Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgements
- Design and conventions of this book
- 1 Introduction: working with the molecules of life in the computer
- 2 Gene technology: cutting DNA
- 3 Gene technology: knocking genes down
- 4 Gene technology: amplifying DNA
- 5 Human disease: when DNA sequences are toxic
- 6 Human disease: iron imbalance and the iron responsive element
- 7 Human disease: cancer as a result of aberrant proteins
- 8 Evolution: what makes us human?
- 9 Evolution: resolving a criminal case
- 10 Evolution: the sad case of the Tasmanian tiger
- 11 A function to every gene: termites, metagenomics and learning about the function of a sequence
- 12 A function to every gene: royal blood and order in the sequence universe
- 13 A function to every gene: a slimy molecule
- 14 Information resources: learning about flu viruses
- 15 Finding genes: going ashore at CpG islands
- 16 Finding genes: in the world of snurpsp
- 17 Finding genes: hunting for the distant RNA relatives
- 18 Personal genomes: the differences between you and me
- 19 Personal genomes: what’s in my genome?
- 20 Personal genomes: details of family genetics
- Appendix I Brief Unix reference
- Appendix II A selection of biological sequence analysis software
- Appendix III A short Perl reference
- Appendix IV A brief introduction to R
- Index
- References
16 - Finding genes: in the world of snurpsp
Published online by Cambridge University Press: 05 August 2012
- Frontmatter
- Contents
- Preface
- Acknowledgements
- Design and conventions of this book
- 1 Introduction: working with the molecules of life in the computer
- 2 Gene technology: cutting DNA
- 3 Gene technology: knocking genes down
- 4 Gene technology: amplifying DNA
- 5 Human disease: when DNA sequences are toxic
- 6 Human disease: iron imbalance and the iron responsive element
- 7 Human disease: cancer as a result of aberrant proteins
- 8 Evolution: what makes us human?
- 9 Evolution: resolving a criminal case
- 10 Evolution: the sad case of the Tasmanian tiger
- 11 A function to every gene: termites, metagenomics and learning about the function of a sequence
- 12 A function to every gene: royal blood and order in the sequence universe
- 13 A function to every gene: a slimy molecule
- 14 Information resources: learning about flu viruses
- 15 Finding genes: going ashore at CpG islands
- 16 Finding genes: in the world of snurpsp
- 17 Finding genes: hunting for the distant RNA relatives
- 18 Personal genomes: the differences between you and me
- 19 Personal genomes: what’s in my genome?
- 20 Personal genomes: details of family genetics
- Appendix I Brief Unix reference
- Appendix II A selection of biological sequence analysis software
- Appendix III A short Perl reference
- Appendix IV A brief introduction to R
- Index
- References
Summary
I fell in love with RNA in one of my first jobs as an undergraduate.
(Joan Steitz, quoted by Sedwick, 2011)Methods of gene prediction
We saw in the previous chapter how prediction of CpG islands may be used to identify transcription start sites of protein-coding genes. However, there are many other elements and statistical properties of such genes that we may exploit for gene finding.
What are the methods available for computational gene finding? In general, one may distinguish between two major categories: de novo or ab initio methods and homology-based methods. The de novo methods make use of statistical signals in DNA sequences that are characteristic of protein-coding genes; the homology-based methods rely on the identification of exons by matching known mRNA or protein sequences or even profile HMMs to a genomic sequence. The homology-based methods are powerful but they require that mRNA or protein sequence information is available. Here we will focus on the de novo type of gene finding. What are the signals characteristic of proteincoding genes?
- Type
- Chapter
- Information
- Genomics and BioinformaticsAn Introduction to Programming Tools for Life Scientists, pp. 208 - 221Publisher: Cambridge University PressPrint publication year: 2012