ExtendAlign: the post-analysis tool to correct and improve the alignment of dissimilar short sequences
Flores-Torres, M.; Gomez-Romero, L.; Hasse-Hernandez, J. I.; Aguilar-Ordonez, I.; Tovar, H.; Avendano-Vazquez, S. E.; Flores-Jasso, C. F.
Show abstract
In this work, we evaluated several tools used for the alignment of short sequences and found that most aligners execute reasonably well for identical sequences, whereas a variety of alignment errors emerge for dissimilar ones. Since alignments are essential in computational biology, we developed ExtendAlign, a post-analysis tool that corrects these errors and improves the alignment of dissimilar short sequences. We used simulated and biological data to show that ExtendAlign outperforms the other aligners in most metrics tested. ExtendAlign is useful for pinpointing the identity percentage for alignments of short sequences in the range of [~]35-50% similarity.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Positional motif analysis reveals the extent of specificity of protein-RNA interactions observed by CLIP 95%
- ARTEM: a method for RNA and DNA tertiary motif identification with backbone permutations, and its example application to kink-turn-like motifs 95%
- CHESS 3: an improved, comprehensive catalog of human genes and transcripts based on large-scale expression data, phylogenetic analysis, and protein structure 95%
Similar papers in this journal
- Tailored machine learning models for functional RNA detection in genome-wide screens 95%
- BRAKER2: Automatic Eukaryotic Genome Annotation with GeneMark-EP+ and AUGUSTUS Supported by a Protein Database 95%
- Kmerator Suite: design of specific k-mer signatures andautomatic metadata discovery in large RNA-Seq datasets. 95%
Similar papers in this journal
- RNA covariation at helix-level resolution for the identification of evolutionarily conserved RNA structure 95%
- Predicting Mean Ribosome Load for 5'UTR of any length using Deep Learning 95%
- XPRESSyourself: Enhancing, Standardizing, and Automating Ribosome Profiling Computational Analyses Yields Improved Insight into Data 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.