scholarly journals Comparative Gene Prediction Based on Gene Structure Conservation

2006 ◽  
pp. 32-41
Author(s):  
Shu Ju Hsieh ◽  
Chun Yuan Lin ◽  
Ning Han Liu ◽  
Chuan Yi Tang
Keyword(s):  
Gene Structure ◽  
Gene Prediction ◽  
Structure Conservation

scholarly journals A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms

2019 ◽  
Author(s):  
Nicolas Scalzitti ◽  
Anne Jeannin-Girardon ◽  
Pierre Collet ◽  
Olivier Poch ◽  
Julie Dawn Thompson
Keyword(s):  
Ab Initio ◽  
Gene Structure ◽  
Structure Prediction ◽  
Gene Prediction ◽  
Draft Genome ◽  
Prediction Methods ◽  
Eukaryotic Genes ◽  
Test Sets ◽  
Structure Complexity ◽  
Genome Assemblies

Abstract Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality, complex gene structures, or a lack of suitable sequences for evidence-based annotations. Results: We describe the construction of a new benchmark, called G3PO (benchmark for Gene and Protein Prediction PrOgrams), designed to represent many of the typical challenges faced by current genome annotation projects. The benchmark is based on a carefully validated and curated set of real eukaryotic genes from 147 phylogenetically disperse organisms, and a number of test sets are defined to evaluate the effects of different features, including genome sequence quality, gene structure complexity, protein length, etc. We used the benchmark to perform an independent comparative analysis of the most widely used ab initio gene prediction programs and identified the main strengths and weaknesses of the programs. More importantly, we highlight a number of features that could be exploited in order to improve the accuracy of current prediction tools. Conclusions: The experiments showed that ab initio gene structure prediction is a very challenging task, which should be further investigated. We believe that the baseline results associated with the complex gene test sets in G3PO provide useful guidelines for future studies.

scholarly journals Whokaryote: distinguishing eukaryotic and prokaryotic contigs in metagenomes based on gene structure

2021 ◽  
Author(s):  
Lotte J U Pronk ◽  
Marnix H Medema
Keyword(s):  
Microbial Community ◽  
Gene Structure ◽  
Gene Prediction ◽  
Gene Clusters ◽  
Intergenic Distance ◽  
Biosynthetic Gene Clusters ◽  
Functional Potential ◽  
Eukaryotic Genes ◽  
Eukaryotic Gene ◽  
Eukaryotic Microbes

Metagenomics has become a prominent technology to study the functional potential of all organisms in a microbial community. Most studies focus on the bacterial content of these communities, while ignoring eukaryotic microbes. Indeed, many metagenomics analysis pipelines silently assume that all contigs in a metagenome are prokaryotic. However, because of marked differences in gene structure, prokaryotic gene prediction tools fail to accurately predict eukaryotic genes. Here, we developed a classifier that distinguishes eukaryotic from prokaryotic contigs based on foundational differences between these taxa in gene structure. We first developed a random forest classifier that uses intergenic distance, gene density and gene length as the most important features. We show that, with an estimated accuracy of 97%, this classifier with principled features grounded in biology can perform almost as well as the classifiers EukRep and Tiara, which use k-mer frequencies as features. By re-training our classifier with Tiara predictions as additional feature, weaknesses of both types of classifiers are compensated; the result is an enhanced classifier that outperforms all individual classifiers, with an F1-score of 1.00 on precision, recall and accuracy for both eukaryotes and prokaryotes, while still being fast. In a reanalysis of metagenome data from a disease-suppressive plant endosphere microbial community, we show how using Whokaryote to select contigs for eukaryotic gene prediction facilitates the discovery of several biosynthetic gene clusters that were missed in the original study. Our enhanced classifier, which we call ′Whokaryote′, is wrapped in an easily installable package and is freely available from https://git.wageningenur.nl/lotte.pronk/whokaryote.

scholarly journals A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms

2020 ◽  
Author(s):  
Nicolas Scalzitti ◽  
Anne Jeannin-Girardon ◽  
Pierre Collet ◽  
Olivier Poch ◽  
Julie Dawn Thompson
Keyword(s):  
Ab Initio ◽  
Gene Structure ◽  
Structure Prediction ◽  
Gene Prediction ◽  
Draft Genome ◽  
Prediction Methods ◽  
Eukaryotic Genes ◽  
Test Sets ◽  
Structure Complexity ◽  
Genome Assemblies

Abstract Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality, complex gene structures, or a lack of suitable sequences for evidence-based annotations. Results: We describe the construction of a new benchmark, called G3PO (benchmark for Gene and Protein Prediction PrOgrams), designed to represent many of the typical challenges faced by current genome annotation projects. The benchmark is based on a carefully validated and curated set of real eukaryotic genes from 147 phylogenetically disperse organisms, and a number of test sets are defined to evaluate the effects of different features, including genome sequence quality, gene structure complexity, protein length, etc. We used the benchmark to perform an independent comparative analysis of the most widely used ab initio gene prediction programs and identified the main strengths and weaknesses of the programs. More importantly, we highlight a number of features that could be exploited in order to improve the accuracy of current prediction tools. Conclusions: The experiments showed that ab initio gene structure prediction is a very challenging task, which should be further investigated. We believe that the baseline results associated with the complex gene test sets in G3PO provide useful guidelines for future studies.

scholarly journals Definition of the Gene Content of the Human Genome: The Need for Deep Experimental Verification

2001 ◽  
Vol 2 (3) ◽  
pp. 169-175 ◽  
Author(s):  
Andrew J. G. Simpson ◽  
Sandro J. de Souza ◽  
Anamaria A. Camargo ◽  
Ricardo R. Brentani
Keyword(s):  
Human Genome ◽  
Gene Structure ◽  
Experimental Verification ◽  
Human Gene ◽  
Sequence Data ◽  
Gene Prediction ◽  
Human Genes ◽  
Number Of Genes ◽  
Definition Of

Based on the analysis of the drafts of the human genome sequence, it is being speculated that our species may possess an unexpectedly low number of genes. The quality of the drafts, the impossibility of accurate gene prediction and the lack of sufficient transcript sequence data, however, render such speculations very premature. The complexity of human gene structure requires additional and extensive experimental verification of transcripts that may result in major revisions of these early estimates of the number of human genes.

Murine CD70: cDNA cloning and gene structure

1997 ◽  
Vol 56 (1-3) ◽  
pp. 56
Author(s):  
K Tesselaar
Keyword(s):  
Cdna Cloning ◽  
Gene Structure

Human hexokinase II mRNA and gene structure

Diabetes ◽  
1995 ◽  
Vol 44 (3) ◽  
pp. 290-294 ◽  
Author(s):  
R. L. Printz ◽  
H. Ardehali ◽  
S. Koch ◽  
D. K. Granner
Keyword(s):  
Gene Structure ◽  
Hexokinase Ii
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