When we were asked for help with high-level microarray data analysis (on Affymetrix HGU-133A microarray), we faced the problem of selecting an appropriate method. We wanted to select a method that would yield "the best result" (detected as many "really" differentially expressed genes (DEGs) as possible, without false positives and false negatives). However, life scientists could not help us – they use their "favorite" method without special argumentation. We also did not find any norm or recommendation. Therefore, we decided to examine it for our own purpose. We considered whether the results obtained using different methods of high-level microarray data analyses – Significant Analysis of Microarrays, Rank Products, Bland-Altman, Mann-Whitney test, T test and the Linear Models for Microarray Data – would be in agreement. Initially, we conducted a comparative analysis of the results on eight real data sets from microarray experiments (from the Array Express database). The results were surprising. On the same array set, the set of DEGs by different methods were significantly different. We also applied the methods to artificial data sets and determined some measures that allow the preparation of the overall scoring of tested methods for future recommendation. We found a very low level concordance of results from tested methods on real array sets. The number of common DEGs (detected by all six methods on fixed array sets, checked on eight array sets) ranged from 6 to 433 (22,283 total array readings). Results on artificial data sets were better than those on the real data. However, they were not fully satisfying. We scored tested methods on accuracy, recall, precision, f-measure and Matthews correlation coefficient. Based on the overall scoring, the best methods were SAM and LIMMA. We also found TT to be acceptable. The worst scoring was MW. Based on our study, we recommend: 1. Carefully taking into account the need for study when choosing a method, 2. Making high-level analysis with more than one method and then only taking the genes that are common to all methods (which seems to be reasonable) and 3. Being very careful (while summarizing facts) about sets of differentially expressed genes: different methods discover different sets of DEGs.

The spatial organization of chromatin within the interphase nucleus and the interactions between chromosome territories (CTs) are essential for various biological processes, such as DNA replication, transcription, and repair. However, detailed data about the CT arrangement in monocotyledonous plants are scarce. In this study, chromosome painting was used to analyse the distribution and associations of individual chromosomes in the 3-D preserved nuclei of Brachypodium distachyon root cells in order to determine the factors that may have an impact on the homologous CT arrangement. It was shown that the frequency of CT association is linked to the steric constraints imposed by the limited space within the nucleus and may depend on chromosome size and morphology as well as on the nuclear shape. Furthermore, in order to assess whether the distribution of interphase chromosomes is random or is subject to certain patterns, a comparison between the experimental data and the results of a computer simulation (ChroTeMo), which was based on a fully probabilistic distribution of the CTs, was performed. This comparison revealed that homologous chromosome arm CTs associate more often than if they were randomly arranged inside the interphase nucleus.

This paper presents ChroTeMo, a tool for chromosome territory modelling, accompanied by ChroTeVi–a chromosome territory visualisation software that uses the data obtained by ChroTeMo. These tools have been developed in order to complement the molecular cytogenetic research of interphase nucleus structure in a model grass Brachypodium distachyon. Although the modelling tool has been initially created for one particular species, it has universal application. The proposed version of ChroTeMo allows for generating a model of chromosome territory distribution in any given plant or animal species after setting the initial, species-specific parameters. ChroTeMo has been developed as a fully probabilistic modeller. Due to this feature, the comparison between the experimental data on the structure of a nucleus and the results obtained from ChroTeMo can indicate whether the distribution of chromosomes inside a nucleus is also fully probabilistic or is subjected to certain non-random patterns. The presented tools have been written in Python, so they are multiplatform, portable and easy to read. Moreover, if necessary they can be further developed by users writing their portions of code. The source code, documentation, and wiki, as well as the issue tracker and the list of related articles that use ChroTeMo and ChroTeVi, are accessible in a public repository at Github under GPL 3.0 license.

This article presents a comparative international research study analyzing the opinions of students from Poland, Ukraine, and Kazakhstan regarding the importance, popularity, and elements of educational platforms in the field of computer science. The study employed the Kruskal-Wallis test for statistical analysis. The research questions addressed are as follows: RQ1: What are educational platforms in general, and which specific platforms are most popular among students from Poland, Ukraine, and Kazakhstan? RQ2: Which topics are most frequently searched for on educational platforms, and what motivates students from these countries to engage in learning through educational platforms? RQ3: How do students from Poland, Ukraine, and Kazakhstan evaluate the usefulness of different types of content posted on educational platforms, and do they use various platforms to share their code? Two hypotheses are proposed: firstly, that the country of origin of the student does not significantly affect the frequency of use of educational platforms, and secondly, that the country of origin does influence the choice of courses students are interested in on educational platforms. The most popular topics on these platforms are programming and computer networks, with students from Kazakhstan also displaying a keen interest in subjects related to artificial intelligence and computer graphics. Additionally, this study analyzes the conditions of learning and teaching in specialized modules at each university, including teacher requirements, curriculums, and the potential for practical implementation of new knowledge by students. Furthermore, the study examines course elements that are most essential to students, such as video recordings of lectures, tutorials/instructional videos, practical tasks, and solutions to tasks. The article concludes with a discussion and summary of the findings.

The article presents a new operation in the genetic algorithm. This operation mimics the epigenetic process of cytosine methylation. The Epigenetic processes have a huge impact on the functioning of living organisms, but have not yet been reflected in the operations of genetic algorithms. In a study on the evaluation of the operation mimics epigenetics process were used genetic algorithm for Knapsack issue.