c4Lab 的計算與系統生物學奇幻之旅

Nowadays, we teach computers to learn skills to achieve some tasks. Computers classify news, filter junk emails, play games, compose music, and even monitor terrorism. In c4Lab, we teach computers biology. Even better, computers learn biology by itself. We call the knowledge organized by computers prediction models, and the information delivered by computers predictions. As the prediction accuracy increases, computational tools provide us with more and more facts about living organisms.

2013年9月28日星期六

Genome annotation

本週從MAKER2出發!

MAKER2於2011發表於BMC Bioinformatics，截至2013/9/28為止，在Google Scholar累積28篇論文引用之。在這些引用MAKER2的論文中，我們已經先看過A beginner's guide to eukaryotic genome annotation，也用過了ParsEval: parallel comparison and analysis of gene structure annotations。其中值得閱讀的相關文獻有：

接著看PASA2，自Haas於2003年發表的工具PASA延續開發至今日的版本，近期主要的參考文獻有：

Comparative Functional Genomics of the Fission Yeasts

追蹤到SNAP與CEGMA：

在ab initio prediction (e.g. Augustus)階段就加入RNA-seq資訊也是可以考慮的方法：

Incorporating Illumina RNAseq into AUGUSTUS with Tophat

最後，另有一可能的解決方案，是直接從RNA-seq data著手：

Genome-guided Trinity for Gene Structure Annotation

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