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1.  rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids 
PLoS Computational Biology  2014;10(4):e1003571.
Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/
doi:10.1371/journal.pcbi.1003571
PMCID: PMC3983074  PMID: 24722481
2.  HLA Typing from 1000 Genomes Whole Genome and Whole Exome Illumina Data 
PLoS ONE  2013;8(11):e78410.
Specific HLA genotypes are known to be linked to either resistance or susceptibility to certain diseases or sensitivity to certain drugs. In addition, high accuracy HLA typing is crucial for organ and bone marrow transplantation. The most widespread high resolution HLA typing method used to date is Sanger sequencing based typing (SBT), and next generation sequencing (NGS) based HLA typing is just starting to be adopted as a higher throughput, lower cost alternative. By HLA typing the HapMap subset of the public 1000 Genomes paired Illumina data, we demonstrate that HLA-A, B and C typing is possible from exome sequencing samples with higher than 90% accuracy. The older 1000 Genomes whole genome sequencing read sets are less reliable and generally unsuitable for the purpose of HLA typing. We also propose using coverage % (the extent of exons covered) as a quality check (QC) measure to increase reliability.
doi:10.1371/journal.pone.0078410
PMCID: PMC3819389  PMID: 24223151
3.  Petabyte-scale innovations at the European Nucleotide Archive 
Nucleic Acids Research  2008;37(Database issue):D19-D25.
Dramatic increases in the throughput of nucleotide sequencing machines, and the promise of ever greater performance, have thrust bioinformatics into the era of petabyte-scale data sets. Sequence repositories, which provide the feed for these data sets into the worldwide computational infrastructure, are challenged by the impact of these data volumes. The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/embl), comprising the EMBL Nucleotide Sequence Database and the Ensembl Trace Archive, has identified challenges in the storage, movement, analysis, interpretation and visualization of petabyte-scale data sets. We present here our new repository for next generation sequence data, a brief summary of contents of the ENA and provide details of major developments to submission pipelines, high-throughput rule-based validation infrastructure and data integration approaches.
doi:10.1093/nar/gkn765
PMCID: PMC2686451  PMID: 18978013

Results 1-3 (3)