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Local dimension-reduced dynamical spatio-temporal models for resting state network estimation

Brain Informatics 2015年第2期2卷 53-63页

作者： Vieira, Gilson Amaro, Edson Baccalá, Luiz A. Inter-institutional Grad Program on Bioinformatics University of São Paulo São Paulo Brazil LIM-44 Department of Radiology University of São Paulo São Paulo Brazil Escola Politécnica University of São Paulo São Paulo Brazil

To overcome the limitations of independent component analysis (ICA), today’s most popular analysis tool for investigating whole-brain spatial activation in resting state functional magnetic resonance imaging (fMRI), we present a new class of local dimension-reduced dynamical spatio-temporal model which dispenses the independence assumptions that severely limit deeper connectivity descriptions between spatial components. The new method combines novel concepts of group sparsity with contiguity-constrained clusterization to produce physiologically consistent regions of interest in illustrative fMRI data whose causal interactions may then be easily estimated, something impossible under the usual ICA assumptions. © 2015, The Author(s).

关键词： Activation analysis

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ENERGY-BASED ARCHITECTURE FOR CLASSIFICATION OF PUBLICATION FIGURES

ENERGY-BASED ARCHITECTURE FOR CLASSIFICATION OF PUBLICATION ...

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Annual ORNL Biomedical Sciences and Engineering Conference on Collaborative Biomedical Innovations

作者： P. E. Barbano M. L. Nagy M. Krauthammer Department of Mathematics Yale University Program for Computational Biology and Bioinformatics Yale University

ISBN: (纸本)9781479921195

We present an implementation of the experimental and theoretical results obtained in the analysis of text and image content of biomedical publications. Particularly, we propose a novel optical recognition system using an adaptive algorithm for the classification and analysis of highly heterogeneous images in research papers. When compared with conventional algorithms, our technology substantially increases the probability of detection and classification of images buried in text or obscured by other images. We report successful testing of the new architecture using PubMed publications.

关键词： publications images ARCHITECTURE Classification of algorithms new buildings Taxonomy texts optical identification WWOX gene Image classification

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Segment Self-Repulsion is the Major Driving Force of Influenza Genome Packaging

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Physical Review Letters 2013年第9期110卷 098104-098104页

作者： Sergey V. Venev Konstantin B. Zeldovich Program in Bioinformatics and Integrative Biology University of Massachusetts Medical School 55 Lake Avenue North Worcester Massachusetts 01655 USA

The genome of influenza A virus consists of eight separate RNA segments, which are selectively packaged into virions prior to virus budding. The microscopic mechanism of highly selective packaging involves molecular interactions between packaging signals in the genome segments and remains poorly understood. We propose that the condition of proper packaging can be formulated as a large gap between RNA-RNA interaction energies in the viable virion with eight unique segments and in improperly packed assemblages lacking the complete genome. We then demonstrate that selective packaging of eight unique segments into an infective influenza virion can be achieved by self-repulsion of identical segments at the virion assembly stage, rather than by previously hypothesized intricate molecular recognition of particular segments. Using Monte Carlo simulations to maximize the energy gap, without any other assumptions, we generated model eight-segment virions, which all display specific packaging, strong self-repulsion of the segments, and reassortment patterns similar to natural influenza. The model provides a biophysical foundation of influenza genome packaging and reassortment and serves as an important step towards robust sequence-driven prediction of reassortment patterns of the influenza virus.

关键词： INFLUENZA A virus GENOMES MOLECULAR interactions RNA-RNA interactions MOLECULAR recognition MONTE Carlo method

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A block-based evolutionary optimization strategy to investigate gene-gene interactions in genetic association studies

A block-based evolutionary optimization strategy to investig...

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IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Joel Fontanarosa Yang Dai Bioinformatics Program Department of Bioengineering University of Illinois Chicago Chicago IL USA

Multi-locus interactions in genetic association studies are believed to influence the heritability of a number of common diseases. In this study, we propose a discrete optimization strategy to improve the power and computational efficiency of multi-locus association analysis. We implemented an adaptive evolutionary algorithm in combination with a linkage disequilibrium-based discretization approach to reduce the need for exhaustive search for combinations by taking advantage of inherent genomic structure. The method was applied to several simulated disease models as well as to a real genome-wide association study. The results indicate that our method performs as well as or better than the most powerful competing methods for detecting true interactions, and it achieves this performance with improved computational efficiency.

关键词： bioinformatics Genomics Computational modeling Couplings Diseases Data models

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Integrating immunoinformatics and computational epitope prediction for a vaccine candidate against respiratory syncytial virus

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Infectious Disease Modelling 2024年第3期9卷 763-774页

作者： Truc Ly Nguyen Heebal Kim Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences Seoul National UniversitySeoul08826Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National UniversitySeoul08826Republic of Korea eGnome Inc.Seoul05836Republic of Korea

Respiratory syncytial virus(RSV)poses a significant global health threat,especially affecting infants and the *** this,the present study proposes an innovative approach to vaccine design,utilizing immunoinformatics and computational *** analyzed RSV's structural proteins across both subtypes A and B,identifying potential helper T lymphocyte,cytotoxic T lymphocyte,and linear B lymphocyte *** such as antigenicity,allergenicity,toxicity,and cytokine-inducing potential were rigorously ***,we evaluated the conservancy of these epitopes and their population coverage across various RSV *** comprehensive analysis identified six major histocompatibility complex class I(MHC-I)binding,five MHC-II binding,and three B-cell *** were integrated with suitable linkers and adjuvants to form the ***,molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors(TLR4 and TLR5),with a notable preference for *** simulation analysis underscored the vaccine's potential to elicit a strong immune *** study presents a promising RSV vaccine candidate and offers theoretical support,marking a significant advancement in vaccine development ***,the promising in silico findings need to be further validated through additional in vivo studies.

关键词： Respiratory syncytial virus Multiepitope vaccine Immunoinformatics Docking molecular Molecular dynamics simulation Immune simulation

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The crystal structure of a replicative hexameric helicase DnaC and its complex with single-stranded DNA

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Nucleic Acids Research 2009年第3期37卷 804-814页

作者： Lo, Yu-Hua Tsai, Kuang-Lei Sun, Yuh-Ju Chen, Wei-Ti Huang, Cheng-Yang Hsiao, Chwan-Deng Institute of Molecular Biology Academia Sinica Taipei 115 Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Hsinchu 300 Taiwan Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan

DNA helicases are motor proteins that play essential roles in DNA replication, repair and recombination. In the replicative hexameric helicase, the fundamental reaction is the unwinding of duplex DNA;however, our understanding of this function remains vague due to insufficient structural information. Here, we report two crystal structures of the DnaB-family replicative helicase from Geobacillus kaustophilus HTA426 (Gk DnaC) in the apo-form and bound to single-stranded DNA (ssDNA). The Gk DnaC-ssDNA complex structure reveals that three symmetrical basic grooves on the interior surface of the hexamer individually encircle ssDNA. The ssDNA-binding pockets in this structure are directed toward the N-terminal domain collar of the hexameric ring, thus orienting the ssDNA toward the DnaG primase to facilitate the synthesis of short RNA primers. These findings provide insight into the mechanism of ssDNA binding and provide a working model to establish a novel mechanism for DNA translocation at the replication fork. © 2008 The Author(s).

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Finding Phylogenetically Informative Genes by Estimating Multispecies Gene Entropy

Finding Phylogenetically Informative Genes by Estimating Mul...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiaoxu Han Department of Mathematics and Bioinformatics Program Eastern Michigan University Ypsilanti MI USA

Although entropy and relative entropy (K-L distance) are widely applied in many bioinformatics areas, there is no method given to compute the multispecies gene entropy yet. This paper presents the first multispecies gene entropy estimation method from the data mining point of view. In this study, a self-organizing map (SOM) is employed to mine a multispecies gene set to obtain the probability distribution of each gene in the feature space, which is the approximation of its corresponding probability distribution in the original sequence space. The multispecies gene entropy is computed by the probability distribution of a gene in the feature space. The phylogenetic applications of the multispecies gene entropy are investigated in an example of resolving incongruence between gene trees and species trees. It is found that genes with nearest K-L distances to the minimum entropy gene are more likely to be phylogenetically informative. A K-L distance based gene concatenation approach under gene clustering is proposed to resolve the gene tree and species tree problem. Under the same testing dataset, the K-L distance based approach not only avoids the ad-hoc mechanism of the original gene concatenation method but also is easy to extend to other dataset and free from prohibitive phylogenetic computing from large number of taxa.

关键词： Entropy Sequences DNA Probability distribution bioinformatics Phylogeny Data mining Distributed computing Testing Information analysis

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Multiscale gene sets from protein interaction networks

Multiscale gene sets from protein interaction networks

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2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013

作者： Yang, Shu Pham, Lisa Christadore, Lisa M. Schaus, Scott Kolaczyk, Eric D. Department of Mathematics and Statistics Boston University Boston MA United States Bioinformatics Program Boston University Boston MA United States Department of Chemistry Boston University Boston MA United States

ISBN: (纸本)9781479902484

Gene sets have been widely used on genome-scale data for various purposes. Ideally, gene sets should have multiple scales that can explain biological processes in different scales and depth, which is often missing from most popular algorithmically defined gene sets. We propose a principled way to generate multiscale gene sets based on protein-protein interaction (PPI) networks and techniques from multiscale harmonic analysis. Specifically, on a yeast PPI network, we adopt the diffusion wavelets tool developed by Coifman and Maggioni and modify it for heavy tail graphs. Then, we define gene sets through a tiling of the PPI network based on the scaling functions. We compare our multiscale gene sets to two standard gene set databases (GO and KEGG) and gene sets derived from a hierarchical clustering method. We find that our gene sets have a large, non-trivial overlap with the standard databases, and yet still have a sizeable non-overlap as well. In addition, the sense of scale from our gene sets also matches well with that from GO. Finally, we use yeast cell cycle experiments to demonstrate the potential usage of our multiscale gene sets. © 2013 IEEE.

关键词： Proteins

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FSMEC: A feature selection method based on the minimum spanning tree and evolutionary computation 13

FSMEC: A feature selection method based on the minimum spann...

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13th Australasian Data Mining Conference, AusDM 2015

作者： Zaher, Amer Abu Berretta, Regina Arefin, Ahmed Shamsul Moscato, Pablo The Priority Research Centre for Bioinformatics The University of Newcastle Biomarker Discovery and Information-based Medicine Information-based Medicine Program Hunter Medical Research Institute School of Electrical Engineering and Computer Science Australia

ISBN: (纸本)9781921770180

In feature selection we aim at reducing the dimensionality of a dataset by excluding characteristics that do not compromise, and potentially enhance, the classification of a set of samples. We present a new type of supervised and multivariate feature selection approach that works by constructing proximity graphs in such a way that the number of edges connecting samples from different classes is minimised. We present this general idea using the Minimum Spanning Tree as a proximity graph and an Evolutionary Algorithm approach is used to search for a feature subset. We compare the performance of our algorithm against other feature selection methods, (alpha,beta)-k-Feature Set, and a ranking-based feature selection method, based on the use of CM1-scores. We employ two publicly available real-world datasets (one with training and test variants). The classification accuracies have been evaluated using a total of 49 methods from an open source data mining and machine learning package WEKA. © 2015, Australian Computer Society, Inc.

关键词： Evolutionary algorithms

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Investigation of RNA-RNA Interactions Using the RISE Database

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Current Protocols in bioinformatics 2018年第1期64卷 e58/1-e58/1页

作者： Ju, Yanyan Gong, Jing Yang, Yucheng T. Zhang, Qiangfeng Cliff MOE Key Laboratory of Bioinformatics Beijing Advanced Innovation Center for Structural Biology Center for Synthetic and Systems Biology Tsinghua-Peking Joint Center for Life Sciences School of Life Sciences Tsinghua University Beijing China Department of Molecular Biophysics and Biochemistry Yale University New Haven CT United States Program in Computational Biology and Bioinformatics Yale University New Haven CT United States

RNA-RNA interactions (RRIs) are essential to understanding the regulatory mechanisms of RNAs. Mapping RRIs in vivo in a transcriptome-wide manner remained challenging until the recent development of several sequencing-based technologies. However, RRIs generated from large-scale studies had not been systematically collected and analyzed before. This article introduces RISE, a database of the RNA Interactome from Sequencing Experiments. RISE provides a comprehensive collection of RRIs in human, mouse, and yeast, derived from transcriptome-wide sequencing experiments, as well as targeted sequencing studies and other public databases/datasets. To facilitate better understanding of the biological roles of these RRIs, RISE also offers rich functional annotations involving RNAs, and an interactive interface to explore the analysis results. Here, we provide a brief description of the RISE website and a step-by-step protocol for using RISE to study RRIs. © 2018 by John Wiley & Sons, Inc. © 2018 John Wiley & Sons, Inc.

关键词： interaction RISE RNA RNA structure RNA-RNA sequencing experiments

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