Search results for "Medical Informatics"

Stronger proprioceptive BOLD-responses in the somatosensory cortices reflect worse sensorimotor function in adolescents with and without cerebral pal…

2020

Graphical abstract

Comparison of relaxation techniques in virtual reality for breast cancer patients

2019

A number of studies demonstrated that virtual reality (VR) featuring pleasant scenarios and relaxing narratives is effective in promoting relaxation in users, both in healthy and pathological contexts. One important field for application of relaxing VR is breast cancer, because of therapy-related distress and changes in body imagine experienced by patients during the care process. However, comparisons between different relaxation techniques adapted to virtual reality are rare. In the present study, the same virtual environment has been integrated with audio narratives designed according to two different relaxation techniques (respiration control and body scan). As initial exploration, 16 br…

RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets.

2019

Background MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. Methods We performed three RIP-Chip experiments using either anti-AGO2 or anti-GW182 antibodies and compiled a data set made up of the miRNA and mRNA expression profiles of three samples for each experiment. Specifically, we analyzed the input sample, the immunoprecipita…

Topological structure analysis of chromatin interaction networks.

2019

Abstract Background Current Hi-C technologies for chromosome conformation capture allow to understand a broad spectrum of functional interactions between genome elements. Although significant progress has been made into analysis of Hi-C data to identify biologically significant features, many questions still remain open, in particular regarding potential biological significance of various topological features that are characteristic for chromatin interaction networks. Results It has been previously observed that promoter capture Hi-C (PCHi-C) interaction networks tend to separate easily into well-defined connected components that can be related to certain biological functionality, however, …

2021

Introduction: Digital health technologies such as self-monitoring devices and apps are becoming increasingly important as tools to promote healthy habits and support individuals in their self-care. There is still a scarcity of research that builds on motivational theory to better understand the functioning of digital health technologies. The self-determination theory (SDT) is a macro theory of motivation that delineates three basic psychological needs that are linked to different types of motivation and lead to well-being when satisfied and illbeing when frustrated.Objective: To explore how the use of a digital tool for self-monitoring and communication with healthcare satisfies or frustrat…

GenClust: A genetic algorithm for clustering gene expression data

2005

Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …

Modality-specific dysfunctional neural processing of social-abstract and non-social-concrete information in schizophrenia

2021

Highlights • Social/non-social information processing in three modalities was investigated in SZ. • SZ showed reduced activation for social information only in gesture modality. • Reduced activation in SZ was observed for non-social information only in speech. • Neural Neural processing in bimodal condition is not different between patients and controls.

JANE: efficient mapping of prokaryotic ESTs and variable length sequence reads on related template genomes

2009

Abstract Background ESTs or variable sequence reads can be available in prokaryotic studies well before a complete genome is known. Use cases include (i) transcriptome studies or (ii) single cell sequencing of bacteria. Without suitable software their further analysis and mapping would have to await finalization of the corresponding genome. Results The tool JANE rapidly maps ESTs or variable sequence reads in prokaryotic sequencing and transcriptome efforts to related template genomes. It provides an easy-to-use graphics interface for information retrieval and a toolkit for EST or nucleotide sequence function prediction. Furthermore, we developed for rapid mapping an enhanced sequence align…

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification

2020

Abstract Background Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization. Interestingly, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using DNA sequence as input data. Results In this work, we propose CORENup, a deep learning model for nucleosome identification. CORENup processes a DNA sequence as input using one-hot representation and combines in a parallel fashion a fully convolutional neural network and a recurrent layer. These two parallel …