Using high-throughput sequencing data, we have shown that that longest introns in some genes active in brain are removed in two recursive splicing steps, a mechanism previously only seen in Drosophila. By performing sequence analysis, we found that for recursive splicing to work, a recursive splice site (RS) signal is required. We found that such site also requires a cryptic exon, and is normally removed without a trace. However, when two cryptic exons are present, recursive splicing is inefficient, which leads to their inclusion and results in an aberrant transcript that becomes recognized by a machinery that degrades this transcript. We postulate that this may serve as a binary switch for the quality control of new, cryptic isoforms, and as a checkpoint for the evolution of new transcripts. Many of the identified genes are linked to autism and other neurological disorders.
COBISS.SI-ID: 1536358339
Based on statistical analysis of a comprehensive collection of basketball shots, which we compiled through videoanalysis, we discovered practically relevant differences and similarities between different basketball competitions. To achieve this, we developed a novel statistical approach a hierarchical Bayesian variant of multinomial logistic regression, which we dealt with computationally using Hamiltonian Monte Carlo.
COBISS.SI-ID: 4684209
A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists.
COBISS.SI-ID: 1536488643
We developed a method for the estimation of human energy expenditure (the intensity of movement) with an ensemble of regression models. The method uses the readings of n sensors to construct an ensemble of n models. Each model estimates the energy expenditure from the readings of n – 1 sensors in the context of the remaining sensor (e.g., a model estimates the energy expenditure from accelerometers and other sensors in the context of low/medium/high heart rate). The energy expenditure values for different contexts are combined, resulting in a more accurate estimation than by using just one model or by using a dedicated commercial device.
COBISS.SI-ID: 28565543
We have designed, theoretically justified and implemented an original method for visualzation of approximation sets as solutions to multiobjective optimization problems. The method reduces the dimensionality of the approximation set and visualizes it in the form of a prosection matrix. It also allows for visualization of differences between various approximation sets for a given problem. This provides a decision-maker with a better insight into solution quality and problem properties when selecting a final solution.
COBISS.SI-ID: 27961383