Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics最新文献

Nanoencapsulation of Zerumbone in Oleic Acid-Modified Chitosan Nanoparticles 油酸修饰壳聚糖纳米颗粒中Zerumbone的纳米包封

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155097

E. R. Wikantyasning, S. D. Andasari, M. Da'i, Asyafra Nabila

{"title":"Nanoencapsulation of Zerumbone in Oleic Acid-Modified Chitosan Nanoparticles","authors":"E. R. Wikantyasning, S. D. Andasari, M. Da'i, Asyafra Nabila","doi":"10.1145/3155077.3155097","DOIUrl":"https://doi.org/10.1145/3155077.3155097","url":null,"abstract":"Zerumbone is an active compound of Zingiber zerumbet which has been shown to possess antioxidant and anticancer activities. The limited therapeutic application of this compound was due to its poor water solubility. The aim of this study was to encapsulate zerumbone in hydrophobic chitosan nanoparticles that modified using oleic acid. Oleic acid-modified chitosan was synthesized by coupling chitosan with oleic acid through the 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide HCl-mediated reaction, and was characterized using Fourier-transform infrared (FTIR) spectroscopy. Isolated zerumbone was coated by oleic acid-modified chitosan using ionic-gelation method. The nanoparticles was characterized using particle size analyzer for particle size and zeta potential, and the entrapment efficiency was determined by measuring the concentration of zerumbone using gas chromatography-mass spectroscopy. It was found that prepared zerumbone loaded-nanoparticles had an average size in the range from 500 to 580 nm and carried a positive charge with the zeta potential in the range of +16 to +30 mV. The entrapment efficiency of nanoparticles was about 6 times higher than encapsulation efficiency of zerumbone in chitosan nanoparticles. The nanoparticles have great potential for delivery of zerumbone as anticancer.","PeriodicalId":237079,"journal":{"name":"Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127165661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

SWT and Spread Spectrum Coding Based Copyright Protection Technique for Digital Images 基于SWT和扩频编码的数字图像版权保护技术

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155085

P. Nagarjuna, Dharmender Tyagi, R. B. Ramachandra

引用次数: 0

Scanning Electron Microscope (SEM) Investigations on Gelatin-Chitosan-Bioactive Glass (58s) Scaffolds for Bone Tissue Engineering 明胶-壳聚糖-生物活性玻璃(58s)骨组织工程支架的扫描电镜研究

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155094

Zarrin Ahmadi, F. Moztarzadeh

{"title":"Scanning Electron Microscope (SEM) Investigations on Gelatin-Chitosan-Bioactive Glass (58s) Scaffolds for Bone Tissue Engineering","authors":"Zarrin Ahmadi, F. Moztarzadeh","doi":"10.1145/3155077.3155094","DOIUrl":"https://doi.org/10.1145/3155077.3155094","url":null,"abstract":"Nowadays, finding a proper substitute for the damaged or lost tissue is still a crucial open problem for the clinical scientific research. The fundamental aspects of the bone resemble a natural composite which consists of a wide range of polymers and ceramics. Therefore, there is a large amount of effort put into combining a structure which could feature sufficient mechanical strength, good biocompatibility and acceptable rate of biodegradation as a bone scaffold. In this paper, gelatin and chitosan have been chosen to play a role as the polymer matrix and bioactive glass 58s as a ceramic phase to characterize a new composition. To create a spongy structure with differently-sized porosity, five samples of scaffolds with different proportions of bioactive glass have been synthesized in the laboratory, which was dried in a freeze dryer. The electron microscope scanning illustrates the size of porosities and also the amount of forming appetite in the scaffolds' surfaces. The porosities sizes are observed to have the approximate size of 160-377μm, which is qualified for angiogenesis and cell growth in the bone and makes the scaffold an ideal choice for bone substitution.","PeriodicalId":237079,"journal":{"name":"Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124162978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Individual Drug Treatment Prediction in Oncology Based on Machine Learning Using Cell Culture Gene Expression Data 基于细胞培养基因表达数据的机器学习的肿瘤个体药物治疗预测

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155078

N. Borisov, Victor Tkachev, I. Muchnik, A. Buzdin

引用次数: 12

Unsupervised Learning of Sequencing Read Types 排序读取类型的无监督学习

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155080

Jan Tomljanovic, Tomislav Sebrek, M. Šikić

引用次数: 1

Recurrent Neural Networks with Non-Sequential Data to Predict Hospital Readmission of Diabetic Patients 基于非序列数据的递归神经网络预测糖尿病患者再入院

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155081

Chahes Chopra, S. Sinha, Shubham Jaroli, A. Shukla, Saumil Maheshwari

引用次数: 28

Improving Classification Performance by Combining Feature Vectors with a Boosting Approach for Brain Computer Interface (BCI) 结合特征向量和增强方法提高脑机接口(BCI)分类性能

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155087

R. Rajan, Sunny Thekkan Devassy

{"title":"Improving Classification Performance by Combining Feature Vectors with a Boosting Approach for Brain Computer Interface (BCI)","authors":"R. Rajan, Sunny Thekkan Devassy","doi":"10.1145/3155077.3155087","DOIUrl":"https://doi.org/10.1145/3155077.3155087","url":null,"abstract":"Brain-computer interfaces (BCI) are an interesting emerging technology providing an efficient communication system between human brain and external devices like computers or neuroprosthesis. Among assorts of neuroimaging techniques, electroencephalogram (EEG) is among one of the non-invasive methods exploited mostly in BCI studies. Recent studies have shown that Motor Imagery (MI) based BCI can be used as a rehabilitation tool for patients with severe neuromuscular disabilities. The spatial and spectral information related to brain activities associated with BCI paradigms are usually pre-determined as default in EEG analysis without speculation, which can lead to loses effects in practical applications due to individual variability across different subjects. Recent studies have shown that feature combination of each specifically tailored for different physiological phenomena such as Readiness Potential (RP) and Event Related Desynchronization (ERD) might benefit BCI making it robust against artifacts. Hence, the objective is to design a CSSBP with combined feature vectors, where the signal is divided into several sub bands using a band pass filter, and this channel and frequency configurations are then modeled as preconditions before learning base learners and introducing a new heuristic of stochastic gradient boost for training the base learners under these preconditions. The effectiveness and robustness of this algorithm along with feature combination is evaluated on two different data sets recorded from distinct populations. Results showed that Boosting approach with feature combination clearly outperformed the state-of-the-art algorithms, and improved the classification performance and resulted in increased robustness. This method can also be used to explore the neurophysiological mechanism of underlying brain activities.","PeriodicalId":237079,"journal":{"name":"Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics","volume":"359 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116054811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Online Medical Image Management System 在线医学图像管理系统

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155089

Ching-Yu Huang, Reuben Hernandez, Shean Ballesteros, X. Lin

引用次数: 0

Fatigue Analysis in Biceps Brachii Muscles Using Semg Signals and Polynomial Chirplet Transform 基于Semg信号和多项式小波变换的肱二头肌疲劳分析

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155090

D. M. Ghosh, S. Ramakrishnan

{"title":"Fatigue Analysis in Biceps Brachii Muscles Using Semg Signals and Polynomial Chirplet Transform","authors":"D. M. Ghosh, S. Ramakrishnan","doi":"10.1145/3155077.3155090","DOIUrl":"https://doi.org/10.1145/3155077.3155090","url":null,"abstract":"Muscle fatigue analysis finds significant applications in the areas of biomechanics, sports medicine and clinical studies. Surface electromyography (sEMG) signals have wide application because of its non invasiveness. By nature, signals recorded using surface electrodes from muscles are highly nonstationary and random. The objective of this work is to analyze muscle related fatigue using sEMG signals and polynomial chirplet transform (PCT). sEMG signals are acquired from biceps brachii muscles of twenty volunteers (Mean (sd): age, 23.5 (4.3) years) in isometric contractions. The initial 500 ms is considered as nonfatigue and final 500 ms of the signals are considered as fatigue zone. Then signals are subjected to polynomial chirplet transform to estimate the time-frequency spectrum. Four features, instantaneous mean frequency (IsMNF), instantaneous median frequency (IsMDF), instantaneous spectral entropy (ISpEn) and instantaneous spectral skewness (ISSkw) are extracted for further analysis. Results show that the PCT is able to characterize the nonstationary and multi component nature of sEMG signals. The IsMNF, IsMDF, ISpEn are found to be high in nonfatigue conditions. Further, all the features are very distinct in muscle nonfatigue and fatigue conditions (p<0.001). This technique can be used in analyzing different neuromuscular disorders.","PeriodicalId":237079,"journal":{"name":"Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121462974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comparison of Filtered Back Projection and Maximum Likelihood Expected Maximization 滤波后投影与最大似然期望最大化的比较

Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics Pub Date : 2017-10-18 DOI: 10.1145/3155077.3155091

N. Sengee, Chinzorig Radnaabazar, Suvdaa Batsuuri, Khurel-Ochir Tsedendamba

引用次数: 1