutta

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Background-The community composition of the human microbiome is known to vary at distinct anatomical niches. But little is known about the nature of variations if any, at the genome/sub-genome levels of a specific microbial community across different niches. The present report aims to explore, as a case study, the variations in gene repertoire of 28 Prevotella reference draft genomes derived from different body-sites of human, as reported earlier by the Human Microbiome Consortium. Results-The analysis reveals the exclusive presence of 11798, 3673, 3348 and 934 gene families and exclusive absence of 17, 221, 115 and 645 gene families in Prevotella genomes derived from the human oral cavity, gastro-intestinal tracts (GIT), urogenital tract (UGT) and skin, respectively. The pan-genome for Prevotella remains “open”. Distribution of various functional COG categories differs appreciably among the habitat-specific genes, within Prevotella pan-genome and between the GIT-derived Bacteroides and Prevotella. The skin and GIT isolates of Prevotella are enriched in singletons involved in Signal transduction mechanisms, while the UGT and oral isolates show higher representation of the Defense mechanisms category. No niche-specific variations could be observed in the distribution of KEGG pathways. Conclusion-Prevotella may have developed distinct genetic strategies for adaptation to different anatomical habitats through selective, niche-specific acquisition and elimination of suitable gene-families. In addition, individual microorganisms tend to develop their own distinctive adaptive stratagems through large repertoires of singletons. Such in situ, habitat-driven refurbishment of the genetic makeup can impart substantial intra-lineage genome diversity within the microbes without perturbing their general taxonomic heritage.

Keywords: body niche adaptation, human microbiome, pangenome, Prevotella

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Authors: Yahia Massinissa, Yahia Mouloud

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Cystic fibrosis (CF), the most common lethal genetic disease in the Europe population, is caused by mutations in the transmembrane conductance regulator gene (CFTR). It affects most organs including an epithelial tissue, base of hydroelectrolytic transepithelial transport, notably that aerial ways, the pancreas, the biliary ways, the intestine, sweat glands and the genital tractus. The gene whose anomalies are responsible of the cystic fibrosis codes for a protein Cl channel named CFTR (cystic fibrosis transmembrane conductance regulator) that exercises multiple functions in the cell, one of the most important in control of sodium and chlorine through epithelia. The deficient function translates itself notably by an abnormal production of viscous secretion that obstructs the execrator channels of this target organ: one observes then a dilatation, an inflammation and an atrophy of these organs. It also translates itself by an increase of the concentration in sodium and in chloride in sweat, to the basis of the sweat test. In order to do a phenotypical and genotypical diagnosis at a part of the Algerian population, our survey has been carried on 16 patients with evocative symptoms of the cystic fibrosis at that the clinical context has been confirmed by a sweat test. However, anomalies of the CFTR gene have been determined by electrophoresis in gel of polyacrylamide of the PCR products (polymerase chain reaction), after enzymatic digestion, then visualized to the ultraviolet (UV) after action of the ethidium bromide. All mutations detected at the time of our survey have already been identified at patients attained by this pathology in other populations of the world. However, the important number of found mutation with regard to the one of the studied patients testifies that the origin of this big clinical variability that characterizes the illness in the consequences of an enormous diversity of molecular defects of the CFTR gene.

Keywords: cystic fibrosis, CFTR gene, polymorphism, algerian population, sweat test, genotypical diagnosis

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Authors: Maryam Monazzah, Ronak Samadpour, Mehdi Nasr-esfahani, Fatemeh Qalavand, Marziye Motamedi

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Bipolaris sorokiniana, and Heterodera filipjevi, are important wheat diseases that lead to yield losses worldwide. Identifying novel resistant sources helps us combat these devastating diseases. In this study, we studied the role of Cre3 gene and antioxidant enzymes in the immune responses of wheat genotypes to H. filipjevi and B. sorokiniana. Therefore, real-time PCR analysis using Cre3 gene marker, a resistant gene to cereal cyst nematodes, was conducted on leaves and roots, along with changes ‎in the activity of antioxidant enzymes, peroxidase, and catalase. Enzyme activity assay was performed on roots attacked by nematode and in leaves infected with Bipolaris. Wheat accessions including “Bam” (resistant), “Parsi” (moderately-resistant), “Azar2”, “Ohadi”, “Homa” (highly-susceptible) were previously screened against both stresses under greenhouse and field conditions. Results showed that Cre3 expression against cyst nematodes was significantly higher in resistant cultivars compared to susceptible cultivars. Cre3 was used in marker-assisted selection programs to identify genotypes carrying resistant genes to cyst nematodes. Interestingly, Cre3 was also up-regulated in both tissues of resistant cultivars to B. sorokiniana. Therefore, Cre3 in wheat similarly modulates immunity against B. sorokiniana and might be one of the central components of the induced immune system in wheat. The activity of antioxidant enzymes also indicated the highest increase in resistant genotypes upon both stresses that subsequently neutralize oxidative stress in tissues and decrease damage. Further studies on these resistance components may help us gain insight into the molecular basis of resistance and shed new light on the interaction and overlap between different forms of stress.

Keywords: Bipolaris sorokiniana, Heterodera filipjevi, resistant gene expression, wheat

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Authors: K. Veluraja

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Glycan of glycolipids and glycoproteins is playing a significant role in living systems particularly in molecular recognition processes. Molecular recognition processes are attributed to their occurrence on the surface of the cell, sequential arrangement and type of sugar molecules present in the oligosaccharide structure and glyosidic linkage diversity (glycoinformatics) and conformational diversity (glycoconformatics). Molecular Dynamics Simulation study is a theoretical-cum-computational tool successfully utilized to establish glycoconformatics of glycan. The study on various oligosaccharides of glycan clearly indicates that oligosaccharides do exist in multiple conformational states and these conformational states arise due to the flexibility associated with a glycosidic torsional angle (φ,ψ) . As an example: a single disaccharide structure NeuNacα(2-3) Gal exists in three different conformational states due to the differences in the preferential value of glycosidic torsional angles (φ,ψ). Hence establishing three dimensional structural and conformational models for glycan (cartesian coordinates of every individual atoms of an oligosaccharide structure in a preferred conformation) is quite crucial to understand various molecular recognition processes such as glycan-toxin interaction and glycan-virus interaction. The gycoconformatics models obtained for various glycan through Molecular Dynamics Simulation stored in our 3DSDSCAR (3DSDSCAR.ORG) a public domain database and its utility value in understanding the molecular recognition processes and in drug design venture will be discussed.

Keywords: glycan, glycoconformatics, molecular dynamics simulation, oligosaccharide

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