2011 IEEE 11th International Conference on Bioinformatics and Bioengineering最新文献

Repetition Coding as an Effective Error Correction Code for Information Encoded in DNA 重复编码作为DNA编码信息的有效纠错码

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.45

D. Haughton, F. Balado

引用次数: 16

Three-dimensional Vision-based Nail-fold Morphological and Hemodynamic Analysis 基于三维视觉的甲襞形态及血流动力学分析

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.14

L. Lo, John Y. Chiang, Yu-shan Cai

{"title":"Three-dimensional Vision-based Nail-fold Morphological and Hemodynamic Analysis","authors":"L. Lo, John Y. Chiang, Yu-shan Cai","doi":"10.1109/BIBE.2011.14","DOIUrl":"https://doi.org/10.1109/BIBE.2011.14","url":null,"abstract":"In this paper, a Three-dimensional Vision-based Nail-fold Morphological and Hemodynamic Analysis (TVNMHA) is proposed to automatically extract morphological/hemodynamic features from an image sequence, reconstruct the corresponding three-dimensional vacular tubular models, and visualize the dynamic blood flow in the model constructed. The morphological features extracted include number, density, width/height, width of the curved segment, arteriolar limb caliber, curved segment caliber, venular limb caliber, blood color and tortuosity of capillaries. The corresponding pathological information derived has a spatial precision accurate up to 1.6£gm. TVNMHA also employs optical flow method (OFM) to measure the velocity of the flowing plasma gaps between two consecutive frames with an error 10~32£gm/sec [1]. The laser Doppler velocimetry is a common tool employed in measuring capillary with larger diameter (is about 500£gm). The average velocity of an area measured comes with an error around 100£gm/sec [2], much higher than that of TVNMHA. TVNMHA can separately derive velocities for each capillaries within the whole microscopic range and obtain diversified morphological/hemodynamic features of capillaries with a low-cost equipment setup.","PeriodicalId":391184,"journal":{"name":"2011 IEEE 11th International Conference on Bioinformatics and Bioengineering","volume":"73 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116237168","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

Identifying Hub Proteins and Their Essentiality from Protein-protein Interaction Network 从蛋白-蛋白相互作用网络中鉴定枢纽蛋白及其必要性

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.67

S. A. Bakar, J. Taheri, Albert Y. Zomaya

引用次数: 2

Parallel Association Rule Mining for Medical Applications 医学应用的并行关联规则挖掘

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.31

G. Zhang, C. Xu, P. Sheu, H. Yamaguchi

引用次数: 6

Gene Expression Data Classification Using Locality Preserving Projections 基于局部保留投影的基因表达数据分类

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.17

Houqin Bian, R. Chung

{"title":"Gene Expression Data Classification Using Locality Preserving Projections","authors":"Houqin Bian, R. Chung","doi":"10.1109/BIBE.2011.17","DOIUrl":"https://doi.org/10.1109/BIBE.2011.17","url":null,"abstract":"Classification analysis of gene expression data could lead to knowledge of gene functions and diseases mechanisms. However, the data involve nonlinear interactions among genes and environmental factors. Worst yet, while the data are usually of high dimensions, the sample sizes acquirable are generally relatively small, resulting in the well known difficulty ¨C the curse of dimensionality ¨C in the classification task. This work describes how gene expression data can be analyzed using Locality Preserving Projections (LPP) manifold learning method. LPP is a dimensionality reduction strategy for feature selection and visualization. Using LPP, the high dimensional gene expression data are mapped to a low dimensional subspace for data analysis. LPP finds the optimal linear approximations to the eigen functions of the Laplace Beltrami operator on the manifold. Not only does it share many convenient data-representation properties of the nonlinear techniques like Laplacian Eigenmaps or Locally Linear Embedding, it is also linear and more crucially is defined everywhere in the ambient space rather than just on the training data points. Comparative experimental results with PCA, LDA, LLE, etc. on different gene expression datasets show that the LPP-based method has the potential of being more efficient for complex gene expression data classification.","PeriodicalId":391184,"journal":{"name":"2011 IEEE 11th International Conference on Bioinformatics and Bioengineering","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130799762","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

The Length Evolution of 5' Untranslated Regions - The Stochastic Model Revisited 5'非翻译区长度演化——重新考察随机模型

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.32

Chun-Hsi Chen, Hsuan-Yu Lin, C. Pan, Feng-Chi Chen

{"title":"The Length Evolution of 5' Untranslated Regions - The Stochastic Model Revisited","authors":"Chun-Hsi Chen, Hsuan-Yu Lin, C. Pan, Feng-Chi Chen","doi":"10.1109/BIBE.2011.32","DOIUrl":"https://doi.org/10.1109/BIBE.2011.32","url":null,"abstract":"The length evolution of 5’ untranslated regions (5’UTRs) is a fundamental issue in molecular evolution. 5’UTRs are important for both transcriptional and translational regulations. These regulatory regions are suggested to elongate with increased organismal complexity and decreased effective population size. However, the factors that determine the lengths of 5’UTRs remain elusive. A stochastic model has been proposed to explain the length evolution of 5’UTRs. This model posits that the lengths of 5’UTRs change due to the stochastic process of gains/losses of the transcription initiation signals, with upstream start codons (uAUGs, a translation repressor signal) as the major constraint to suppress 5’UTR elongation. This model predicts that species with larger effective population sizes have shorter 5’UTRs because the high efficiency of selection can effectively restrain deleterious elongation of 5’UTRs in these species. However, here we demonstrate that Drosophila melanogaster has significantly longer 5’UTRs than mouse, chicken, frog, and zebrafish despite the insect’s very large effective population size. We further show that the exceptionally long 5’UTRs in D. melanogaster do not result from relaxed selection pressure on uAUGs, biased nucleotide composition, or lineage-specific gains/losses of genes. Interestingly, two other insect species – honeybee and mosquito – also have comparably long 5’UTRs, which are longer than those of other invertebrates. Therefore, the stochastic model cannot explain the differences in 5’UTR length across species. Rather, lineage-specific factors may play an important role in this regard. The generality of the stochastic model thus needs to be re-considered. Keywords5’untranslated region; upstream start codon; evolution; effective population size","PeriodicalId":391184,"journal":{"name":"2011 IEEE 11th International Conference on Bioinformatics and Bioengineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130992414","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 Observation on Circulatory System of Vegetative State Patient with Music Therapy 音乐治疗对植物人循环系统的影响

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.28

Yaw-Chern Lee, Hui-Min Wang, Hui-Ya Chiang, Sheng-Chieh Huang

引用次数: 0

Gene Networks Validation based on Metabolic Pathways 基于代谢途径的基因网络验证

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.10

Francisco Gómez-Vela, N. Díaz-Díaz, J. Aguilar-Ruiz

{"title":"Gene Networks Validation based on Metabolic Pathways","authors":"Francisco Gómez-Vela, N. Díaz-Díaz, J. Aguilar-Ruiz","doi":"10.1109/BIBE.2011.10","DOIUrl":"https://doi.org/10.1109/BIBE.2011.10","url":null,"abstract":"In the last few years, DNA microarray technology has attained a very important role in biological and biomedical research. It enables analyzing the relations among thousands of genes simultaneously, generating huge amounts of data. The gene networks represent, in a graph data structure, genes or gene products and the functional relationships between them. These models have been fully used in Bioinformatics because they provide an easy way to understand gene expression regulation. Nowadays, a lot of gene network algorithms have been developed as knowledge extraction techniques. A very important task in all these studies is to assure the network models reliability in order to prove that the methods used are precise. This validation process can be carried out by using the inherent information of the input data or by using public biological knowledge. In this last case, these sources of information provide a great opportunity of verifying the biological soundness of the generated networks. In this work, authors present a gene network validation methodology based on the information stored in KEGG database. With this aim, a complete KEGG pathway conversion to gene network is presented, and a global and functional validation process is proposed, where the whole metabolical information stored in KEGG is used at the same time.","PeriodicalId":391184,"journal":{"name":"2011 IEEE 11th International Conference on Bioinformatics and Bioengineering","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115734443","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

Effects of Poly-L-Ornithine and Fibronectin Coatings for Human Melanocyte Cell Illuminating Experiments 聚l -鸟氨酸和纤维连接蛋白涂层对人黑素细胞照明实验的影响

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.56

Chung-Jen Ou, I. Ching, C. Ou

引用次数: 0

Rough-Fuzzy Hybrid Approach for Identification of Bio-markers and Classification on Alzheimer's Disease Data 阿尔茨海默病数据生物标记物识别与分类的粗糙-模糊混合方法

2011 IEEE 11th International Conference on Bioinformatics and Bioengineering Pub Date : 2011-10-24 DOI: 10.1109/BIBE.2011.20

C. Lee, C. Lam, M. Masek

{"title":"Rough-Fuzzy Hybrid Approach for Identification of Bio-markers and Classification on Alzheimer's Disease Data","authors":"C. Lee, C. Lam, M. Masek","doi":"10.1109/BIBE.2011.20","DOIUrl":"https://doi.org/10.1109/BIBE.2011.20","url":null,"abstract":"A new approach is proposed in this paper for identification of biomarkers and classification on Alzheimer's disease data by employing a rough-fuzzy hybrid approach called ARFIS (a framework for Adaptive TS-type Rough-Fuzzy Inference Systems). In this approach, the entropy-based discretization technique is employed first on the training data to generate clusters for each attribute with respect to the output information. The rough set-based feature reduction method is then utilized to reduce the number of features in a decision table obtained using the cluster information. Another rough set-based approach is employed for the generation of decision rules. After the construction and the evaluation phases of the proposed rough-fuzzy hybrid system, the classification is carried out on the testing set of the given data. The experimental results showed that the proposed approach achieved compatible classification results on Alzheimer's disease data compared to results from other existing approaches in the literature. It can be concluded that the proposed rough-fuzzy hybrid approach is a novel approach in predictive data mining in clinical medicine in terms of utilizing 1) rough set-based approaches for feature reduction and rule generation, 2) a hybrid fuzzy system for pattern classification, and revealing 3) rules for prediction of diagnostic results.","PeriodicalId":391184,"journal":{"name":"2011 IEEE 11th International Conference on Bioinformatics and Bioengineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123647404","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: 4