The Experts below are selected from a list of 113796 Experts worldwide ranked by ideXlab platform

Christophe Klopp - One of the best experts on this subject based on the ideXlab platform.

  • Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies
    PeerJ, 2017
    Co-Authors: Cédric Cabau, Frédéric Escudie, Anis Djari, Yann Guiguen, Julien Bobe, Christophe Klopp
    Abstract:

    Background - Results - We built a RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1.3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Conclusion - Transcriptome assembly is a challenging Computational Task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The RNA-Seq Assembly Pipeline (DRAP) is an easy to use software package to produce compact and corrected transcript set. DRAP is free, open-source and available under GPL V3 license at http://www.sigenae.org/drap.

  • DRAP: de novo RNA-Seq Assembly Pipeline
    2017
    Co-Authors: Cédric Cabau, Frédéric Escudie, Anis Djari, Yann Guiguen, Julien Bobe, Christophe Klopp
    Abstract:

    Trinity and Oases are two commonly used de novo transcriptome assemblers. The contig sets they produce are of good quality. Still, their compaction (number of contigs needed to represent the transcriptome) and their quality (chimera and nucleotide error rates) can be improved. We built a de novo RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1.3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Transcriptome assembly is a challenging Computational Task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The de novo RNA-Seq Assembly Pipeline (DRAP) is an easy to use software package to produce compact and corrected transcript set.

Cédric Cabau - One of the best experts on this subject based on the ideXlab platform.

  • Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies
    PeerJ, 2017
    Co-Authors: Cédric Cabau, Frédéric Escudie, Anis Djari, Yann Guiguen, Julien Bobe, Christophe Klopp
    Abstract:

    Background - Results - We built a RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1.3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Conclusion - Transcriptome assembly is a challenging Computational Task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The RNA-Seq Assembly Pipeline (DRAP) is an easy to use software package to produce compact and corrected transcript set. DRAP is free, open-source and available under GPL V3 license at http://www.sigenae.org/drap.

  • DRAP: de novo RNA-Seq Assembly Pipeline
    2017
    Co-Authors: Cédric Cabau, Frédéric Escudie, Anis Djari, Yann Guiguen, Julien Bobe, Christophe Klopp
    Abstract:

    Trinity and Oases are two commonly used de novo transcriptome assemblers. The contig sets they produce are of good quality. Still, their compaction (number of contigs needed to represent the transcriptome) and their quality (chimera and nucleotide error rates) can be improved. We built a de novo RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1.3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Transcriptome assembly is a challenging Computational Task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The de novo RNA-Seq Assembly Pipeline (DRAP) is an easy to use software package to produce compact and corrected transcript set.

Andreas M. Köster - One of the best experts on this subject based on the ideXlab platform.

  • Efficient calculation of nuclear spin-rotation constants from auxiliary density functional theory
    Journal of Chemical Physics, 2015
    Co-Authors: Bernardo Zuniga-gutierrez, Monica Camacho-gonzalez, Alfonso Bendana-castillo, Patricia Simon-bastida, Patrizia Calaminici, Andreas M. Köster
    Abstract:

    The computation of the spin-rotation tensor within the framework of auxiliary density functional theory (ADFT) in combination with the gauge including atomic orbital (GIAO) scheme, to treat the gauge origin problem, is presented. For the spin-rotation tensor, the calculation of the magnetic shielding tensor represents the most demanding Computational Task. Employing the ADFT-GIAO methodology, the central processing unit time for the magnetic shielding tensor calculation can be dramatically reduced. In this work, the quality of spin-rotation constants obtained with the ADFT-GIAO methodology is compared with available experimental data as well as with other theoretical results at the Hartree-Fock and coupled-cluster level of theory. It is found that the agreement between the ADFT-GIAO results and the experiment is good and very similar to the ones obtained by the coupled-cluster single-doubles-perturbative triples-GIAO methodology. With the improved Computational performance achieved, the computation of the...

  • efficient calculation of the rotational g tensor from auxiliary density functional theory
    Journal of Physical Chemistry A, 2015
    Co-Authors: Bernardo Zunigagutierrez, Monica Camachogonzalez, Patricia Simonbastida, Alfonso Bendanacastillo, Patrizia Calaminici, Andreas M. Köster
    Abstract:

    : The computation of the rotational g tensor with the recently developed auxiliary density functional theory (ADFT) gauge including atomic orbital (GIAO) methodology is presented. For the rotational g tensor, the calculation of the magnetizability tensor represents the most demanding Computational Task. With the ADFT-GIAO methodology, the CPU time for the magnetizability tensor calculation can be dramatically reduced. Therefore, it seems most desirable to employ the ADFT-GIAO methodology also for the computation of the rotational g tensor. In this work, the quality of rotational g tensors obtained with the ADFT-GIAO methodology is compared with available experimental data as well as with other theoretical results at the Hartree-Fock and coupled-cluster level of theory. It is found that the agreement between the ADFT-GIAO results and the experiment is good. Furthermore, we also show that the ADFT-GIAO g tensor calculation is applicable to large systems like carbon nanotube models containing hundreds of atom and thousands of basis functions.

Christophe Sabourin - One of the best experts on this subject based on the ideXlab platform.

  • A Pseudo-3D Vision-Based Dual Approach for Machine-Awareness in Indoor Environment Combining Multi-resolution Visual Information
    Advances in Computational Intelligence, 2017
    Co-Authors: Hossam Fraihat, Kurosh Madani, Christophe Sabourin
    Abstract:

    In this paper we describe a pseudo-3D vision-based dual approach for Machine-Awareness in indoor environment. The so-called duality is provided by color and depth cameras of Kinect system, which presents an appealing potential for 3D robots vision. Placing the human-machine (including human-robot) interaction as a primary outcome of the intended visual Machine-Awareness in investigated system, we aspire proffering the machine the autonomy in awareness about its surrounding environment. Combining pseudo-3D vision, and salient objects’ detection algorithms, the investigated approach seeks an autonomous detection of relevant items in 3D environment. The pseudo-3D perception allows reducing Computational complexity inherent to the 3D vision context into a 2D Computational Task by processing 3D visual information within a 2D-images’ framework. The statistical foundation of the investigated approach proffers it a solid and comprehensive theoretical basis, holding out a bottom-up nature making the issued system unconstrained regarding prior hypothesis. We provide experimental results validating the proposed system.

  • Machine-awareness in indoor environment: A pseudo-3D vision-based approach combining multi-resolution visual information
    2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2017
    Co-Authors: Kurosh Madani, Hossam Fraihat, Christophe Sabourin
    Abstract:

    The present paper describes a dual approach using pseudo-3D vision for Machine-Awareness in indoor environment. Provided by color and depth cameras of the a Kinect system, the aforementioned duality presents an appealing solution for robots' 3D-vision. Placing the human-robot and in a more general way the human-machine interactions as a key outcome of the expected visual Machine-Awareness, the proposed vision-system aims proffering the machine the self-reliance in awareness about the surrounding environment in which the machine is supposed to evolve. Blend pseudo-3D vision and salient objects' detection algorithm, the investigated approach seeks an autonomous detection of relevant items in 3D environment. The pseudo-3D perception leads to reducing Computational complexity inborn to the 3D vision context into a 2D Computational Task by processing 3D visual information within a 2D-images' framework. The statistical foundation of the investigated approach proffers it a solid and comprehensive theoretical basis, holding out a bottom-up nature making the issued system unconstrained regarding prior hypothesis. We provide experimental results validating the proposed system.

Ashley Montanaro - One of the best experts on this subject based on the ideXlab platform.

  • Quantum Computational supremacy
    Nature, 2017
    Co-Authors: Aram W. Harrow, Ashley Montanaro
    Abstract:

    The field of quantum algorithms aims to find ways to speed up the solution of Computational problems by using a quantum computer. A key milestone in this field will be when a universal quantum computer performs a Computational Task that is beyond the capability of any classical computer, an event known as quantum supremacy. This would be easier to achieve experimentally than full-scale quantum computing, but involves new theoretical challenges. Here we present the leading proposals to achieve quantum supremacy, and discuss how we can reliably compare the power of a classical computer to the power of a quantum computer. Proposals for demonstrating quantum supremacy, when a quantum computer supersedes any possible classical computer at a specific Task, are reviewed.