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Database resources of the National Center for Biotechnology Information

by David L. Wheeler, Tanya Barrett, Dennis A. Benson, Stephen H. Bryant, Kathi Canese, Vyacheslav Chetvernin, Deanna M. Church, Michael Dicuccio, Ron Edgar, Scott Federhen, Lewis Y. Geer, Yuri Kapustin, Oleg Khovayko, David L, David J. Lipman, Thomas L. Madden, Donna R. Maglott, James Ostell, Vadim Miller, Kim D. Pruitt, Gregory D. Schuler, Edwin Sequeira, Steven T. Sherry, Karl Sirotkin, Re Souvorov, Grigory Starchenko, Roman L. Tatusov, Tatiana A. Tatusova, Lukas Wagner, Eugene Yaschenko - Nucleic Acids Res , 2008
"... In addition to maintaining the GenBankÒ nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s Web site. NCBI resources include Entrez, ..."
Abstract - Cited by 979 (15 self) - Add to MetaCart
In addition to maintaining the GenBankÒ nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s Web site. NCBI resources include Entrez,

The Protein Data Bank

by Helen M. Berman, John Westbrook, Zukang Feng, Gary Gilliland, T. N. Bhat, Helge Weissig, Ilya N. Shindyalov, Philip E. Bourne - Nucleic Acids Res , 2000
"... The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the futur ..."
Abstract - Cited by 1387 (24 self) - Add to MetaCart
for the future development of the resource. INTRODUCTION The Protein Data Bank (PDB) was established at Brookhaven National Laboratories (BNL) (1) in 1971 as an archive for biological macromolecular crystal structures. In the beginning the archive held seven structures, and with each year a handful more were

RSVP: A New Resource Reservation Protocol

by Lixia Zhang, Stephen Deering, Deborah Estrin, Scott Shenker, et al. , 1993
"... Whe origin of the RSVP protocol can be traced back to 1991, when a team of network researchers, including myself, started playing with a number of packet scheduling algorithms on the DARTNET (DARPA Testbed NETwork), a network testbed made of open source, workstation-based routers. Because scheduling ..."
Abstract - Cited by 1005 (25 self) - Add to MetaCart
scheduling algorithms simply shuffle packet processing orders according to some established rates or priorities for different data flows, to test a scheduling algorithm requires setting up the appropriate control state at each router along the data flow paths. I was challenged to design a set-up protocol

MapReduce: Simplified data processing on large clusters.

by Jeffrey Dean , Sanjay Ghemawat - In Proceedings of the Sixth Symposium on Operating System Design and Implementation (OSDI-04), , 2004
"... Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of ..."
Abstract - Cited by 3439 (3 self) - Add to MetaCart
of partitioning the input data, scheduling the program's execution across a set of machines, handling machine failures, and managing the required inter-machine communication. This allows programmers without any experience with parallel and distributed systems to easily utilize the resources of a large

BIRCH: an efficient data clustering method for very large databases

by Tian Zhang, Raghu Ramakrishnan, Miron Livny - In Proc. of the ACM SIGMOD Intl. Conference on Management of Data (SIGMOD , 1996
"... Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely st,udied problems in this area is the identification of clusters, or deusel y populated regions, in a multi-dir nensional clataset. Prior work does not adequately address the problem of ..."
Abstract - Cited by 576 (2 self) - Add to MetaCart
multi-dimensional metric data points to try to produce the best quality clustering with the available resources (i. e., available memory and time constraints). BIRCH can typically find a goocl clustering with a single scan of the data, and improve the quality further with a few aclditioual scans. BIRCH

Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks

by Michael Isard, Mihai Budiu, Yuan Yu, Andrew Birrell, Dennis Fetterly - In EuroSys , 2007
"... Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad applica-tion combines computational “vertices ” with communica-tion “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of availa ..."
Abstract - Cited by 762 (27 self) - Add to MetaCart
simultaneously on multi-ple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at run time, and modify the graph as the computation pro-gresses to make efficient use of the available resources. Dryad is designed to scale from powerful multi-core sin

Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing

by Edward Ashford Lee, David G. Messerschmitt - IEEE TRANSACTIONS ON COMPUTERS , 1987
"... Large grain data flow (LGDF) programming is natural and convenient for describing digital signal processing (DSP) systems, but its runtime overhead is costly in real time or cost-sensitive applications. In some situations, designers are not willing to squander computing resources for the sake of pro ..."
Abstract - Cited by 598 (37 self) - Add to MetaCart
Large grain data flow (LGDF) programming is natural and convenient for describing digital signal processing (DSP) systems, but its runtime overhead is costly in real time or cost-sensitive applications. In some situations, designers are not willing to squander computing resources for the sake

Mediators in the architecture of future information systems

by Gio Wiederhold - IEEE COMPUTER , 1992
"... The installation of high-speed networks using optical fiber and high bandwidth messsage forwarding gateways is changing the physical capabilities of information systems. These capabilities must be complemented with corresponding software systems advances to obtain a real benefit. Without smart softw ..."
Abstract - Cited by 1135 (20 self) - Add to MetaCart
-level functional partitioning. These partitions are mapped into information process-ing modules. The modules are assigned to nodes of the distributed information systems. A central role is assigned to modules that mediate between the users ' workstations and data re-sources. Mediators contain

A Security Architecture for Computational Grids

by Ian Foster , Carl Kesselman, Gene Tsudik, Steven Tuecke , 1998
"... State-of-the-art and emerging scientific applications require fast access to large quantities of data and commensurately fast computational resources. Both resources and data are often distributed in a wide-area network with components administered locally and independently. Computations may involve ..."
Abstract - Cited by 568 (47 self) - Add to MetaCart
State-of-the-art and emerging scientific applications require fast access to large quantities of data and commensurately fast computational resources. Both resources and data are often distributed in a wide-area network with components administered locally and independently. Computations may

The Data Grid: Towards an Architecture for the Distributed Management and Analysis of Large Scientific Datasets

by Ann Chervenak , Ian Foster, Carl Kesselman, Charles Salisbury, Steven Tuecke - JOURNAL OF NETWORK AND COMPUTER APPLICATIONS , 1999
"... In an increasing number of scientific disciplines, large data collections are emerging as important community resources. In this paper, we introduce design principles for a data management architecture called the Data Grid. We describe two basic services that we believe are fundamental to the des ..."
Abstract - Cited by 471 (41 self) - Add to MetaCart
In an increasing number of scientific disciplines, large data collections are emerging as important community resources. In this paper, we introduce design principles for a data management architecture called the Data Grid. We describe two basic services that we believe are fundamental
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