ArticlePloS one2012
Evaluating high-throughput ab initio gene finders to discover proteins encoded in eukaryotic pathogen genomes missed by laboratory techniques.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Brownotate, a Comprehensive Solution to Generate Protein Sequence Databases for Any Species.Proteomics · 2026Article
- GeneMark-ETP significantly improves the accuracy of automatic annotation of large eukaryotic genomes.Genome research · 2024Article
- A new gene finding tool GeneMark-ETP significantly improves the accuracy of automatic annotation of large eukaryotic genomes.bioRxiv : the preprint server for biology · 2024Article
- Comparative Genome Annotation.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Using AnABlast for intergenic sORF prediction in the Caenorhabditis elegans genome.Bioinformatics (Oxford, England) · 2020Article
- Understanding the causes of errors in eukaryotic protein-coding gene prediction: a case study of primate proteomes.BMC bioinformatics · 2020Article
- A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms.BMC genomics · 2020Article
- Ancient evolutionary signals of protein-coding sequences allow the discovery of new genes in the Drosophila melanogaster genome.BMC genomics · 2020Article
- Repertoire-wide gene structure analyses: a case study comparing automatically predicted and manually annotated gene models.BMC genomics · 2019Article
- Draft Genome of a Blister BeetleFrontiers in genetics · 2019Article
- Long-Read Annotation: Automated Eukaryotic Genome Annotation Based on Long-Read cDNA Sequencing.Plant physiology · 2019Article
- Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data.BMC bioinformatics · 2017Article
- Variant Exported Blood-Stage Proteins Encoded by Plasmodium Multigene Families Are Expressed in Liver Stages Where They Are Exported into the Parasitophorous Vacuole.PLoS pathogens · 2016Article
- Splice Sites Seldom Slide: Intron Evolution in Oomycetes.Genome biology and evolution · 2016Article
- GeneValidator: identify problems with protein-coding gene predictions.Bioinformatics (Oxford, England) · 2016Article
- IPred - integrating ab initio and evidence based gene predictions to improve prediction accuracy.BMC genomics · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next generation sequencing technology is advancing genome sequencing at an unprecedented level. By unravelling the code within a pathogen's genome, every possible protein (prior to post-translational modifications) can theoretically be discovered, irrespective of life cycle stages and environmental stimuli. Now more than ever there is a great need for high-throughput ab initio gene finding. Ab initio gene finders use statistical models to predict genes and their exon-intron structures from the genome sequence alone. This paper evaluates whether existing ab initio gene finders can effectively predict genes to deduce proteins that have presently missed capture by laboratory techniques. An aim here is to identify possible patterns of prediction inaccuracies for gene finders as a whole irrespective of the target pathogen. All currently available ab initio gene finders are considered in the evaluation but only four fulfil high-throughput capability: AUGUSTUS, GeneMark_hmm, GlimmerHMM, and SNAP. These gene finders require training data specific to a target pathogen and consequently the evaluation results are inextricably linked to the availability and quality of the data. The pathogen, Toxoplasma gondii, is used to illustrate the evaluation methods. The results support current opinion that predicted exons by ab initio gene finders are inaccurate in the absence of experimental evidence. However, the results reveal some patterns of inaccuracy that are common to all gene finders and these inaccuracies may provide a focus area for future gene finder developers.
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