2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)最新文献_第6页

Non-contact Instantaneous Heart Rate Monitoring Using Microwave Doppler Sensor and Time-Frequency Domain Analysis 基于微波多普勒传感器的非接触式瞬时心率监测及时频分析

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.23

D. Matsunaga, S. Izumi, H. Kawaguchi, M. Yoshimoto

引用次数: 10

Dynamic and Static Balance in Persons with Different Arch Height and Impacts of an Arch Support 不同拱高人群的动、静态平衡及拱架的影响

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.57

Yi-Ting Chen, Jun-Ding Zhu, Jen-Suh Chern

引用次数: 1

Comparing Programming Language Comprehension between Novice and Expert Programmers Using EEG Analysis 用脑电图分析比较新手和老手的编程语言理解能力

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.30

Seolhwa Lee, Andrew Matteson, Danial Hooshyar, SongHyun Kim, Jaebum Jung, GiChun Nam, Heuiseok Lim

引用次数: 54

Feature Selection with Non-Linear Dependence Based on Multi-objective Strategy 基于多目标策略的非线性依赖特征选择

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.38

Chun-Liang Lu, Wei Tang, Yu-Shuen Tsai, N. Pal, I. Chung

{"title":"Feature Selection with Non-Linear Dependence Based on Multi-objective Strategy","authors":"Chun-Liang Lu, Wei Tang, Yu-Shuen Tsai, N. Pal, I. Chung","doi":"10.1109/BIBE.2016.38","DOIUrl":"https://doi.org/10.1109/BIBE.2016.38","url":null,"abstract":"It is an interesting and important issue to identify a small set of useful features from a high dimensional data that can be used to design a classification mechanism. Usually, researchers prefer to find the features that have high relevance, in the sense that the correlation of each of those features with class labels is high or the mutual information between each of the features and class labels is high. Such approaches usually end up finding features that may be linearly dependent with each other. For some biological studies, it may be interesting to find a set of genes (features), which have high relevance with the class labels and also the genes are nonlinearly dependent -we explicitly want to exclude relevant genes that are linearly correlated among them. Although, our primary focus in this study is to find such genes from microarray data sets, such features may also be important in other studies. In this study, the Combinations of Relevantly Non-linear Dependency Subsets (CoRNDS) is proposed to tackle such the multi-objective problem. It opens up a good to simultaneously control selection of number of useful features, optimize the relevance between the selected features with class labels, and the non-linear dependency between the selected features. Using innovative ways we design three new objectives and optimize them by using the well-known multi-objective evolutionary algorithm based on decomposition (MOEA/D) method. To the best of our knowledge, this is the first attempt to feature (gene) selection along with identification of non-linear dependency between features via a multi-objective strategy. Experimental results show that the feasibility and effective performance on microarray cancer dataset. As to these selected gene subsets, investigate their auxiliary role of co-regulation in the biological pathways, and the occurrence in the pathogenesis of cancer are interesting future works.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116831016","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

Identification and Analysis of Palindromes for RNA Sequences RNA序列回文的鉴定与分析

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.35

Chien-Hung Huang, Sheng-Jia Weng, P. Korla, Jywe-Fei Fang, J. Tsai, Nilubon Kurubanjerdjit, K. Ng

{"title":"Identification and Analysis of Palindromes for RNA Sequences","authors":"Chien-Hung Huang, Sheng-Jia Weng, P. Korla, Jywe-Fei Fang, J. Tsai, Nilubon Kurubanjerdjit, K. Ng","doi":"10.1109/BIBE.2016.35","DOIUrl":"https://doi.org/10.1109/BIBE.2016.35","url":null,"abstract":"A palindrome is a string of the form S = A1 A2 or S = A1 aA2, where A1 and A2 are substrings of S and the reverse of A2 exactly matches with A1. DNA palindromes show direct influence on tumerogenesis due to the formation of DNA palindromes at microRNA genes, which involve in tumor development. Furthermore, RNA palindromes play a crucial role in genomic instability and gene amplification in some human cancers. Therefore, it is important to develop effective approaches to identify and characterize biological approximate palindromes. In this paper, we developed a simple algorithm to find all the exact and approximate palindromes up to k errors (k is specified by the user) for the two different types of RNA sequence data, i.e. mRNA sequences of fusion genes and human microRNAs (miRNAs). We confirmed that the palindromes in RNA sequences are A-U rich. According to the Kolmogorov-Smirnov test, it was found that miRNA has a frequency distribution of palindromes different from the fusion genes' mRNAs. The proposed algorithm is easy to implement, which provides an effective tool for investigating the relationship between palindromes and cancer biology.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132698253","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

GReMLIN: A Graph Mining Strategy to Infer Protein-Ligand Interaction Patterns GReMLIN:一种推断蛋白质-配体相互作用模式的图挖掘策略

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.48

C. A. Santana, F. Cerqueira, C. H. Silveira, A. V. Fassio, R. Minardi, S. Silveira

引用次数: 5

Statistical Principle-Based Approach for Detecting miRNA-Target Gene Interaction Articles 基于统计原理的mirna -靶基因相互作用检测方法

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.60

Nai-Wen Chang, Hong-Jie Dai, Yu-Lun Hsieh, W. Hsu

{"title":"Statistical Principle-Based Approach for Detecting miRNA-Target Gene Interaction Articles","authors":"Nai-Wen Chang, Hong-Jie Dai, Yu-Lun Hsieh, W. Hsu","doi":"10.1109/BIBE.2016.60","DOIUrl":"https://doi.org/10.1109/BIBE.2016.60","url":null,"abstract":"MicroRNAs (miRNAs) are small non-coding RNAs of approximately 23 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. miRNAs have been considered as good candidates for early detection or prognosis biomarkers for various diseases. Validated miRNA targets are usually reported in literature, necessitating researchers to manually screen through the related literature to keep up-to-date with novel findings. However, the amount of miRNA-related literature is increasing rapidly which makes it difficult for researchers to keep up to date. This study develops a text mining pipeline based on the statistical principle-based approach (SPBA) to detect MiRNA-Target Interactions (MTIs) mentioned in literatures. SPBA uses a collection of principles to represent linguistic concepts or rules used by human for describing MTIs. Each principle is composed of a collection of slots, which can be automatically learned from training data by merging the labeled slot sequences into more representative principles through a dominating set algorithm. Followed by a partial matching algorithm, the proposed approach can successfully recognize miRNA mentions and extract their MTIs in articles with a promising F-score of 98.8% and an accuracy of 71.43%.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"19 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130867028","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: 6

Automatic Lesion Detection System (ALDS) for Skin Cancer Classification Using SVM and Neural Classifiers 基于支持向量机和神经分类器的皮肤癌自动病灶检测系统

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.53

Muhammad Ali Farooq, M. A. M. Azhar, R. H. Raza

{"title":"Automatic Lesion Detection System (ALDS) for Skin Cancer Classification Using SVM and Neural Classifiers","authors":"Muhammad Ali Farooq, M. A. M. Azhar, R. H. Raza","doi":"10.1109/BIBE.2016.53","DOIUrl":"https://doi.org/10.1109/BIBE.2016.53","url":null,"abstract":"Technology aided platforms provide reliable tools in almost every field these days. These tools being supported by computational power are significant for applications that need sensitive and precise data analysis. One such important application in the medical field is Automatic Lesion Detection System (ALDS) for skin cancer classification. Computer aided diagnosis helps physicians and dermatologists to obtain a \"second opinion\" for proper analysis and treatment of skin cancer. Precise segmentation of the cancerous mole along with surrounding area is essential for proper analysis and diagnosis. This paper is focused towards the development of improved ALDS framework based on probabilistic approach that initially utilizes active contours and watershed merged mask for segmenting out the mole and later SVM and Neural Classifier are applied for the classification of the segmented mole. After lesion segmentation, the selected features are classified to ascertain that whether the case under consideration is melanoma or non-melanoma. The approach is tested for varying datasets and comparative analysis is performed that reflects the effectiveness of the proposed system.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"456 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132055650","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: 46

Dual Wavelength Silicon-Based-Photodetector for Biomedical Sensing System Applications 生物医学传感系统应用的双波长硅基光电探测器

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.10

Yao-Chin Wang, Zu-Po Yang, Bor-Shyh Lin

引用次数: 0

Stent Design for Compensating Wall Shear Stress via Computational Modeling and Fluid Dynamics 基于计算建模和流体动力学的支架补偿壁剪应力设计

2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2016-10-01 DOI: 10.1109/BIBE.2016.46

Chun-Ming Chang, Wei Shin Wong, J. Tsai

引用次数: 0