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Dive into the research topics where Andreas Prlić is active.

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Featured researches published by Andreas Prlić.


Nucleic Acids Research | 2011

The RCSB Protein Data Bank: redesigned web site and web services

Peter W. Rose; Bojan Beran; Chunxiao Bi; Wolfgang F. Bluhm; Dimitris Dimitropoulos; David S. Goodsell; Andreas Prlić; Martha Quesada; Gregory B. Quinn; John D. Westbrook; Jasmine Young; Benjamin T. Yukich; Christine Zardecki; Helen M. Berman; Philip E. Bourne

The RCSB Protein Data Bank (RCSB PDB) web site (http://www.pdb.org) has been redesigned to increase usability and to cater to a larger and more diverse user base. This article describes key enhancements and new features that fall into the following categories: (i) query and analysis tools for chemical structure searching, query refinement, tabulation and export of query results; (ii) web site customization and new structure alerts; (iii) pair-wise and representative protein structure alignments; (iv) visualization of large assemblies; (v) integration of structural data with the open access literature and binding affinity data; and (vi) web services and web widgets to facilitate integration of PDB data and tools with other resources. These improvements enable a range of new possibilities to analyze and understand structure data. The next generation of the RCSB PDB web site, as described here, provides a rich resource for research and education.


Nucleic Acids Research | 2012

The RCSB Protein Data Bank: new resources for research and education

Peter W. Rose; Chunxiao Bi; Wolfgang F. Bluhm; Cole Christie; Dimitris Dimitropoulos; Shuchismita Dutta; Rachel Kramer Green; David S. Goodsell; Andreas Prlić; Martha Quesada; Gregory B. Quinn; Alexander G. Ramos; John D. Westbrook; Jasmine Young; Christine Zardecki; Helen M. Berman; Philip E. Bourne

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) develops tools and resources that provide a structural view of biology for research and education. The RCSB PDB web site (http://www.rcsb.org) uses the curated 3D macromolecular data contained in the PDB archive to offer unique methods to access, report and visualize data. Recent activities have focused on improving methods for simple and complex searches of PDB data, creating specialized access to chemical component data and providing domain-based structural alignments. New educational resources are offered at the PDB-101 educational view of the main web site such as Author Profiles that display a researcher’s PDB entries in a timeline. To promote different kinds of access to the RCSB PDB, Web Services have been expanded, and an RCSB PDB Mobile application for the iPhone/iPad has been released. These improvements enable new opportunities for analyzing and understanding structure data.


Bioinformatics | 2008

BioJava: an open-source framework for bioinformatics

Richard C. G. Holland; Thomas A. Down; Matthew R. Pocock; Andreas Prlić; David Huen; Keith James; Sylvain Foisy; Andreas Dräger; Andy Yates; Michael Heuer; Mark Schreiber

Summary: BioJava is a mature open-source project that provides a framework for processing of biological data. BioJava contains powerful analysis and statistical routines, tools for parsing common file formats and packages for manipulating sequences and 3D structures. It enables rapid bioinformatics application development in the Java programming language. Availability: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.5 or higher. Contact: [email protected]. All queries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists.


Nucleic Acids Research | 2015

The RCSB Protein Data Bank: views of structural biology for basic and applied research and education.

Peter W. Rose; Andreas Prlić; Chunxiao Bi; Wolfgang F. Bluhm; Cole Christie; Shuchismita Dutta; Rachel Kramer Green; David S. Goodsell; John D. Westbrook; Jesse Woo; Jasmine Young; Christine Zardecki; Helen M. Berman; Philip E. Bourne; Stephen K. Burley

The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine.


Bioinformatics | 2010

Pre-calculated protein structure alignments at the RCSB PDB website

Andreas Prlić; Spencer E Bliven; Peter W. Rose; Wolfgang F. Bluhm; Chris Bizon; Adam Godzik; Philip E. Bourne

Summary: With the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user. Availability and Implementation: A web user interface is available at http://www.rcsb.org/pdb/workbench/workbench.do. The source code is available under the LGPL license from http://www.biojava.org. A source bundle, prepared for local execution, is available from http://source.rcsb.org Contact: [email protected]; [email protected]


Bioinformatics | 2012

BioJava: an open-source framework for bioinformatics in 2012

Andreas Prlić; Andrew Yates; Spencer Bliven; Peter W. Rose; Julius Jacobsen; Peter V. Troshin; Mark Chapman; Jianjiong Gao; Chuan Hock Koh; Sylvain Foisy; Richard C. G. Holland; Gediminas Rimsa; Michael Heuer; Hannes Brandstätter-Müller; Philip E. Bourne; Scooter Willis

Motivation: BioJava is an open-source project for processing of biological data in the Java programming language. We have recently released a new version (3.0.5), which is a major update to the code base that greatly extends its functionality. Results: BioJava now consists of several independent modules that provide state-of-the-art tools for protein structure comparison, pairwise and multiple sequence alignments, working with DNA and protein sequences, analysis of amino acid properties, detection of protein modifications and prediction of disordered regions in proteins as well as parsers for common file formats using a biologically meaningful data model. Availability: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.6 or higher. All inquiries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists Contact: [email protected]


Nucleic Acids Research | 2017

The RCSB protein data bank: integrative view of protein, gene and 3D structural information

Peter W. Rose; Andreas Prlić; Ali Altunkaya; Chunxiao Bi; Anthony R. Bradley; Cole Christie; Luigi Di Costanzo; Jose M. Duarte; Shuchismita Dutta; Zukang Feng; Rachel Kramer Green; David S. Goodsell; Brian P. Hudson; Tara Kalro; Robert Lowe; Ezra Peisach; Christopher Randle; Alexander S. Rose; Chenghua Shao; Yi-Ping Tao; Yana Valasatava; Maria Voigt; John D. Westbrook; Jesse Woo; Huangwang Yang; Jasmine Young; Christine Zardecki; Helen M. Berman; Stephen K. Burley

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a ‘Structural View of Biology.’ Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive.


BMC Bioinformatics | 2008

Integrating biological data – the Distributed Annotation System

Andrew M. Jenkinson; Mario Albrecht; Ewan Birney; Hagen Blankenburg; Thomas A. Down; Robert D. Finn; Henning Hermjakob; Tim Hubbard; Rafael C. Jimenez; Philip Jones; Andreas Kähäri; Eugene Kulesha; José R. Macías; Gabrielle A. Reeves; Andreas Prlić

BackgroundThe Distributed Annotation System (DAS) is a widely adopted protocol for dynamically integrating a wide range of biological data from geographically diverse sources. DAS continues to expand its applicability and evolve in response to new challenges facing integrative bioinformatics.ResultsHere we describe the various infrastructure components of DAS and present a new extended version of the DAS specification. Version 1.53E incorporates several recent developments, including its extension to serve new data types and an ontology for protein features.ConclusionOur extensions to the DAS protocol have facilitated the integration of new data types, and our improvements to the existing DAS infrastructure have addressed recent challenges. The steadily increasing numbers of available data sources demonstrates further adoption of the DAS protocol.


BMC Bioinformatics | 2007

Integrating sequence and structural biology with DAS

Andreas Prlić; Thomas A. Down; Eugene Kulesha; Robert D. Finn; Andreas Kähäri; Tim Hubbard

BackgroundThe Distributed Annotation System (DAS) is a network protocol for exchanging biological data. It is frequently used to share annotations of genomes and protein sequence.ResultsHere we present several extensions to the current DAS 1.5 protocol. These provide new commands to share alignments, three dimensional molecular structure data, add the possibility for registration and discovery of DAS servers, and provide a convention how to provide different types of data plots. We present examples of web sites and applications that use the new extensions. We operate a public registry of DAS sources, which now includes entries for more than 250 distinct sources.ConclusionOur DAS extensions are essential for the management of the growing number of services and exchange of diverse biological data sets. In addition the extensions allow new types of applications to be developed and scientific questions to be addressed. The registry of DAS sources is available at http://www.dasregistry.org


Proteins | 2001

Assessment of the CASP4 fold recognition category

Manfred J. Sippl; Peter Lackner; Francisco S. Domingues; Andreas Prlić; Rainer Malik; Antonina Andreeva; Markus Wiederstein

We present the assessment of the CASP4 fold recognition category. The tasks we had to execute include the splitting of multidomain targets into single domains, the classification of target domains in terms of prediction categories, the numerical evaluation of predictions, the mapping of numerical scores to quality indices, the ranking of predictors, the selection of top‐performing groups, and the analysis and critical discussion of the state of the art in this field. The 125 fold recognition groups were assessed by a total score that summarizes their performance over all targets and a quality score reflecting the average quality of the submitted models. Most of the top‐performing groups achieved respectable results on both scores simultaneously. Several groups submitted models that were much closer to the respective target structures than any of the known folds in the Protein Data Bank. The CASP4 assessment included the automated servers of the parallel CAFASP experiment. For the total score, the highest rank achieved by a fully automated server is 12. Two thirds of the predictors have rather low scores. Proteins 2001;Suppl 5:55–67.

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Peter W. Rose

University of California

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Philip E. Bourne

National Institutes of Health

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Jose M. Duarte

University of California

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Chunxiao Bi

University of California

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Anthony R. Bradley

San Diego Supercomputer Center

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