2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)最新文献_第5页

A Feature Preserved Mesh Subdivision Framework for Biomedical Mesh 生物医学网格的特征保留网格细分框架

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-22

J. Yang, Y. Gong, Hefeng Wu, Qi Li

引用次数: 0

Classification of Interictal Epileptiform Discharges using Partial Directed Coherence 部分定向相干性对癫痫发作间期放电的分类

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.000-9

Panuwat Janwattanapong, M. Cabrerizo, Chen Fang, H. Rajaei, Alberto Pinzon-Ardila, S. Gonzalez-Arias, M. Adjouadi

{"title":"Classification of Interictal Epileptiform Discharges using Partial Directed Coherence","authors":"Panuwat Janwattanapong, M. Cabrerizo, Chen Fang, H. Rajaei, Alberto Pinzon-Ardila, S. Gonzalez-Arias, M. Adjouadi","doi":"10.1109/BIBE.2017.000-9","DOIUrl":"https://doi.org/10.1109/BIBE.2017.000-9","url":null,"abstract":"This paper introduces the classification of patterns extracted from different types of interictal epileptiform discharges (IEDs) that includes interictal spike (IS), spike and slow wave complex (SSC), and repetitive spikes and slow wave complex (RSS)), using the partial directed coherence (PDC) analysis. The PDC analysis estimates the intensity and direction of propagation from neural activities generated in the cerebral cortex, and analyzes the coefficients obtained from employing multivariate autoregressive model (MVAR). Features extracted by using PDC are transformed into binary matrices by using surrogate data testing with a 0.05 significance level. The significant propagations are represented as 1 in the binary matrix and 0 otherwise. Binary matrices are converted into binary vectors. These vectors are then selected as the inputs of a multilayer Perceptron (MLP) neural network. The first classifier is trained to distinguish between 2 types of IEDs and tenfold cross validation is implemented to evaluate the system. The performance of the classifier was evaluated, where it achieved the highest F1 score of 100.00% when performed on IS vs RSS and 96.67% on IS vs CSS. The average F1 score of the first classifier obtained was 91.11%. The second classifier was trained to perform all types of IEDs classifications. The classifier yielded an overall accuracy of 86.67% with the highest achieved F1 score of 90.00%. Both classifiers were able to detect and classify different types of IEDs when using the features extracted from PDC with a very high performance.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116186436","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

Streaming Distributed DNA Sequence Alignment Using Apache Spark 流式分布式DNA序列比对使用Apache Spark

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-57

Hamid Mushtaq, Nauman Ahmed, Z. Al-Ars

{"title":"Streaming Distributed DNA Sequence Alignment Using Apache Spark","authors":"Hamid Mushtaq, Nauman Ahmed, Z. Al-Ars","doi":"10.1109/BIBE.2017.00-57","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-57","url":null,"abstract":"The large amount of data generated by NextGeneration Sequencing (NGS) technology, usually in the order of hundreds of gigabytes per experiment, has to be analyzed quickly to generate meaningful variant results. The first step in analyzing such data is to map those sequenced reads to their corresponding positions in the human genome. One of the most popular tools to do such sequence alignment is the Burrows-Wheeler Aligner (BWA mem). One limitation of the BWA program though is that it cannot be run on a cluster. In this paper, we propose StreamBWA, a new framework that allows the BWA mem program to run on a cluster in a distributed fashion, at the same time while the input data is being streamed into the cluster. It can process the input data directly from a compressed file, which either lies on the local file system or on a URL. Moreover, StreamBWA can start combining the output files of the distributed BWA mem tasks at the same time while these tasks are still being executed on the cluster. Empirical evaluation shows that this streaming distributed approach is approximately 2x faster than the nonstreaming approach. Furthermore, our streaming distributed approach is 5x faster than other state-of-the-art solutions such as SparkBWA. The source code of StreamBWA is publicly available at https://github.com/HamidMushtaq/StreamBWA.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128685774","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: 12

Real-time QRS detector using Stationary Wavelet Transform for Automated ECG Analysis 基于平稳小波变换的实时QRS检测器用于心电自动分析

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-12

Vignesh Kalidas, L. Tamil

引用次数: 49

Is Central Origin of Muscle Fatigue Distinguished Solely in Finger Tapping Performance? 肌肉疲劳的中枢起源是否只在手指敲击动作中有区别?

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00009

Leyla Aydin, E. Kiziltan, Ersin E, Bahadir Azizaaolu, Arda Bekkaraman, S. Doan, Gizem Ertirk, Cansel Ku

{"title":"Is Central Origin of Muscle Fatigue Distinguished Solely in Finger Tapping Performance?","authors":"Leyla Aydin, E. Kiziltan, Ersin E, Bahadir Azizaaolu, Arda Bekkaraman, S. Doan, Gizem Ertirk, Cansel Ku","doi":"10.1109/BIBE.2017.00009","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00009","url":null,"abstract":"Ischemia in presence of drug induced long QT syndrome 2 (LQTS2) predisposes the tissue to Torsade de pointes (TdP). Reentrant arrhythmias occurring during phase 1B of ischemia have been primarily associated with areas of cellular uncoupling and hyperkalaemia. This study aims to investigate how a region of lowered gap junction conductance (GJC) in presence of LQTS2 can initiate a TdP. Here, a discrete grid of 250x100 cells interconnected using GJCs is taken representing a portion of the transmural wall with anisotropic conduction velocities. LQTS2 is introduced by reducing the potassium current (IKr) of all cells to 50%. An ischemic zone is located almost in the centre of the mid myocardium layer in the form of an elliptic inhomogeneity with varying percentage reduction of GJC compared to the surrounding. Results show that reduction of intercellular conductance in a midmyocardial island can cause a non-sustained reentrant arrhythmia to develop due to premature pacing beats. Addition of hyperkalaemic conditions in the ischemic zone has the effect of prolonging the arrhythmia.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134255856","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

High Performance Streaming Smith-Waterman Implementation with Implicit Synchronization on Intel FPGA using OpenCL 基于OpenCL的Intel FPGA上隐式同步的高性能流Smith-Waterman实现

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.000-6

Ernst Houtgast, V. Sima, Z. Al-Ars

引用次数: 22

ES1D: A Deep Network for EEG-Based Subject Identification 基于脑电图的主题识别深度网络

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-74

Pablo Arnau-González, Stamos Katsigiannis, N. Ramzan, D. Tolson, M. Arevalillo-Herráez

引用次数: 20

Towards Probabilistic Simulation of Tandem Mass Spectrometry Fragmentation Applied for Peptide Identification 串联质谱破碎法用于多肽鉴定的概率模拟

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-27

H. Loukil, M. Tmar, M. Louati, A. Masmoudi, F. Gargouri

{"title":"Towards Probabilistic Simulation of Tandem Mass Spectrometry Fragmentation Applied for Peptide Identification","authors":"H. Loukil, M. Tmar, M. Louati, A. Masmoudi, F. Gargouri","doi":"10.1109/BIBE.2017.00-27","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-27","url":null,"abstract":"Peptide identification using mass spectrometry is an indispensable tool in the field of proteomics. There is already a wide range of approaches in the literature that attempt to infer peptides throughout various computational methods mixed with several biology properties. An important progress in the proteomics research has led a strong need for more efficient and accurate approaches for peptide identification. The accuracy and efficiency of these techniques is indispensable to ensure as many correctly identified peptides as possible. In this paper, we start by a comparison of database search and de novo peptide identification. We then present the main impact of cleavage distribution on intensity values during fragmentation process. Next, we present our proposed method of peptide identification by integrating intensity distribution in both database and de novo methods in order to improve the identification process. Other features have been taken into account in our calculation such as water and ammonia losses, and the correlation between amino acids. Then, we present the experiments and results applied to evaluate our approach in order to prove and ensure the effectiveness of our hypothesis. Finally, we propose our perspectives on future work by giving our thoughtful solutions for several problems that prevent to reach the correct identification.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122034492","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

Selecting Optimal Models Based on Efficiency and Robustness in Multi-valued Biological Networks 基于效率和鲁棒性的多值生物网络最优模型选择

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-55

Hooman Sedghamiz, Wenxiang Chen, Mark Rice, L. D. Whitley, G. Broderick

{"title":"Selecting Optimal Models Based on Efficiency and Robustness in Multi-valued Biological Networks","authors":"Hooman Sedghamiz, Wenxiang Chen, Mark Rice, L. D. Whitley, G. Broderick","doi":"10.1109/BIBE.2017.00-55","DOIUrl":"https://doi.org/10.1109/BIBE.2017.00-55","url":null,"abstract":"In this paper, we propose an optimization algorithm for literature-derived model and parameter identification in multi-valued biological regulatory networks. Our approach is a multi-objective optimization method where the objectives are inspired from structural Efficiency, dynamical Robustness and biological selectivity of cells in their actions. Given an incomplete model derived from literature and partially instrumented clinical observations, our method identifies the optimal model parameterization by maximizing structural Efficiency, dynamical Robustness and Selectivity. As the parameterization space is super exponential, we implemented our method in a constraint satisfaction framework by defining logical equivalences of the dynamical features. The implemented framework is then solved with a lazy clause solver known as Chuffed. We apply our method on female Hypothalamic-Pituitary-Gonadal axis (HPG) and demonstrate how it is able to identify a model that reproduces the complex menstrual cycle. The algorithm found a structure and parameterization for the 5 node 14 edge (~50% edge density) HPG model with a normalized length cost and robustness of 1.46 and 0.35 respectively in 713 seconds on an Intel core i7 machine.Our method discovered that there are at least 6 more regulatory interactions that must be added to the commonly accepted HPG basic model in order to reproduce the menstrual cycle efficiently and robustly. The discovery of additional interactions suggest that our algorithm provides new insight to the biological model identification by combining the information from literature, clinical measurements and dynamical parameters.","PeriodicalId":262603,"journal":{"name":"2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129659918","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: 8

Determination of Dialysis Access Patency Using 2D Angiographic Images 利用二维血管造影图像测定透析通路通畅

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) Pub Date : 2017-10-01 DOI: 10.1109/BIBE.2017.00-34

N. Koirala, R. Setser, J. Bullen, G. McLennan

引用次数: 3