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Author

Philip F. LoCascio

Other affiliations: University of Tennessee
Bio: Philip F. LoCascio is an academic researcher from Oak Ridge National Laboratory. The author has contributed to research in topics: Protein structure prediction & Massively parallel. The author has an hindex of 8, co-authored 13 publications receiving 9466 citations. Previous affiliations of Philip F. LoCascio include University of Tennessee.

Papers
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Journal ArticleDOI
TL;DR: This work developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm), which achieved good results compared to existing methods, and it is believed it will be a valuable asset to automated microbial annotation pipelines.
Abstract: The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals. With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives. We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/ . Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.

7,157 citations

Journal ArticleDOI
Gerald A. Tuskan1, Gerald A. Tuskan2, Stephen P. DiFazio1, Stephen P. DiFazio3, Stefan Jansson4, Joerg Bohlmann5, Igor V. Grigoriev6, Uffe Hellsten6, Nicholas H. Putnam6, Steven G. Ralph5, Stephane Rombauts7, Asaf Salamov6, Jacquie Schein, Lieven Sterck7, Andrea Aerts6, Rishikeshi Bhalerao4, Rishikesh P. Bhalerao8, Damien Blaudez9, Wout Boerjan7, Annick Brun9, Amy M. Brunner10, Victor Busov11, Malcolm M. Campbell12, John E. Carlson13, Michel Chalot9, Jarrod Chapman6, G.-L. Chen1, Dawn Cooper5, Pedro M. Coutinho14, Jérémy Couturier9, Sarah F. Covert15, Quentin C. B. Cronk5, R. Cunningham1, John M. Davis16, Sven Degroeve7, Annabelle Déjardin9, Claude W. dePamphilis13, John C. Detter6, Bill Dirks17, Inna Dubchak6, Inna Dubchak18, Sébastien Duplessis9, Jürgen Ehlting5, Brian E. Ellis5, Karla C Gendler19, David Goodstein6, Michael Gribskov20, Jane Grimwood21, Andrew Groover22, Lee E. Gunter1, Björn Hamberger5, Berthold Heinze, Yrjö Helariutta23, Yrjö Helariutta8, Yrjö Helariutta24, Bernard Henrissat14, D. Holligan15, Robert A. Holt, Wenyu Huang6, N. Islam-Faridi22, Steven J.M. Jones, M. Jones-Rhoades25, Richard A. Jorgensen19, Chandrashekhar P. Joshi11, Jaakko Kangasjärvi24, Jan Karlsson4, Colin T. Kelleher5, Robert Kirkpatrick, Matias Kirst16, Annegret Kohler9, Udaya C. Kalluri1, Frank W. Larimer1, Jim Leebens-Mack15, Jean-Charles Leplé9, Philip F. LoCascio1, Y. Lou6, Susan Lucas6, Francis Martin9, Barbara Montanini9, Carolyn A. Napoli19, David R. Nelson26, C D Nelson22, Kaisa Nieminen24, Ove Nilsson8, V. Pereda9, Gary F. Peter16, Ryan N. Philippe5, Gilles Pilate9, Alexander Poliakov18, J. Razumovskaya1, Paul G. Richardson6, Cécile Rinaldi9, Kermit Ritland5, Pierre Rouzé7, D. Ryaboy18, Jeremy Schmutz21, J. Schrader27, Bo Segerman4, H. Shin, Asim Siddiqui, Fredrik Sterky, Astrid Terry6, Chung-Jui Tsai11, Edward C. Uberbacher1, Per Unneberg, Jorma Vahala24, Kerr Wall13, Susan R. Wessler15, Guojun Yang15, T. Yin1, Carl J. Douglas5, Marco A. Marra, Göran Sandberg8, Y. Van de Peer7, Daniel S. Rokhsar6, Daniel S. Rokhsar17 
15 Sep 2006-Science
TL;DR: The draft genome of the black cottonwood tree, Populus trichocarpa, has been reported in this paper, with more than 45,000 putative protein-coding genes identified.
Abstract: We report the draft genome of the black cottonwood tree, Populus trichocarpa. Integration of shotgun sequence assembly with genetic mapping enabled chromosome-scale reconstruction of the genome. More than 45,000 putative protein-coding genes were identified. Analysis of the assembled genome revealed a whole-genome duplication event; about 8000 pairs of duplicated genes from that event survived in the Populus genome. A second, older duplication event is indistinguishably coincident with the divergence of the Populus and Arabidopsis lineages. Nucleotide substitution, tandem gene duplication, and gross chromosomal rearrangement appear to proceed substantially more slowly in Populus than in Arabidopsis. Populus has more protein-coding genes than Arabidopsis, ranging on average from 1.4 to 1.6 putative Populus homologs for each Arabidopsis gene. However, the relative frequency of protein domains in the two genomes is similar. Overrepresented exceptions in Populus include genes associated with lignocellulosic wall biosynthesis, meristem development, disease resistance, and metabolite transport.

4,025 citations

Journal ArticleDOI
TL;DR: MetaProdigal is presented, a metagenomic version of the gene prediction program Prodigal that can identify genes in short, anonymous coding sequences with a high degree of accuracy and can identify sequences that use alternate genetic codes and confidence values for each gene call.
Abstract: Motivation: Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. Results: We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translation initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements. Availability: The Prodigal software is freely available under the General Public License from http://code.google.com/p/prodigal/. Contact: [email protected] Supplementary Information: Supplementary data are available at Bioinformatics online.

450 citations

01 Sep 2006
TL;DR: Analyzing the draft genome of the black cottonwood tree, Populus trichocarpa, revealed a whole-genome duplication event; about 8000 pairs of duplicated genes from that event survived in the Populus genome.
Abstract: We report the draft genome of the black cottonwood tree, Populus trichocarpa. Integration of shotgun sequence assembly with genetic mapping enabled chromosome-scale reconstruction of the genome. More than 45,000 putative protein-coding genes were identified. Analysis of the assembled genome revealed a whole-genome duplication event; about 8000 pairs of duplicated genes from that event survived in the Populus genome. A second, older duplication event is indistinguishably coincident with the divergence of the Populus and Arabidopsis lineages. Nucleotide substitution, tandem gene duplication, and gross chromosomal rearrangement appear to proceed substantially more slowly in Populus than in Arabidopsis. Populus has more protein-coding genes than Arabidopsis, ranging on average from 1.4 to 1.6 putative Populus homologs for each Arabidopsis gene. However, the relative frequency of protein domains in the two genomes is similar. Overrepresented exceptions in Populus include genes associated with lignocellulosic wall biosynthesis, meristem development, disease resistance, and metabolite transport.

355 citations

Journal ArticleDOI
TL;DR: In this article, a threading-based protein structure prediction system called PROSPECT is presented, which consists of a dozen tools for identification of protein domains and signal peptide, protein triage to determine the protein type (membrane or globular), protein fold recognition, generation of atomic structural models, prediction result validation, etc.
Abstract: Motivation Experimental techniques alone cannot keep up with the production rate of protein sequences, while computational techniques for protein structure predictions have matured to such a level to provide reliable structural characterization of proteins at large scale. Integration of multiple computational tools for protein structure prediction can complement experimental techniques. Results We present an automated pipeline for protein structure prediction. The centerpiece of the pipeline is our threading-based protein structure prediction system PROSPECT. The pipeline consists of a dozen tools for identification of protein domains and signal peptide, protein triage to determine the protein type (membrane or globular), protein fold recognition, generation of atomic structural models, prediction result validation, etc. Different processing and prediction branches are determined automatically by a prediction pipeline manager based on identified characteristics of the protein. The pipeline has been implemented to run in a heterogeneous computational environment as a client/server system with a web interface. Genome-scale applications on Caenorhabditis elegans, Pyrococcus furiosus and three cyanobacterial genomes are presented. Availability The pipeline is available at http://compbio.ornl.gov/proteinpipeline/

23 citations


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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations

Journal ArticleDOI
TL;DR: Prokka is introduced, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer, and produces standards-compliant output files for further analysis or viewing in genome browsers.
Abstract: UNLABELLED: The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. AVAILABILITY AND IMPLEMENTATION: Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/.

10,432 citations

Journal ArticleDOI
TL;DR: The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates and has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation.
Abstract: The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates. As of September 2008, the database describes the present knowledge on 113 glycoside hydrolase, 91 glycosyltransferase, 19 polysaccharide lyase, 15 carbohydrate esterase and 52 carbohydrate-binding module families. These families are created based on experimentally characterized proteins and are populated by sequences from public databases with significant similarity. Protein biochemical information is continuously curated based on the available literature and structural information. Over 6400 proteins have assigned EC numbers and 700 proteins have a PDB structure. The classification (i) reflects the structural features of these enzymes better than their sole substrate specificity, (ii) helps to reveal the evolutionary relationships between these enzymes and (iii) provides a convenient framework to understand mechanistic properties. This resource has been available for over 10 years to the scientific community, contributing to information dissemination and providing a transversal nomenclature to glycobiologists. More recently, this resource has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation. The CAZy resource resides at URL: http://www.cazy.org/.

6,028 citations

Journal ArticleDOI
TL;DR: An objective measure of genome quality is proposed that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities and is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches.
Abstract: Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.

5,788 citations

Journal ArticleDOI
14 Jan 2010-Nature
TL;DR: An accurate soybean genome sequence will facilitate the identification of the genetic basis of many soybean traits, and accelerate the creation of improved soybean varieties.
Abstract: Soybean (Glycine max) is one of the most important crop plants for seed protein and oil content, and for its capacity to fix atmospheric nitrogen through symbioses with soil-borne microorganisms. We sequenced the 1.1-gigabase genome by a whole-genome shotgun approach and integrated it with physical and high-density genetic maps to create a chromosome-scale draft sequence assembly. We predict 46,430 protein-coding genes, 70% more than Arabidopsis and similar to the poplar genome which, like soybean, is an ancient polyploid (palaeopolyploid). About 78% of the predicted genes occur in chromosome ends, which comprise less than one-half of the genome but account for nearly all of the genetic recombination. Genome duplications occurred at approximately 59 and 13 million years ago, resulting in a highly duplicated genome with nearly 75% of the genes present in multiple copies. The two duplication events were followed by gene diversification and loss, and numerous chromosome rearrangements. An accurate soybean genome sequence will facilitate the identification of the genetic basis of many soybean traits, and accelerate the creation of improved soybean varieties.

3,743 citations