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13th International conference on Natural Computation, Fuzzy systems and Knowledge Discovery (ICNC-FSKD)

作者： Che, Dongsheng Gao, Pingsheng Tian, Pu Chen, Bernard East Stroudsburg Univ Dept Comp Sci East Stroudsburg PA 18301 USA Univ Cent Arkansas Comp Sci Dept Conway AR 72034 USA

ISBN: (纸本)9781538621653

Genetic materials are exchanged very frequently across microbial organisms. In many cases, a cluster of adjacent genes, rather than individual genes, are transferred from one genome into another genome. The influx gene clusters in the recipient genome are also known as genomic islands (GIs). While various computational approaches have been employed to identify genomic islands, they are not universally applicable to predict any microbial genome. In this paper, we propose a genetic algorithm (GA) approach to search genomic islands for any genome. The GA evaluates candidate solutions in the population based on sequence composition based fitness value, and finds final solutions through crossover and mutation operations throughout the evolution. We applied our GA approach on four genomes. Experimental results have shown that our GA could not only find previously reported GIs, but also find some new GIs not reported before. We believe that our GA-based approach for GI finding should complement existing GI prediction tools.

关键词： Genomics bioinformatics Genetic algorithms Organisms Sociology Statistics Tools

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S2P: A Desktop Application for Fast and Easy Processing of 2D-Gel and MALDI-Based Mass Spectrometry Protein Data 1

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11th International conference on Practical Applications of computational Biology and bioinformatics (PACBB)

作者： Lopez-Fernandez, Hugo Araujo, Jose E. Glez-Pena, Daniel Reboiro-Jato, Miguel Fdez-Riverola, Florentino Capelo-Martinez, Jose L. Univ Vigo Edificio Politecn ESEI Escuela Super Ingn Informat Campus Univ As Lagoas S-N Orense 32004 Spain Univ Vigo CINBIO Ctr Invest Biomed Campus Univ Lagoas Marcosende Vigo 36310 Spain Univ Nova Lisboa UCIBIO REQUIMTE Dept Quim Fac Ciencias & Tecnol P-2829516 Caparica Portugal

ISBN: (数字)9783319608167

ISBN: (纸本)9783319608167;9783319608150

2D-gel electrophoresis is widely used in combination with MALDI-TOF mass spectrometry in order to analyse the proteome of biological samples. It can be used to discover proteins that are differentially expressed between two groups (e.g. two disease conditions) obtaining thus a set of potential biomarkers. Biomarker discovery requires a lot of data processing in order to prepare data for analysis or in order to merge data from different sources. This kind of work is usually done manually, being highly time consuming and distracting the operator or researcher from other important tasks. Moreover, doing this repetitive process in a non-automated, handling-based manner is error-prone, affecting reliability and reproducibility. To overcome these drawbacks, the S2P, an AIBench based desktop multiplatform application, has been specifically created to process 2D-gel and MALDI-mass spectrometry protein identification-based data in a computer-aided manner. S2P is open source and free to all users at http://***/s2p.

关键词： Protein identification Data processing bioinformatics tools Open source 2D-gel MALDI-TOF-MS Protein data Mascot identifications

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Guest Editorial: ieee International conference on bioinformatics and Biomedicine (BIBM 2014) Special Issue

IEEE TRANSACTIONS ON NANOBIOSCIENCE

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ieee TRANSACTIONS ON NANOBIOSCIENCE 2015年第5期14卷 498-499页

作者： Hu, Xiaohua Wang, Yadong Drexel Univ Philadelphia PA 19104 USA Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Peoples R China

The papers in this special section were presented at the ieee BIBM 2014 conference that was held in Belfast, U.K., from November 18–22, 2014. The scientific program highlights five themes to provide breadth, depth, and synergy for research collaboration: 1) genomics and molecular structure, function, and evolution; 2) computational systems biology; 3) medical informatics and translational bioinformatics; 4) cross-cutting computational methods and bioinformatics infrastructures; and 5) healthcare informatics.

关键词： Special issues and sections Informatics bioinformatics Genomics Evolution (biology) computational systems biology Meetings

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Automated subdural hematoma segmentation for traumatic brain injured (TBI) patients 39

Automated subdural hematoma segmentation for traumatic brain...

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39th Annual International conference of the ieee Engineering in Medicine and Biology Society, EMBC 2017

作者： Farzaneh, Negar Soroushmehr, S.M. Reza Williamson, Craig A. Jiang, Cheng Srinivasan, Ashok Bapuraj, Jayapalli R. Ward, Kevin R. Korley, Frederick K. Najarian, Kayvan Department of Computational Medicine and Bioinformatics University of Michigan Ann ArborMI United States Michigan Center for Integrative Research in Critical Care University of Michigan Ann ArborMI United States Department of Emergency Medicine University of Michigan Ann ArborMI United States Department of Computer Science University of Michigan Ann Arbor United States Departments of Neurosurgery and Neurology University of Michigan Ann ArborMI United States Departments of Radiology University of Michigan Ann Arbor United States

ISBN: (纸本)9781509028092

Traumatic brain injury is a serious public health problem in the U.S. contributing to a large portion of permanent disability. However, its early management and treatment could limit the impact of the injury, save lives and reduce the burden of cost for patients as well as healthcare systems. Subdural hematoma is one of the most common types of TBI, which its visual detection and quantitative evaluation are time consuming and prone to error. In this study, we propose a fully auto-mated machine learning based approach for 3D segmentation of convexity subdural hematomas. Textural, statistical and geometrical features of sample points from intracranial region are extracted based on head Computed Tomography (CT) images. Then, a tree bagger classifier is implemented to classify each pixel as hematoma or no-hematoma. Our method yields sensitivity, specificity and area under the receiver operating curve (AUC) of 85:02%, 73:74% and 0:87 respectively. © 2017 ieee.

关键词： Image segmentation Synchronous digital hierarchy Feature extraction Level set Three-dimensional displays Injuries Entropy

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computational prediction of ubiquitination protein using evolutionary profiles and functional domains

Computational prediction of ubiquitination protein using evo...

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ieee International conference on bioinformatics and Biomedicine (BIBM)

作者： Chun-Hui Xu Wang-Ren Qiu Xuan Xiao Dong Xu University of Missouri System Columbia MO US Computer Department Jing-De-Zhen Ceramic Institute Jing-De-Zhen 333046 China

ISBN: (纸本)9781509030514;9781509030507

Ubiquitination, as a post-translational modification, is a crucial biological process presented in cell signaling, death and localization. Identification of ubiquitination protein is of fundamental importance for understanding molecular mechanisms in biological systems and diseases. Although high-throughput experimental studies using mass spectrometry have identified many ubiquitination proteins and ubiquitination sites, the vast majority of ubiquitination proteins remain undiscovered, even in well studied model organisms. To reduce experimental costs, computational (in silico) methods have been introduced to predict ubiquitination sites. If we can predict whether a query protein can be ubiquitinated or not, it is meaningful by itself and helpful for predicting ubiquitination sites. However, all the computational methods so far only predict ubiquitination sites, with unsatisfactory accuracy. In this study, we developed the first computational method for predicting ubiquitination proteins without relying on ubiquitination site prediction. The method extracts features from sequence conservation information via a grey system model, as well as functional domain annotation and subcellular localization. Together with the detailed feature analysis and application of the Relief feature selection algorithm, the results of 5-fold cross-validation on three datasets achieved a high accuracy of 0.8981, with the Matthew's correlation coefficient 0.7963. Our study may guide the related experimental design and provide useful insights for studying the mechanisms and modulation of ubiquitination pathways.

关键词： Proteins Protein engineering Feature extraction Ceramics computational modeling conferences bioinformatics

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9th Asian conference on Intelligent Information and Database systems, ACIIDS 2017

9th Asian Conference on Intelligent Information and Database...

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9th Asian conference on Intelligent Information and Database systems, ACIIDS 2017

ISBN: (纸本)9783319544717

The proceedings contain 75 papers. The special focus in this conference is on Intelligent Information and Database systems. The topics include: The knowledge increase estimation framework for ontology integration on the instance level;online integration of fragmented XML documents;merging possibilistic belief bases by argumentation;graphical interface for ontology mapping with application to access control;influence of group characteristics on agent voting;an enhanced analysis of the impact of collective cardinality;a power-graph analysis of non-fast information transmission;group recommendation based on the analysis of group influence and review content;on rumor source detection and its experimental verification on twitter;topic preference-based random walk approach for link prediction in social networks;the effect of presentation in online advertising on perceived intrusiveness and annoyance in different emotional states;runtime verification and quality assessment for checking agent integrity in social commerce system;evaluation of tensor-based algorithms for real-time bidding optimization;international business matching using word embedding;mixture seeding for sustainable information spreading in complex networks;complex networks in the epidemic modelling;identification of biomedical articles with highly related core contents;an efficient hybrid model for Vietnamese sentiment analysis;simple and accurate method for parallel web pages detection;a hybrid method for named entity recognition on tweet streams;a method for user profile learning in document retrieval system using Bayesian network and answering temporal analytic queries over big data based on precomputing architecture.

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Scalability of a Genomic Data Analysis in the BioTest Platform 9th

Scalability of a Genomic Data Analysis in the BioTest Platfo...

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9th Asian conference on Intelligent Information and Database systems (ACIIDS)

作者： Psiuk-Maksymowicz, Krzysztof Mrozek, Dariusz Jaksik, Roman Borys, Damian Fujarewicz, Krzysztof Swierniak, Andrzej Silesian Tech Univ Inst Automat Control Ul Akad 16 PL-44100 Gliwice Poland Silesian Tech Univ Biotechnol Ctr Ul Krzywoustego 8 PL-44100 Gliwice Poland Silesian Tech Univ Inst Informat Ul Akad 16 PL-44100 Gliwice Poland

ISBN: (纸本)9783319544304

BioTest platform is dedicated for the processing of biomedical data that originate from various measurement techniques. This includes next-generation sequencing (NGS), that focuses the attention of researchers all of the world due to its broad possibilities in determining the structure of the DNA and RNA. However, the analysis of data provided by NGS requires large disk space, and is time-consuming, becoming a challenge for the data processing systems. In this paper, we have analyzed the possibility of scaling the BioTest platform in terms of genomic data analysis and platform architecture. Scalability tests were carried out using next-generation sequencing data and relied on methods for detection of somatic mutations and polymorphisms in the human DNA. Our results show that the platform is scalable, allowing to significantly reduce the execution time of performed calculations. However, the scalability capabilities depend on the experiment methodology and homogeneity of resources required by each task, which in NGS studies can be highly variable.

关键词： Scalability bioinformatics NGS data analysis computational platform HPC cluster Workload manager

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9th Asian conference on Intelligent Information and Database systems, ACIIDS 2017

9th Asian Conference on Intelligent Information and Database...

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9th Asian conference on Intelligent Information and Database systems, ACIIDS 2017

ISBN: (纸本)9783319544298

The proceedings contain 77 papers. The special focus in this conference is on Intelligent Information and Database systems. The topics include: Exploring spatial and social factors of crime;a fuzzy logic based network intrusion detection system for predicting the TCP SYN flooding attack;analytical ideas to improve daily demand forecasts;increasing the detection of minority class instances in financial statement fraud;to solve the TDVRPTW via hadoop mapreduce parallel computing;mapreduce-based frequent pattern mining framework with multiple item support;an optimal farmland allocation e-service deployment;anticipatory runway incursion prevention based on inaccurate position surveillance information;the relation between syntax restriction of temporal logic and properties of reactive system specification;measuring interestingness of theorems in automated theorem finding by forward reasoning;a predicate suggestion algorithm for automated theorem finding with forward reasoning;modeling a multi-criteria decision support system for capital budgeting project selection;innovative diffusion chance discovery;using sentiment analysis to explore the association between news and housing prices;importance-performance analysis based evaluation method for security incident management capability;moment shape descriptors applied for action recognition in video sequences;automatic detection of singular points in fingerprint images using convolution neural networks;vehicle detection in hsuehshan tunnel using background subtraction and deep belief network;segment counting versus prime counting in the ulam square;improving traffic sign recognition using low dimensional features and image processing approach to diagnose eye diseases.

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Nature Inspired Algorithms for Genome Subsequence Assembly in Hadoop

Nature Inspired Algorithms for Genome Subsequence Assembly i...

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ieee International conference on computational Intelligence and Computing Research

作者： G. Raja U. Srinivasulu Reddy Department of Computer Applications National Institute of Technology Trichy India

ISBN: (纸本)9781509066223

Genome subsequencing has become one of the normal requirements of the modern era due to the huge possibilities it provides for personalized medicine. Assembled genome sequencing will give valuable consciousness into numerous aspects of human life, thereby generating healthier environments and personalized treatments. The most important need of this field is for a quicker and accurate sequencing device. The methods for genome sequencing become very hard due to the massive amount of genome fragments. This paper extents an optimized genome assembly technique with nature inspired algorithm using MapReduce. DNA subsequence is initially matched with the genome to identify the possible matching locations. These identified points are then analyzed for complete matches. The consensus sequence assembly is performed by employing hamming distance identical systems. The experimental outcomes analyzed display that our method is improved and shows high coverage by providing exact sequence alignments.

关键词： bioinformatics Genomics DNA Sequential analysis Optimization Genetic algorithms Next generation networking

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Precision medicine and FPGA technology: Challenges and opportunities 60

Precision medicine and FPGA technology: Challenges and oppor...

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60th ieee International Midwest Symposium on Circuits and systems, MWSCAS 2017

作者： Hill, Brian Smith, Jaclyn Srinivasa, Gans Sonmez, Kemal Sirasao, Ashish Gupta, Amit Mukherjee, Madhubanti Omics Data Automation Inc OR United States University of California Los AngelesCA United States Oregon Health Sciences University OR United States Xilinx Inc CA United States

ISBN: (纸本)9781509063895

As genomic medicine becomes part of standard clinical care, Precision Medicine faces a daunting computational challenge in scaling up to support the genomic, image processing and analytics workloads required for millions of patients, especially in oncology clinics. computational solutions based on heterogeneous hardware platforms like FPGAs have the potential to enable rollout of personalized care for large numbers of patients. We review several clinical use cases to shed light on how FPGA-based solutions can lead to large performance gains and tackle the computational bottlenecks in precision medicine. The biggest barrier to FPGA adoption is their accessibility and the steep learning curve for many bioinformatics and precision medicine codebase development groups. We describe new standard libraries and development environments that will facilitate FPGA-based development and show how they enable performance improvements with modest effort investment. © 2017 ieee.

关键词： Genome

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