A computational analysis of sequence features involved in recognition of short introns

By Lee P. Lim, C. Burge. Proceedings of the National Academy of Sciences of the United States of America, 2001

387 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/00bc7f17d805fff8d3b294ede69512a0723bcc9c

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Citations in the corpus

Mammalian mirtron genes. (2007, background): “The relative proportion of such introns in different species is flies > worms > mammals (Lim and Burge, 2001; Yandell et al., 2006).”
Opportunities and challenges Genome-wide analyses of alternative splicing in plants: (2008, neutral): “…2000; Reddy 2001; Jurica and Moore 2002), but the known splicing regulatory sequences (5Ј and 3Ј splices sites, branch points, and intron–exon sequence elements, see above) lack sufficient information on their own to direct the splicing machinery to the correct splice sites (Lim and Burge 2001).”
Genomewide analysis of Drosophila circular RNAs reveals their structural and sequence properties and age-dependent neural accumulation (2014, neutral): “melanogaster intron lengths are bimodal (Lim and Burge, 2001), with a predominant peak of 50–150 bp followed by a broad distribution of longer introns.”
GMAP: a genomic mapping and alignment program for mRNA and EST sequence (2005, methodology): “Such models are used widely inab initio gene finding programs (Uberbacher and Mural, 1991; Burge and Karlin, 1997; Lukashin and Borodovsky, 1998; Salzberget al., 1999; Reeset al., 2000) and in homologybased gene finding programs (Guigóet al., 1992; Huanget al., 1997; Gotoh, 1999; Batzoglouet al.,…”
Non–coding RNA genes and the modern RNA world (2001, background): “, and it might also be possible to identify untranslated, spliced ncRNAs by the computational identification of clustered splice-site signal”
Pre-mRNA splicing and human disease. (2003, background): “DM type 2 (DM2) is caused by a large CCTG expansion in intron 1 of the ZNF9 gene on Chromosome 3q21 (Liquori et al. 2001).”
Comparative analysis identifies exonic splicing regulatory sequences--The complex definition of enhancers and silencers. (2006, background): “one-half of the information required for recognition by the splicing machinery (Lim and Burge, 2001).”
Gene prediction with a hidden Markov model and a new intron submodel (2003, background): “This is suggested by the assumption that the splicing process is typically different for long and short introns (Lim and Burge, 2001).”
Variation in alternative splicing across human tissues (2004, background): “A number of cis-regulatory elements in exons or introns that play key regulatory roles have also been identified, using a variety of methods including site-directed mutagenesis, systematic evolution of ligands by exponential enrichment (SELEX) and computational approaches [18-22].”
Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. (2008, methodology): “Structures of the BP models used varied from a positional frequency matrix in NetGene2 (Hebsgaard et al. 1996), IntronScan (Lim and Burge 2001), and GipsyGene (Neverov et al. 2003) to the second-order windowed weight array matrix (WWAM) generating a 21-nt-long sequence in GenScan (Burge and Karlin…”
Gene finding in novel genomes (2004, background): “Since sequence features such as codon bias [7] and splicing signals [8] vary from organism to organism, it is expected that gene finders may not perform optimally in a foreign genome.”
Comprehensive splice-site analysis using comparative genomics (2006, background): “The information content is a measure of the degree of conservation in splice-site sequences, with lower information content corresponding to a higher degree of conservation, and vice versa (24,65–68).”