Erinija Pranckeviciene

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Despite its poorly adapted codon usage, HIV-1 replicates and is expressed extremely well in human host cells. HIV-1 has recently been shown to package non-lysyl transfer RNAs (tRNAs) in addition to the tRNA(Lys) needed for priming reverse transcription and integration of the HIV-1 genome. By comparing the codon usage of HIV-1 genes with that of its human(More)
We investigated the geometrical complexity of several high-dimensional, small sample classification problems and its changes due to two popular feature selection procedures, forward feature selection (FFS) and Linear Programming Support Vector Machine (LPSVM). We found that both procedures are able to transform the problems to spaces of very low(More)
Many real-world classification problems are represented by very sparse and high-dimensional data. The recent successes of a linear programming support vector machine (LPSVM) for feature selection motivated a deeper analysis of the method when applied to sparse, multivariate data. Due to the sparseness, the selection of a classification model is greatly(More)
Skeletal muscle differentiation is mediated by a complex gene expression program requiring both the muscle-specific transcription factor Myogenin (Myog) and p38α MAPK (p38α) signaling. However, the relative contribution of Myog and p38α to the formation of mature myotubes remains unknown. Here, we have uncoupled the activity of Myog from that of p38α to(More)
We investigate the relative efficacy of several classification models with and without feature selection. Simple classification rules are frequently preferable and superior to more complex models for microarray data that are typically undersampled. Improved classification accuracy is obtained with feature selection. We summarize some of the important(More)
OBJECTIVE Demonstrate that incorporating domain knowledge into feature selection methods helps identify interpretable features with predictive capability comparable to a state-of-the-art classifier. METHODS Two feature selection methods, one using a genetic algorithm (GA) the other a L(1)-norm support vector machine (SVM), were investigated on three(More)
Every next generation sequencing (NGS) platform relies on proprietary and open source computational tools to analyze sequencing data. NGS tools for Illumina platforms are well documented which is not the case with AB SOLiD systems. We applied several computational and variant calling pipelines to analyse targeted exome sequencing data obtained using AB(More)