GeneID in Drosophila.

By Genís Parra, Enrique Blanco, Roderic Guigó. Genome Research, 2000

405 citations recorded by the source corpus.

GeneID is a program to predict genes in anonymous genomic sequences designed with a hierarchical structure. In the first step, splice sites, and start and stop codons are predicted and scored along the sequence using position weight matrices (PWMs). In the second step, exons are built from the sites. Exons are scored as the sum of the scores of the defining sites, plus the log-likelihood ratio of a Markov model for coding DNA. In the last step, from the set of predicted exons, the gene structure is assembled, maximizing the sum of the scores of the assembled exons. In this paper we describe the obtention of PWMs for sites, and the Markov model of coding DNA in Drosophila melanogaster. We also compare other models of coding DNA with the Markov model. Finally, we present and discuss the results obtained when GeneID is used to predict genes in the Adh region. These results show that the accuracy of GeneID predictions compares currently with that of other existing tools but that GeneID is likely to be more efficient in terms of speed and memory usage.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1d4fdcb6331b21a3334b37c288f23e55ef192907

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Citations in the corpus

AUGUSTUS: a web server for gene finding in eukaryotes (2004, positive): “A large number of gene-finding programs have been proposed since the 1980s, e.g. GENIE (1), GENSCAN (2) and GENEID (3).”
Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources (2006, methodology): “Examples are the programs GENSCAN [1], AUGUSTUS [2] and HMMGene [3] which are HMM-based and GENEID [ 4 ].”
GENCODE: producing a reference annotation for ENCODE (2006, background): “…for splice junctions from all those gene objects predicted by a panel of automated gene prediction algorithms before the E-GASP workshop (Geneid [12], Genescan [13], Twinscan [14], SGP [15], Fgenesh [16], Exonify [17], Acembly [18] Ecgene [19], Ensembl EST [20]) that lie outside a HAVANA…”
GeneMark-EP+: eukaryotic gene prediction with self-training in the space of genes and proteins (2020, positive): “Therefore, ab initio gene finders [e.g. GENSCAN (13), Gen-eMark.hmm (14), AUGUSTUS (15) or GeneID (16)] have been a necessary part of genome annotation tools and pipelines [e.g. GNOMON (17), PASA (18) and Ensembl (19)].”
Using geneid to Identify Genes (2002, methodology): “Version 1.0 of geneid (Parra et al., 2000) was completely rewritten at the IMIM.”
Long non-coding RNAs with enhancer-like function in human (2010, methodology): “Analysis of protein coding potential of the ncRNAs using GeneID (Blanco et al., 2007; Parra et al., 2000) shows ncRNAs coding potential comparable to that of ancestral repeats (Lunter et al.”
CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes (2007, background): “Genscan (Burge and Karlin, 1997) and geneid (Parra et al ., 2000) are the two examples of this approach and they can find both known genes and novel genes as long as the genes fit the underlying probabilistic model.”
Combining gene prediction methods to improve metagenomic gene annotation (2011, methodology): “There are a large number of ab-initio gene-finding programs, e.g.: GENIE [5], GENSCAN [6], GENEID [7], GLIMMER [8], and GeneMark [9].”
Gene finding in novel genomes (2004, neutral): “SNAP is similar to Genscan and other generalized hidden Markov model (HMM) gene finders [9-13], but unlike many, it is easily adaptable to a number of organisms and its source code is freely available.”
Gene prediction with a hidden Markov model and a new intron submodel (2003, methodology): “Examples of ab initio programs are GENSCAN (Burge, 1997), GENIE (Kulp et al., 1996), HMMGene (Krogh, 1997) and GENEID (Parraet al., 2000).”
AUGUSTUS at EGASP: using EST, protein and genomic alignments for improved gene prediction in the human genome (2006, methodology): “Besides AUGUSTUS, these programs were GENSCAN [7], GeneID [8], GeneMark.hmm [9] and Genezilla [10].”