Jonathan E Allen
Affiliation: Lawrence Livermore National Laboratory
- Genome sequence and comparative analysis of the model rodent malaria parasite Plasmodium yoelii yoeliiJane M Carlton
The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, Maryland 20850, USA
Nature 419:512-9. 2002..This is the first genome sequence of a model eukaryotic parasite, and it provides insight into the use of such systems in the modelling of Plasmodium biology and disease...
- JIGSAW: integration of multiple sources of evidence for gene predictionJonathan E Allen
Center for Bioinformatics and Computational Biology, University of Maryland Institute for Advanced Computer Studies, College Park, MD 20742, USA
Bioinformatics 21:3596-603. 2005..Genome annotation pipelines collect a variety of types of evidence about gene structure and synthesize the results, which can then be refined further through manual, expert curation of gene models...
- Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced AlignmentsBrian J Haas
J Craig Venter Institute, The Institute for Genomic Research, Rockville, Maryland 20850, USA
Genome Biol 9:R7. 2008..Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation...
- Conserved amino acid markers from past influenza pandemic strainsJonathan E Allen
Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA
BMC Microbiol 9:77. 2009..Influenza proteomes from distinct viral phenotype classes were searched for class specific amino acid mutations conserved in past pandemics, using reverse engineered linear classifiers...
- DNA signatures for detecting genetic engineering in bacteriaJonathan E Allen
Lawrence Livermore National Lab, Livermore, CA 94550, USA
Genome Biol 9:R56. 2008..Such DNA signatures could be important in detecting genetically engineered bacteria in environmental samples...
- Ultra-deep mutant spectrum profiling: improving sequencing accuracy using overlapping read pairsHaiyin Chen-Harris
Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA, USA
BMC Genomics 14:96. 2013..05%). CONCLUSIONS: Our rare variant detection strategies have important implications beyond viral evolution and can be applied to any basic and clinical research area that requires the identification of rare mutations...
- Scalable metagenomic taxonomy classification using a reference genome databaseSasha K Ames
Center for Applied Scientific Computing, Lawrence Livermore National Laboratory and Global Security Directorate, P O Box 808, Livermore, CA 94551, USA
Bioinformatics 29:2253-60. 2013..Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge...
- The role of viral population diversity in adaptation of bovine coronavirus to new host environmentsMonica K Borucki
Lawrence Livermore National Laboratory, Livermore, CA, USA
PLoS ONE 8:e52752. 2013....
- JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regionsJonathan E Allen
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
Genome Biol 7:S9.1-13. 2006....
- The genome of the basidiomycetous yeast and human pathogen Cryptococcus neoformansBrendan J Loftus
Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA
Science 307:1321-4. 2005..neoformans encodes unique genes that may contribute to its unusual virulence properties, and comparison of two phenotypically distinct strains reveals variation in gene content in addition to sequence polymorphisms between the genomes...
- Computational gene prediction using multiple sources of evidenceJonathan E Allen
The Institute for Genomic Research, Rockville, Maryland 20850, USA
Genome Res 14:142-8. 2004..Our results show that combining gene prediction evidence consistently outperforms even the best individual gene finder and, in some cases, can produce dramatic improvements in sensitivity and specificity...