GeneSplicer: a new computational method for splice site prediction.

By Mihaela Pertea, Xiaoying Lin, Steven L. Salzberg. Nucleic Acids Research, 2001

651 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/402c6d9061b5aa6a78cbf761e6e0936b3eab08b6

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In Molecular Biology

Citations in the corpus

In silico prediction of splice-altering single nucleotide variants in the human genome (2014, methodology): “To compare the predictive performance of PWM, MES, NNSplice, GeneSplicer, HSF, NetGene2, GENSCAN and SplicePredictor, we first examined the ability of these tools to identify wild-type splice sites for all variants in our dataset and treated them as a missing score if the wild-type score of a varian”
Variation Interpretation Predictors: Principles, Types, Performance, and Choice (2016, methodology): “Several methods have been developed to predict splice sites [Hebsgaard et al., 1996; Pertea et al., 2001; Yeo and Burge, 2004] and splicing regulatory sites [Fairbrother et al.”
A deficit of detoxification enzymes: pesticide sensitivity and environmental response in the honeybee (2006, methodology): “GeneSplicer splice site prediction software (Pertea et al., 2001) and BioPerl scripts (Stajich et al.”
An enhanced computational platform for investigating the roles of regulatory RNA and for identifying functional RNA motifs (2013, methodology): “Numerous data sources, such as Rfam [4], fRNAdb [6] and UTRsite [1], and identification approaches, such as GeneSplicer [15], RiboSW [21] and RBSfinder [17], were integrated in RegRNA 2.0, and other additional information, such as GC-content ratio and RNA accessibility, are also presented on the web”
Current methods of gene prediction, their strengths and weaknesses. (2002, background): “GeneSplicer (152) Arabidopsis, human HMM + MDD NETPLANTGENE (42) (http://www.”
TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders (2004, methodology): “Whereas TigrScan utilizes several types of weight matrices and Markov chains, GlimmerHMM additionally incorporates splice site models adapted from the GeneSplicer program (Pertea et al., 2001) and a decision tree adapted from GlimmerM (Salzberg et al., 1999).”
A Guide for Functional Analysis of BRCA1 Variants of Uncertain Significance (VUS) (2012, neutral): “shtml [Pertea et al., 2001]”
Predicting Splicing from Primary Sequence with Deep Learning. (2019, methodology): “To benchmark the performance of our network against existing methods, we selected three popular classifiers that have been referenced in the literature for rare genetic disease diagnosis, GeneSplicer (Pertea et al., 2001), MaxEntScan (Yeo and Burge, 2004), and NNSplice (Reese et al.”