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Can MiRBase provide positive data for machine learning for the detection of MiRNA hairpins?
(Informationsmanagement in der Biotechnologie e.V., 2013)
Experimental detection and validation of miRNAs is a tedious, time-consuming, and expensive process. Computational methods for miRNA gene detection are being developed so that the number of candidates that need experimental ...
Data mining for microrna gene prediction: On the impact of class imbalance and feature number for microrna gene prediction
MicroRNAs (miRNAs) are small, non-coding RNAs which are involved in the posttranscriptional modulation of gene expression. Their short (18-24) single stranded mature sequences are involved in targeting specific genes. It ...
Development of EST-SSR markers for diversity and breeding studies in opium poppy
All publicly available opium poppy expressed sequence tag (EST) sequences, totalling 20 885, were assembled into unigenes and examined for simple sequence repeats (SSRs). Nearly 19% of the 14 957 unigenes contained SSRs ...
Ranking tandem mass spectra: And the impact of database size and scoring function on peptide spectrum matches
Proteomics is currently driven by mass spectrometry. For the analysis of tandem mass spectra many computational algorithms have been proposed. There are two approaches, one which assigns a peptide sequence to a tandem mass ...
Comparison of four Ab initio MicroRNA prediction tools
MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by ...