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Gene Prediction

Overview of attention for book
Cover of 'Gene Prediction'

Table of Contents

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    Book Overview
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    Chapter 1 tRNAscan-SE: Searching for tRNA Genes in Genomic Sequences
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    Chapter 2 Predicting RNA Families in Nucleotide Sequences Using StructRNAfinder
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    Chapter 3 Structural and Functional Annotation of Eukaryotic Genomes with GenSAS
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    Chapter 4 Practical Guide for Fungal Gene Prediction from Genome Assembly and RNA-Seq Reads by FunGAP
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    Chapter 5 Whole-Genome Annotation with BRAKER
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    Chapter 6 EuGene: An Automated Integrative Gene Finder for Eukaryotes and Prokaryotes
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    Chapter 7 ChemGenome2.1: An Ab Initio Gene Prediction Software
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    Chapter 8 Multi-Genome Annotation with AUGUSTUS
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    Chapter 9 GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data
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    Chapter 10 Coding Exon-Structure Aware Realigner (CESAR): Utilizing Genome Alignments for Comparative Gene Annotation
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    Chapter 11 Predicting Genes in Closely Related Species with Scipio and WebScipio
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    Chapter 12 AnABlast: Re-searching for Protein-Coding Sequences in Genomic Regions
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    Chapter 13 Generating Publication-Ready Prokaryotic Genome Annotations with DFAST
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    Chapter 14 BUSCO: Assessing Genome Assembly and Annotation Completeness
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    Chapter 15 Evaluating Genome Assemblies and Gene Models Using gVolante
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    Chapter 16 Choosing the Best Gene Predictions with GeneValidator
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    Chapter 17 COGNATE: Comparative Gene Annotation Characterizer
Attention for Chapter 5: Whole-Genome Annotation with BRAKER
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Chapter title
Whole-Genome Annotation with BRAKER
Chapter number 5
Book title
Gene Prediction
Published by
Humana, New York, NY, January 2019
DOI 10.1007/978-1-4939-9173-0_5
Pubmed ID
Book ISBNs
978-1-4939-9172-3, 978-1-4939-9173-0

Katharina J. Hoff, Alexandre Lomsadze, Mark Borodovsky, Mario Stanke, Hoff, Katharina J., Lomsadze, Alexandre, Borodovsky, Mark, Stanke, Mario

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 133 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 26%
Researcher 19 14%
Student > Bachelor 18 14%
Student > Master 15 11%
Student > Doctoral Student 9 7%
Other 18 14%
Unknown 19 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 48 36%
Agricultural and Biological Sciences 46 35%
Computer Science 4 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Neuroscience 1 <1%
Other 8 6%
Unknown 24 18%