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ieee International conference on bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Huang, Lei Liao, Li Wu, Cathy H. Univ Delaware Dept Comp & Informat Sci Newark DE 19716 USA Univ Delaware Ctr Bioinformat & Computat Biol Newark DE 19711 USA

ISBN: (纸本)9781467367981

Reconstruction of PPI networks is a central task in systems biology, and inference from multiple heterogeneous data sources offers a promising computational approach to making de novo PPI prediction by leveraging complementary information and the partial network structure. However, how to quickly learn weights for heterogeneous data sources remains a challenge. In this work, we developed a method to infer de novo PPIs by combining multiple data sources represented in kernel format and obtaining optimal weights based on random walk over the existing partial network. Our proposed method utilizes Baker algorithm and the training data to construct a transition matrix which constrains how a random walk would traverse the partial network. Multiple heterogeneous features for the proteins in the network, including gene expression and Pfam domain profiles, are then combined into the form of a weighted kernel, which provides a new "adjacency matrix" for the whole network but is required to comply with the transition matrix on the part of the training subnetwork. This requirement is met by adjusting the weights to minimize the element-wise difference between the transition matrix and the weighted kernel. The minimization problem is solved by linear programming. The weighted kernel is then transformed to regularized Laplacian (RL) kernel to infer missing or new edges in the PPI network. The results on synthetic data and real data from Yeast show that the accuracy of PPI prediction measured by AUC is increased by up to 19% as compared to a control method without using optimal weights. Moreover, the weights learned by our method Weight Optimization by Linear Programming (WOLP) are very consistent with that learned by sampling, and can provide insights into the relations between PPIs and various feature kernels, thereby improving PPI prediction.

关键词： bioinformatics Electronics packaging Genomics Kernel Proteins Weight measurement Data sources systems biology Proteins Random walk linear programming Genomics Seeds pulse position indicator Kernel S matrix Electronics packaging Weighing bioinformatics

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9th International conference on Practical Applications of computational Biology and bioinformatics 9

9th International Conference on Practical Applications of Co...

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9th International conference on Practical Applications of computational Biology and bioinformatics, PACBB 2015

作者： Overbeek, Ross Rocha, Miguel P. Fdez-Riverola, Florentino De Paz, Juan F. Fellowship for the Interpretation of Genomes Burr RidgeIL United States Department of Informatics Centre of Biological Engineering University of Minho Braga Portugal Department of Informatics ESEI: Escuela Superior de Ingeniería Informática University of Vigo Ourense Spain Departamento de Informática y Automática University of Salamanca Salamanca Spain

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Transfer Learning for Survival Analysis via Efficient L2,1-Norm Regularized Cox Regression

Transfer Learning for Survival Analysis via Efficient L2,1-N...

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ieee International conference on Data Mining (ICDM)

作者： Yan Li Lu Wang Jie Wang Jieping Ye Chandan K. Reddy Dept. of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI Dept. of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI Dept. of Computer Science Wayne State University Detroit MI Dept. of Computer Science Virginia Tech Arlington VA

ISBN: (纸本)9781509054749

In survival analysis, the primary goal is to monitor several entities and model the occurrence of a particular event of interest. In such applications, it is quite often the case that the event of interest may not always be observed during the study period and this gives rise to the problem of censoring which cannot be easily handled in the standard regression approaches. In addition, obtaining sufficient labeled training instances for learning a robust prediction model is a very time consuming process and can be extremely difficult in practice. In this paper, we propose a transfer learning based Cox method, called Transfer-Cox, which uses auxiliary data to augment learning when there are insufficient amount of training examples. The proposed method aims to extract "useful" knowledge from the source domain and transfer it to the target domain, thus potentially improving the prediction performance in such time-to-event data. The proposed method uses the l 2,1 -norm penalty to encourage multiple predictors to share similar sparsity patterns, thus learns a shared representation across source and target domains, potentially improving the model performance on the target task. To speedup the computation, we apply the screening approach and extend the strong rule to sparse survival analysis models in multiple high-dimensional censored datasets. We demonstrate the performance of the proposed transfer learning method using several synthetic and high-dimensional microarray gene expression benchmark datasets and compare with other related competing state-of-the-art methods. Our results show that the proposed screening approach significantly improves the computational efficiency of the proposed algorithm without compromising the prediction performance. We also demonstrate the scalability of the proposed approach and show that the time taken to obtain the results is linear with respect to both the number of instances and features.

关键词： Analytical models Learning systems Data models Hazards Predictive models Prediction algorithms Standards

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Hardware image assessment for wireless endoscopy capsules

Hardware image assessment for wireless endoscopy capsules

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Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： M. A. Khorsandi N. Karimi S. Samavi M. Hajabdollahi S. M.R. Soroushmehr K. Ward K. Najarían Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Department of Emergency Medicine University of Michigan Ann Arbor U.S.A. Michigan Center for Integrative Research in Critical Care Emergency Medicine Department University of Michigan Ann Arbor U.S.A. Department of Computational Medicine and Bioinformatics Department of Emergency Medicine Michigan Center for Integrative Research in Critical Care University of Michigan Ann Arbor U.S.A.

ISBN: (纸本)9781457702198

Wireless capsule endoscopy is a new technology in the realm of telemedicine that has many advantages over the traditional endoscopy systems. Transmitted images should help diagnosis of diseases of the gastrointestinal tract. Two important technical challenges for the manufacturers of these capsules are power consumption and size of the circuitry. Also, the system must be fast enough for real-time processing of image or video data. To solve this problem, many hardware designs have been proposed for implementation of the image processing unit. In this paper we propose an architecture that could be used for the assessment of endoscopy images. The assessment allows avoidance of transmission of medically useless images. Hence, volume of data is reduced for more efficient transmission of images by the endoscopy capsule. This is done by color space conversion and moment calculation of images captured by the capsule. The inputs of the proposed architecture are RGB image frames and the outputs are images with converted colors and calculated image moments. Experimental results indicate that the proposed architecture has low complexity and is appropriate for a real-time application.

关键词： Image color analysis Hardware Computer architecture Endoscopes Power demand Pipelines Wireless sensor networks

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Human CODIS STR loci profiling from HTS data

Human CODIS STR loci profiling from HTS data

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ieee conference on Technologies for Homeland Security

作者： Darrell O. Ricke Martha Petrovick Johanna Bobrow Tara Boettcher Christina Zook James Harper Edward Wack Eric Schwoebel Bioengineering Systems and Technologies Massachusetts Institute of Technology Lexington MA USA

ISBN: (纸本)9781509007714

Human DNA identification is currently performed by amplifying a small, defined set of short tandem repeat (STR) loci (e.g. CODIS) and analyzing the size of the alleles present at those loci by capillary electrophoresis. High-throughput DNA sequencing (HTS) could enable the simultaneous analysis of many additional STR and single nucleotide polymorphism (SNP) loci, improving accuracy and discrimination. However, it is necessary to demonstrate that HTS can generate accurate data on the CODIS loci to enable backwards compatibility with the FBI NDIS database. Sequencing can also detect novel polymorphisms within alleles that migrate with identical sizes by capillary electrophoresis, improving allele discrimination, and enhancing human identification analysis. All CODIS alleles from an individual can be amplified in a single, multiplex PCR reaction, and combined with additional barcoded samples prior to sequencing. A computational tool for allele identification from multiplexed sequence data has been developed. With longer-read-length platforms, 99.6% allele calling accuracy can be achieved. In the course of STR sequencing protocol development, 12 novel allele sequences have been identified for multiple loci. Sequencing STR loci combined with SNPs will enable new forensic applications.

关键词： Sequential analysis DNA Forensics Multiplexing Protocols bioinformatics High-temperature superconductors

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Next Generation Biobanks 3

Next Generation Biobanks

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ieee International conference on Big Data

作者： Seebode, Christian Ort, Matthias Hufnagl, Peter Regenbrecht, Christian R. A. ORTEC Med Berlin Germany Charite Inst Pathol Berlin Germany

ISBN: (纸本)9781479999255

Biobanks have a long tradition of being mere repositories of cells and tissues. Their best use is in retrospective studies, where stored tissues and cells can be used to address scientific questions, but this paradigm has been changing lately. Biobanks need to inhabit a different role in the scientific process. In fact the information contained in biobanks can fuel the scientific reasoning itself more than just accompanying with management of specimens and data. We present a biobank architecture based on our product Health Intelligence Platform (HIP) that supports these requirements. We describe a way to support scientific reasoning directly with HIP and integrate sample management in a way that it contributes to scientific reasoning and outcome.

关键词： Health information management bioinformatics computational systems biology

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9th International conference on Practical Applications of computational Biology and bioinformatics, PACBB 2015

9th International Conference on Practical Applications of Co...

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9th International conference on Practical Applications of computational Biology and bioinformatics, PACBB 2015

ISBN: (纸本)9783319197753

The proceedings contain 15 papers. The special focus in this conference is on Practical Applications of computational Biology and bioinformatics. The topics include: A preliminary assessment of three strategies for the agent-based modeling of bacterial conjugation;a screening tool for culture medium composition and cell metabolic profiles;an integrated computational platform for metabolomics data analysis;a new dimensionality reduction technique based on HMM for boosting document classification;diagnostic knowledge extraction from medlineplus;a text mining approach for the extraction of kinetic information from literature;a novel search engine supporting specific drug queries and literature management;identification of a putative ganoderic acid pathway enzyme in a ganoderma australe transcriptome by means of a hidden Markov model;a new bioinformatic pipeline to address the most common requirements in RNA-seq data analysis;microarray gene expression data integration;an application to brain tumor grade determination and obtaining relevant genes by analysis of expression arrays with a multi-agent system.

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DPNuc: Identifying Nucleosome Positions Based on the Dirichlet Process Mixture Model

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2015年第6期12卷 1236-1247页

作者： Chen, Huidong Guan, Jihong Zhou, Shuigeng Tongji Univ Dept Comp Sci & Technol Shanghai 201804 Peoples R China Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China

Nucleosomes and the free linker DNA between them assemble the chromatin. Nucleosome positioning plays an important role in gene transcription regulation, DNA replication and repair, alternative splicing, and so on. With the rapid development of ChIP-seq, it is possible to computationally detect the positions of nucleosomes on chromosomes. However, existing methods cannot provide accurate and detailed information about the detected nucleosomes, especially for the nucleosomes with complex configurations where overlaps and noise exist. Meanwhile, they usually require some prior knowledge of nucleosomes as input, such as the size or the number of the unknown nucleosomes, which may significantly influence the detection results. In this paper, we propose a novel approach DPNuc for identifying nucleosome positions based on the Dirichlet process mixture model. In our method, Markov chain Monte Carlo (MCMC) simulations are employed to determine the mixture model with no need of prior knowledge about nucleosomes. Compared with three existing methods, our approach can provide more detailed information of the detected nucleosomes and can more reasonably reveal the real configurations of the chromosomes;especially, our approach performs better in the complex overlapping situations. By mapping the detected nucleosomes to a synthetic benchmark nucleosome map and two existing benchmark nucleosome maps, it is shown that our approach achieves a better performance in identifying nucleosome positions and gets a higher F-score. Finally, we show that our approach can more reliably detect the size distribution of nucleosomes.

关键词： DNA Biological Cells bioinformatics Noise Measurement Estimation computational Modeling Genomics

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ICCSS 2015 - Proceedings: 2015 International conference on Informative and Cybernetics for computational Social systems

ICCSS 2015 - Proceedings: 2015 International Conference on I...

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International conference on Informative and Cybernetics for computational Social systems, ICCSS 2015

ISBN: (纸本)9781467372459

The proceedings contain 26 papers. The topics discussed include: robust audio watermarking scheme via QIM of correlation coefficients using LWT and QR decomposition;the research of automatic horizontal adjustment of stereoscopic video shooting cradle head;a novel feature fusion method for predicting protein subcellular localization with multiple sites;a novel approach for virtual facial shape cloning and makeup reproducing;a distributed k-means clustering algorithm in wireless sensor networks;a flick biometric authentication mechanism on mobile devices;intelligent mobile web service for bioinformatics systems;enhanced hierarchical fuzzy model using evolutionary GA with modified ABC algorithm for classification problem;matrix completion via extended linearized augmented Lagrangian method of multipliers;approximate optimal vibration control for systems with delayed state under persistent disturbances;and control of nonlinear systems with full state constraints using integral barrier Lyapunov functionals.

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3rd International Work-conference on bioinformatics and Biomedical Engineering, IWBBIO 2015

3rd International Work-Conference on Bioinformatics and Biom...

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3rd International Work-conference on bioinformatics and Biomedical Engineering, IWBBIO 2015

ISBN: (纸本)9783319164793

The proceedings contain 70 papers. The special focus in this conference is on eHealth, Next generation sequencing and sequence analysis, Quantitative and systems pharmacology, Hidden markov model (HMM) for biological sequence modeling, Advances in computational intelligence for bioinformatics and biomedicine and Tools for next generation sequencing data analysis. The topics include: e-health informed foreign patient and physician communication;empirical analysis of the effect of eHealth on medical expenditures of patients with chronic diseases;impact of health apps in health and computer science publications. a systematic review from 2010 to 2014;local search for multi objective multiple sequence alignment;alignment free frequency based distance measures for promoter sequence comparison;energy-efficient architecture for DP local sequence alignment;successes and pitfalls in scoring molecular interactions;the use of random forest to predict binding affinity in docking;strong inhomogeneity in triplet distribution alongside a genome;predicting sub-cellular location of proteins based on hierarchical clustering and hidden markov models;risk quantification of multigenic conditions for SNP array based direct-to-consumer genomic services;computational inference in systems biology;a price we pay for inexact dimensionality reduction;DEgenes hunter - a self-customised gene expression analysis workflow for non-model organisms;bioinformatics analyses to separate species specific mrnas from unknown sequences in de novo assembled transcriptomes;evaluation of combined genome assemblies;nucleotide sequence alignment and compression via shortest unique substring and modeling of the urothelium with an agent based approach.

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