Current methods of gene prediction, their strengths and weaknesses.

By Catherine Mathé, M. Sagot, Thomas Schiex, Pierre Rouzé. Nucleic Acids Research, 2002

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Gene prediction with a hidden Markov model and a new intron submodel (2003, methodology): “For an overview of gene prediction methods see Mathé et al. (2002).”
'Big data', Hadoop and cloud computing in genomics (2013, background): “As further evidence of this, the 1,000 Genomes project [8], which involves sequencing and cataloguing human genetic variation, has deposited two times more raw data into NCBI’s GenBank during its first”
Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. (2008, background): “Much attention has been given to developing alternative, extrinsic methods that use EST/cDNA to genome mapping, spliced alignments of known protein sequences, or patterns of conservation between related genomes (Gelfand et al. 1996; Mott 1997; Mathe et al. 2002; Birney et al. 2004; Stanke et al. 200”
Gene identification in novel eukaryotic genomes by self-training algorithm (2005, background): “Majority of ESTs and cDNAs (if available at all) are related to highly expressed genes and frequently represent partial mRNA (22).”