Eukaryotic Gene Prediction - Rice Genome Annotation Project

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Gene Prediction Approaches Intrinsic (ab(initio)GENSCAN, FGENESH, GeneMark.hmmGlimmerM,Genie; Extrinsic (similarity-based)Spliced alignment: GenomeScan, EuGene, , FGENESH+,FGENESH_C, GeneId+, etc;Genomic comparison: TwinScan, , TWAIN, SLAM, SGP,FGENESH_2, etc;IntegratedGeneScope, GeneMachine, , JIGSAW (combiner),RiceGAAS, Ensembl, , etc.
Gene Discovery via Multiple GeneFinders
Page 3: Gene Structure
Page 7 and 8: Gene Prediction Approaches Intrinsi
Page 9 and 10: Development of a Gene Finder Build
Page 11 and 12: Nucleotide level Exon level Gene le
Page 13 and 14: Exon LevelPrediction accuracy with
Page 15 and 16: A Simple CalculationGiven x accurac
Page 17 and 18: Maize Gene Prediction
Page 19 and 20: Accuracy
Page 21 and 22: Gene Prediction Approaches Intrinsi
Page 23 and 24: EST/cDNA Spliced Alignment
Page 25 and 26: Genomic ComparisonMicrosynteny betw
Page 27 and 28: Comparative Analysis of CerealGene
Page 29 and 30: Pros and ConsProsAid to identify lo
Page 31: ARTADE-ARabidopsisTiling-Array-base
Page 35 and 36: TIGR Rice Genome AnnotationPipeline
Page 37 and 38: EnsemblGenePredictionProcedure
Page 39 and 40: Case Study
Page 41 and 42: Create a Gene Model
Page 43 and 44: Expression Data in Gbrowse
Page 45 and 46: Ovary and mature stigma
Page 47: “Have no fear of perfection -you'

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