Literature DB >> 11860211

Computational gene finding in plants.

Mihaela Pertea1, Steven L Salzberg.   

Abstract

Automated methods for identifying protein coding regions in genomic DNA have progressed significantly in recent years, but there is still a strong need for more accurate computational solutions to the gene finding problem. Large-scale genome sequencing projects depend greatly on gene finding to generate accurate and complete gene annotation. Improvements in gene finding software are being driven by the development of better computational algorithms, a better understanding of the cell's mechanisms for transcription and translation, and the enormous increases in genomic sequence data. This paper reviews some of the most widely used algorithms for gene finding in plants, including technical descriptions of how they work and recent measurements of their success on the genomes of Arabidopsis thaliana and rice.

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Year:  2002        PMID: 11860211

Source DB:  PubMed          Journal:  Plant Mol Biol        ISSN: 0167-4412            Impact factor:   4.076


  35 in total

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Authors:  R Farber; A Lapedes; K Sirotkin
Journal:  J Mol Biol       Date:  1992-07-20       Impact factor: 5.469

2.  Computational gene identification: an open problem.

Authors:  R Guigó
Journal:  Comput Chem       Date:  1997

Review 3.  Computational methods for the identification of genes in vertebrate genomic sequences.

Authors:  J M Claverie
Journal:  Hum Mol Genet       Date:  1997       Impact factor: 6.150

4.  Evaluation of gene prediction software using a genomic data set: application to Arabidopsis thaliana sequences.

Authors:  N Pavy; S Rombauts; P Déhais; C Mathé; D V Ramana; P Leroy; P Rouzé
Journal:  Bioinformatics       Date:  1999-11       Impact factor: 6.937

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Authors:  M Q Zhang; T G Marr
Journal:  Comput Appl Biosci       Date:  1993-10

6.  Identification of new Schistosoma mansoni genes by the EST strategy using a directional cDNA library.

Authors:  G R Franco; M D Adams; M B Soares; A J Simpson; J C Venter; S D Pena
Journal:  Gene       Date:  1995-01-23       Impact factor: 3.688

7.  Prediction of transcription terminators in bacterial genomes.

Authors:  M D Ermolaeva; H G Khalak; O White; H O Smith; S L Salzberg
Journal:  J Mol Biol       Date:  2000-08-04       Impact factor: 5.469

8.  Microbial gene identification using interpolated Markov models.

Authors:  S L Salzberg; A L Delcher; S Kasif; O White
Journal:  Nucleic Acids Res       Date:  1998-01-15       Impact factor: 16.971

9.  Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information.

Authors:  S M Hebsgaard; P G Korning; N Tolstrup; J Engelbrecht; P Rouzé; S Brunak
Journal:  Nucleic Acids Res       Date:  1996-09-01       Impact factor: 16.971

10.  Predicting internal exons by oligonucleotide composition and discriminant analysis of spliceable open reading frames.

Authors:  V V Solovyev; A A Salamov; C B Lawrence
Journal:  Nucleic Acids Res       Date:  1994-12-11       Impact factor: 16.971

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  12 in total

1.  Computational gene prediction using multiple sources of evidence.

Authors:  Jonathan E Allen; Mihaela Pertea; Steven L Salzberg
Journal:  Genome Res       Date:  2004-01       Impact factor: 9.043

2.  Evaluation of five ab initio gene prediction programs for the discovery of maize genes.

Authors:  Hong Yao; Ling Guo; Yan Fu; Lisa A Borsuk; Tsui-Jung Wen; David S Skibbe; Xiangqin Cui; Brian E Scheffler; Jun Cao; Scott J Emrich; Daniel A Ashlock; Patrick S Schnable
Journal:  Plant Mol Biol       Date:  2005-02       Impact factor: 4.076

3.  Targeted analysis of orthologous phytochrome A regions of the sorghum, maize, and rice genomes using comparative gene-island sequencing.

Authors:  Daryl T Morishige; Kevin L Childs; L David Moore; John E Mullet
Journal:  Plant Physiol       Date:  2002-12       Impact factor: 8.340

4.  Comparing low coverage random shotgun sequence data from Brassica oleracea and Oryza sativa genome sequence for their ability to add to the annotation of Arabidopsis thaliana.

Authors:  Manpreet S Katari; Vivekanand Balija; Richard K Wilson; Robert A Martienssen; W Richard McCombie
Journal:  Genome Res       Date:  2005-04       Impact factor: 9.043

5.  MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource for plant genomics.

Authors:  Heiko Schoof; Rebecca Ernst; Vladimir Nazarov; Lukas Pfeifer; Hans-Werner Mewes; Klaus F X Mayer
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

Review 6.  Structural and functional analysis of rice genome.

Authors:  Akhilesh K Tyagi; Jitendra P Khurana; Paramjit Khurana; Saurabh Raghuvanshi; Anumapa Gaur; Anita Kapur; Vikrant Gupta; Dibyendu Kumar; V Ravi; Shubha Vij; Parul Khurana; Sulabha Sharma
Journal:  J Genet       Date:  2004-04       Impact factor: 1.166

7.  Genomic comparison of P-type ATPase ion pumps in Arabidopsis and rice.

Authors:  Ivan Baxter; Jason Tchieu; Michael R Sussman; Marc Boutry; Michael G Palmgren; Michael Gribskov; Jeffrey F Harper; Kristian B Axelsen
Journal:  Plant Physiol       Date:  2003-06       Impact factor: 8.340

8.  Specific versus non-specific immune responses in an invertebrate species evidenced by a comparative de novo sequencing study.

Authors:  Emeline Deleury; Géraldine Dubreuil; Namasivayam Elangovan; Eric Wajnberg; Jean-Marc Reichhart; Benjamin Gourbal; David Duval; Olga Lucia Baron; Jérôme Gouzy; Christine Coustau
Journal:  PLoS One       Date:  2012-03-12       Impact factor: 3.240

9.  A method for identifying alternative or cryptic donor splice sites within gene and mRNA sequences. Comparisons among sequences from vertebrates, echinoderms and other groups.

Authors:  Katherine M Buckley; Liliana D Florea; L Courtney Smith
Journal:  BMC Genomics       Date:  2009-07-16       Impact factor: 3.969

Review 10.  Apollo: a sequence annotation editor.

Authors:  S E Lewis; S M J Searle; N Harris; M Gibson; V Lyer; J Richter; C Wiel; L Bayraktaroglu; E Birney; M A Crosby; J S Kaminker; B B Matthews; S E Prochnik; C D Smithy; J L Tupy; G M Rubin; S Misra; C J Mungall; M E Clamp
Journal:  Genome Biol       Date:  2002-12-23       Impact factor: 13.583

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