The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Kristin A Persson - One of the best experts on this subject based on the ideXlab platform.
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The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles
Computational Materials Science, 2015Co-Authors: Shyue Ping Ong, Miriam Brafman, Shreyas Cholia, Dan Gunter, Anubhav Jain, Gerbrand Ceder, Kristin A PerssonAbstract:In this paper, we describe the Materials Application Programming Interface (API), a simple, flexible and efficient interface to programmatically query and interact with the Materials Project database based on the REpresentational State Transfer (REST) pattern for the web. Since its creation in Aug 2012, the Materials API has been the Materials Project's de facto platform for data access, supporting not only the Materials Project's many collaborative efforts but also enabling new Applications and analyses. We will highlight some of these analyses enabled by the Materials API, particularly those requiring consolidation of data on a large number of materials, such as data mining of structural and property trends, and generation of phase diagrams. We will conclude with a discussion of the role of the API in building a community that is developing novel Applications and analyses based on Materials Project data.
Michael P. Cummings - One of the best experts on this subject based on the ideXlab platform.
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beagle an Application Programming interface and high performance computing library for statistical phylogenetics
Systematic Biology, 2012Co-Authors: Daniel L Ayres, Mark T Holder, David L Swofford, Derrick J Zwickl, Paul O. Lewis, Fredrik Ronquist, Aaron E Darling, John P. Huelsenbeck, Peter Beerli, Michael P. CummingsAbstract:Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an Application Programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.
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beagle an Application Programming interface and high performance computing library for statistical phylogenetics
Systematic Biology, 2012Co-Authors: Daniel L Ayres, Mark T Holder, David L Swofford, Derrick J Zwickl, Paul O. Lewis, Fredrik Ronquist, Aaron E Darling, John P. Huelsenbeck, Peter Beerli, Michael P. CummingsAbstract:Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emer- gence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a com- mon library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an Application Programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently ex- ploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software. (Bayesian phylogenetics; GPU; maximum likelihood; parallel computing.)
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grid services base library a high level procedural Application Programming interface for writing globus based grid services
Future Generation Computer Systems, 2007Co-Authors: Adam L. Bazinet, John Fuetsch, Daniel S. Myers, Michael P. CummingsAbstract:The Grid Services Base Library (GSBL) is a procedural Application Programming interface (API) that abstracts many of the high-level functions performed by Globus Grid services, thus dramatically lowering the barriers to writing Grid services. The library has been extensively tested and used for computational biology research in a Globus Toolkit-based Grid system, in which no fewer than twenty Grid services written with this API are deployed.
Vedrin Jeliazkov - One of the best experts on this subject based on the ideXlab platform.
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ambit restful web services an implementation of the opentox Application Programming interface
Journal of Cheminformatics, 2011Co-Authors: Nina Jeliazkova, Vedrin JeliazkovAbstract:The AMBIT web services package is one of the several existing independent implementations of the OpenTox Application Programming Interface and is built according to the principles of the Representational State Transfer (REST) architecture. The Open Source Predictive Toxicology Framework, developed by the partners in the EC FP7 OpenTox project, aims at providing a unified access to toxicity data and predictive models, as well as validation procedures. This is achieved by i) an information model, based on a common OWL-DL ontology ii) links to related ontologies; iii) data and algorithms, available through a standardized REST web services interface, where every compound, data set or predictive method has a unique web address, used to retrieve its Resource Description Framework (RDF) representation, or initiate the associated calculations.
Shyue Ping Ong - One of the best experts on this subject based on the ideXlab platform.
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The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles
Computational Materials Science, 2015Co-Authors: Shyue Ping Ong, Miriam Brafman, Shreyas Cholia, Dan Gunter, Anubhav Jain, Gerbrand Ceder, Kristin A PerssonAbstract:In this paper, we describe the Materials Application Programming Interface (API), a simple, flexible and efficient interface to programmatically query and interact with the Materials Project database based on the REpresentational State Transfer (REST) pattern for the web. Since its creation in Aug 2012, the Materials API has been the Materials Project's de facto platform for data access, supporting not only the Materials Project's many collaborative efforts but also enabling new Applications and analyses. We will highlight some of these analyses enabled by the Materials API, particularly those requiring consolidation of data on a large number of materials, such as data mining of structural and property trends, and generation of phase diagrams. We will conclude with a discussion of the role of the API in building a community that is developing novel Applications and analyses based on Materials Project data.
Nina Jeliazkova - One of the best experts on this subject based on the ideXlab platform.
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computational toxicology using the opentox Application Programming interface and bioclipse
BMC Research Notes, 2011Co-Authors: Nina Jeliazkova, Barry Hardy, Roland C Grafstrom, Egon Willighagen, Ola SpjuthAbstract:Background: Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology Applications. Findings: This article describes progress in extending the integrative bio- and cheminformatics platform Bioclipse to interoperate with OpenTox, a semantic web framework which supports open data exchange and toxicology model building. The Bioclipse workbench environment enables functionality from OpenTox web services and easy access to OpenTox resources for evaluating toxicity properties of query molecules. Relevant cases and interfaces based on ten neurotoxins are described to demonstrate the capabilities provided to the user. The integration takes advantage of semantic web technologies, thereby providing an open and simplifying communication standard. Additionally, the use of ontologies ensures proper interoperation and reliable integration of toxicity information from both experimental and computational sources. Conclusions: A novel computational toxicity assessment platform was generated from integration of two open science platforms related to toxicology: Bioclipse, that combines a rich scriptable and graphical workbench environment for integration of diverse sets of information sources, and OpenTox, a platform for interoperable toxicology data and computational services. The combination provides improved reliability and operability for handling large data sets by the use of the Open Standards from the OpenTox Application Programming Interface. This enables simultaneous access to a variety of distributed predictive toxicology databases, and algorithm and model resources, taking advantage of the Bioclipse workbench handling the technical layers.
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ambit restful web services an implementation of the opentox Application Programming interface
Journal of Cheminformatics, 2011Co-Authors: Nina Jeliazkova, Vedrin JeliazkovAbstract:The AMBIT web services package is one of the several existing independent implementations of the OpenTox Application Programming Interface and is built according to the principles of the Representational State Transfer (REST) architecture. The Open Source Predictive Toxicology Framework, developed by the partners in the EC FP7 OpenTox project, aims at providing a unified access to toxicity data and predictive models, as well as validation procedures. This is achieved by i) an information model, based on a common OWL-DL ontology ii) links to related ontologies; iii) data and algorithms, available through a standardized REST web services interface, where every compound, data set or predictive method has a unique web address, used to retrieve its Resource Description Framework (RDF) representation, or initiate the associated calculations.
