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A Fine-Grained CUDA Implementation of the Multi-objective Evolutionary Approach NSGA-II: Potential Impact for computational and Systems biology Applications 11th

A Fine-Grained CUDA Implementation of the Multi-objective Ev...

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11th International Meeting on computational intelligence Methods for bioinformatics and Biostatistics (CIBB)

作者： D'Agostino, Daniele Pasquale, Giulia Merelli, Ivan Natl Res Council Italy Inst Appl Math & Informat Technol I-16149 Genoa Italy Natl Res Council Italy Inst Biomed Technol I-20090 Segrate Mi Italy

ISBN: (纸本)9783319244624;9783319244617

Many computational and systems biology challenges, in particular those related to big data analysis, can be formulated as optimization problems and therefore can be addressed using heuristics. Beside the typical optimization problems, formulated with respect to a single target, the possibility of optimizing multiple objectives (MO) is rapidly becoming more appealing. In this context, MO Evolutionary Algorithms (MOEAs) are one of the most widely used classes of methods to solve MO optimization problems. However, these methods can be particularly demanding from the computational point of view and, therefore, effective parallel implementations are needed. This fact, together with the wide diffusion of powerful and low-cost general-purpose Graphics Processing Units, promoted the development of software tools that focus on the parallelization of one or more computational phases among the steps characterizing MOEAs. In this paper we present a fine-grained parallelization of the Fast Non-dominating Sorting Genetic Algorithm (NSGA-II) for the CUDA architecture. In particular, we will discuss how this solution can be exploited to solve multi-objective optimization task in the field of computational and systems biology.

关键词： Graphics Processing Units CUDA-accelerated architecture Multi-objective optimization computational and Systems biology

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Mendel: A Distributed Storage Framework for Similarity Searching over Sequencing Data

Mendel: A Distributed Storage Framework for Similarity Searc...

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International symposium on Parallel and Distributed Processing (IPDPS)

作者： Cameron Tolooee Sangmi Lee Pallickara Asa Ben-Hur Department of Computer Science Colorado State University USA

ISBN: (纸本)9781509021413

Rapid advances in genomic sequencing technology have resulted in a data deluge in biology and bioinformatics. This increase in data volumes has introduced computational challenges for frequently performed sequence analytics routines such as DNA and protein homology searches, these must also preferably be done in real-time. In this paper, we propose a scalable and similarity-aware distributed storage framework, Mendel, that enables retrieval of biologically significant DNA and protein alignments against a voluminous genomic sequence database. Mendel fragments the sequence data and generates an inverted-index, which is then dispersed over a distributed collection of machines using a locality aware distributed hash table. A novel distributed nearest neighbor search algorithm identifies sequence segments with high similarity and extending them to find an alignment. This paper includes an empirical evaluation of the performance, sensitivity, and scalability of the proposed system versus the National Center for Biotechnology Information's non-redundant protein dataset. Mendel demonstrates higher sensitivity and faster query evaluations when compared to other modern frameworks.

关键词： bioinformatics Genomics DNA Distributed databases Proteins Algorithm design and analysis

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Multiple 3D RNA Structure Superposition Using Neighbor Joining

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2015年第3期12卷 520-530页

作者： Hoksza, David Svozil, Daniel Charles Univ Prague Dept Software Engn Prague Czech Republic Inst Chem Technol Lab Informat & Chem CR-16628 Prague Czech Republic

Recent advances in RNA research and the steady growth of available RNA structures call for bioinformatics methods for handling and analyzing RNA structural data. Recently, we introduced SETTER-a fast and accurate method for RNA pairwise structure alignment. In this paper, we describe MultiSETTER, SETTER extension for multiple RNA structure alignment. MultiSETTER combines SETTER's decomposition of RNA structures into non-overlapping structural subunits with the multiple sequence alignment algorithm ClustalW adapted for the structure alignment. The accuracy of MultiSETTER was assessed by the automatic classification of RNA structures and its comparison to SCOR annotations. In addition, MultiSETTER classification was also compared to multiple sequence alignment-based and secondary structure alignment-based classifications provided by LocARNA and RNADistance tools, respectively. MultiSETTER precompiled Windows libraries, as well as the C++ source code, are freely available from http://***/multisetter.

关键词： Structural bioinformatics RNA tertiary structure structural superposition structural similarity

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A Comparison Study of Reverse Engineering Gene Regulatory Network Modeling

A Comparison Study of Reverse Engineering Gene Regulatory Ne...

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ieee symposium on bioinformatics and Bioengineering (BIBE)

作者： Charles C. N. Wang Pei-Chun Chang Phillip C. Y. Sheu Jeffrey J. P. Tsai Department of Biomedical Informatics Asia University Taichung Wufeng Taiwan Department of Electrical Engineering & Computer Science University of California Irvine CA

The construction and understanding of Gene Regulatory Networks (GRNs) are among the hardest tasks faced by systems biology. To infer gene regulatory networks from gene expression data has been a vigorous research area. It aims to constitute an intermediate step from exploratory to gene expression analysis. In recent years, many reverse engineering methods have been proposed. In practice, different model approaches will generate different network structures. Therefore, it is very important for users to assess the performance of these algorithms. We present a comparative study with three different reverse engineering methods, including the S-system Parameter Estimation Method (SPEM), the Graphical Gaussian Model (GGM) and the TimeDelay-ARACNE. Our approach consists of the analysis of real gene expression data with the different methods, and the assessment of algorithmic performances by sensitivity, specificity, precision and F-score.

关键词： Reverse engineering Gene expression Mathematical model computational modeling Sensitivity Biological system modeling Correlation

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The Influence of the Background Model on DNA Motif Prediction: an Assessment for Zinc Finger Transcription Factor ZFX 10

The Influence of the Background Model on DNA Motif Predictio...

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10th Jubilee ieee International symposium on Applied computational intelligence and Informatics

作者： Lihu, Andrei Holban, Stefan Politehn Univ Timisoara Dept Comp Sci Bd Vasile Parvan 2 Timisoara 300223 Romania

ISBN: (纸本)9781479999118

Motif finding is a computationally expensive procedure subject to noise and false positives, but of major importance in understanding gene expression and cancer. Several authors argued in favor of using higher order background models to better discriminate motifs. This paper studies the effect of using Markov higher order models in three commonly used algorithms to identify the ZFX transcription factor's binding sites from a mouse embryonic stem cells dataset. We conclude that there are particular Markov orders that yield improved outcomes for each algorithm.

关键词： Algorithm design and analysis bioinformatics computational modeling DNA Markov processes Predictive models Stem cells

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A Cloud Solution for Multi-omics Data Integration

A Cloud Solution for Multi-omics Data Integration

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Fabio Tordini Computer Science department University of Torino Italy

Recent advances in molecular biology, bioinformatics techniques have brought to an explosion of the information about the spatial organisation of the DNA inside the nucleus. In particular, 3C-based techniques are revealing the genome folding for many different cell types,, permit to create a more effective representation of the disposition of genes in the three-dimensional space. This information can be used to re-interpret heterogeneous genomic data (multi-omic) relying on 3D maps of the chromosome. The storage, computational requirements needed to accomplish such operations on raw sequenced data have to be fulfilled using HPC solutions,, the the Cloud paradigm is a valuable, convenient mean for delivering HPC to bioinformatics. In this work we describe a data analysis work-flow that allows the integration, the interpretation of multi-omic data on a sort of "topographical" nuclear map, capable of representing the effective disposition of genes in a graph-based representation. We propose a cloud-based task farm pattern to orchestrate the services needed to accomplish genomic data analysis, where each service represents a special-purpose tool, playing a part in well known data analysis pipelines.

关键词： bioinformatics Cloud computing Genomics Pipelines Data analysis DNA

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TCBB special section on the Brazilian symposium on bioinformatics 2013

TCBB special section on the Brazilian symposium on bioinform...

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作者： Setubal, João C. Almeida, Nalvo Department of Biochemistry Institute of Chemistry University of Sao Paulo Sao Paulo SP Brazil School of Computing Federal University of Mato Grosso do Sul CP 549 Campo Grande MS Brazil

The latest issue of Transactions On computational biology and bioinformatics (TCBB) contained extended versions of works that were presented at the Brazilian symposium on bioinformatics 2013 (BSB 2013), which was held in Recife, Brazil from November 3-6, 2013. Eighteen papers were presented at BSB 2013 out of which four of these were invited for submission to a special section of TCBB. These four manuscripts were carefully evaluated by 11 international experts. These four papers cover a wide arc of results, ranging from the most theoretical to the practical and emerging as an excellent showcase of the work presented at BSB 2013, including computational biology.

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Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2015年第6期12卷 1365-1373页

作者： Rubiolo, Mariano Milone, Diego H. Stegmayer, Georgina UTN FRSF CIDISI RA-3000 Santa Fe Argentina FICH UNL CONICET Res Inst Signals Syst & Computat Intelligence RA-3000 Santa Fe Argentina

Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

关键词： Gene regulatory networks gene profiles times series data neural networks

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Parameterized BLOSUM Matrices for Protein Alignment

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2015年第3期12卷 686-694页

作者： Song, Dandan Chen, Jiaxing Chen, Guang Li, Ning Li, Jin Fan, Jun Bu, Dongbo Li, Shuai Cheng Beijing Inst Technol Beijing Engn Res Ctr High Volume language Informa Sch Comp Sci & Technol Beijing 100081 Peoples R China Univ Missouri Dept Comp Sci Columbia MO 65211 USA City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China Chinese Acad Sci Inst Comp Technol Key Lab Intelligence Informat Proc Beijing 100190 Peoples R China Univ Wisconsin Dept Stat Madison WI 53706 USA

Protein alignment is a basic step for many molecular biology researches. The BLOSUM matrices, especially BLOSUM62, are the de facto standard matrices for protein alignments. However, after widely utilization of the matrices for 15 years, programming errors were surprisingly found in the initial version of source codes for their generation. And amazingly, after bug correction, the "intended" BLOSUM62 matrix performs consistently worse than the "miscalculated" one. In this paper, we find linear relationships among the eigenvalues of the matrices and propose an algorithm to find optimal unified eigenvectors. With them, we can parameterize matrix BLOSUMx for any given variable x that could change continuously. We compare the effectiveness of our parameterized isentropic matrix with BLOSUM62. Furthermore, an iterative alignment and matrix selection process is proposed to adaptively find the best parameter and globally align two sequences. Experiments are conducted on aligning 13,667 families of Pfam database and on clustering MHC II protein sequences, whose improved accuracy demonstrates the effectiveness of our proposed method.

关键词： Protein alignment substitution matrix parameterized BLOSUM matrices

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Mobile access to on-line analytic bioinformatics tools 3

Mobile access to on-line analytic bioinformatics tools

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

作者： Del Pino, Sergio Díaz Karlsson, Tor Johan Mikael Cano, Juan Falgueras Trelles, Oswaldo Computer Architecture Department Málaga University Louis Pasteur 35 Málaga 29071 Spain Integromics S.L Parque Tecnológico de Ciencias de la Salud Avenida de la Innovación nº 1 Armilla Granada 18100 Spain Computer Sciences Department Malaga University Louis Pasteur 35 Malaga 29071 Spain Spain

ISBN: (纸本)9783319164793

The use of mobile devices grow continuously in many aspects of our everyday lives. It is essential that bioinformatics and biomedicine adapt to this trend because these platforms can provide universal access to computational resources independently of their location. We report the implementation of a light-weight client which allows researchers to launch complex analysis experiments and monitor the progress using their mobile devices. Starting from the analysis of existing functionality in current bioinformatics clients for webservices, we have selected, designed and implemented a complete set of functions for accessing computational resources in bioinformatics and biomedicine through mobile devices. © Springer International Publishing Switzerland 2015.

关键词： Web services

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