<abstract xmlns="http://www.w3.org/1999/xhtml">

Prostate cancer is a severe threat to human lives. Approximately 1 in 7 men will be diagnosed with prostate cancer throughout their lifetimes, and 1 in 39 men will die from prostate cancer. There are many factors which increase or decrease the survival time of prostate cancer patients. Data is used here from a randomised clinical trial for the choice of treatment for prostate cancer patients in stages 3 and 4. This study is done to identify probable variables that influence the survival time of patients only for these two stages. The AFT and the Cox-PH models determine how variables affect prostate cancer patients' survival time.
</abstract>

Evaluation of the Effect of Prognostic Variables on the Survival Analysis of Prostate Cancer

<abstract xmlns="http://www.w3.org/1999/xhtml">

This paper concerns the problem of diagnosing the type of cancer with the use of machine learning and statistical methods. Nowadays, the problem of neoplasms, in particular breast cancer, is one of humanity's greatest challenges. The identification of cancer and its type is extremely important. In solving this problem, classification methods can be used as objective tools that may be helpful for doctors making a diagnosis. For this reason, we discuss many efficient classifiers in the context of cancer detection. In addition, we consider the topic of data set transformations to deal with the problem of data unbalance, as well as measures of classification quality. In the experimental part, an attempt will be made to find the best classifier and to improve the quality of the original data set to obtain the highest values of classification quality measures for a particular data set.
</abstract>

Classification methods in the diagnosis of breast cancer

<abstract xmlns="http://www.w3.org/1999/xhtml">

We compared two of the most common methods for differential expression analysis in the RNA-seq field: edgeR and DESeq2. We evaluated these methods based on four real RNA-seq plant datasets. The results indicate that there is a large number of joint differentially expressed genes between the two methods. However, depending on the research goal and the preparation of an experiment, different approaches to statistical analysis and interpretation of the results can be suggested. We focus on answering the question: what workflow should be used in the statistical analysis of the datasets under consideration to minimize the number of falsely identified differentially expressed genes?
</abstract>

Application of edgeR and DESeq2 methods in plant experiments based on RNA-seq technology

<abstract xmlns="http://www.w3.org/1999/xhtml">

In this paper, some multivariate and double multivariate modelling approaches are presented. Moreover, this article provides an overview of the modelling of the structure of the covariance matrix. Furthermore, some methods of covariance structure identification are given.
</abstract>

Structures of the covariance matrix: An overview

<abstract xmlns="http://www.w3.org/1999/xhtml">

Linearly structured covariance matrices are widely used in multivariate analysis. The covariance structure can be chosen from a class of linear structures. Therefore, the optimal structure is identified in terms of minimizing the discrepancy function. In this research, the entropy loss function is used as the discrepancy function. We give a methodology and algorithm for determining the optimal structure from the class of structures under consideration. The accuracy of the proposed method is checked using a simulation study.
</abstract>

Structure identification for a linearly structured covariance matrix

<abstract xmlns="http://www.w3.org/1999/xhtml">

The Faculty of Agronomy at the University of Life Sciences in Poznań conducted laboratory tests on the content of B vitamins in the grain of three varieties of yellow-colored fodder maize. The grains of the variety ES Metronom had the statistically significantly highest content of vitamins B1 and B9. In the case of vitamin B3, the significantly highest concentration was recorded in the grain of the variety ES Abakus, while the lowest concentration was found for the variety ES Metronom. In contrast, the grain of the variety ES Bombastic had significantly higher vitamin B6 content than that of the varieties ES Abakus and ES Metronom. The grain of the variety ES Metronom had significantly higher vitamin B9 content than the other two varieties tested. In general, it should be concluded that the content of B vitamins in maize grain is not determined by the type of maize hybrid.
</abstract>

Department of Mathematical and Statistical Methods

Department of Gastronomical Sciences and Functional Foods

The role of maize variety (<italic>Zea mays</italic> L.) in shaping the grain vitamin content

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Volume 60 (2023): Issue 2 (December 2023)

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Biometrical Letters

 Biometrical Letters is the official journal of the Polish Biometric Society, founded in 1964, now published with the financial support of the Ministry of Science and Higher Education. The anonymous double-blind peer review by the two independent reviewers is applied to all the papers.  The purposes of Biometrical Letters are:   publishing papers dealing with various aspects of the analysis and interpretation of results from biometrical experiments, using mathematical and statistical methods;  promoting and extending the use of statistical and mathematical methods in the principal disciplines of life sciences by reporting on the development and application of these methods;  presenting statistical and mathematical tools useful in biometry. Methodological developments should be motivated by interesting problems from life sciences, applied or applicable;  publishing review papers and papers presenting practical use of various methods of data analysis and statistical inference.   The core of most Biometrical Letters articles is statistical inference that sets scientific or policy objectives, motivates methodological development and demonstrates the operation of new methods.  The paper should include a description of the biometrical problem and a section detailing the application of the new methodology.  The Journal welcomes the submission of manuscripts from bioscience, mathematical and statistical theory, biology, genetics, medical statistics, agriculture, forestry, ecology, environmental sciences, biometrics and clinical trials. Case studies and articles on the use and development of statistical software are also welcome.  Rejection Rate   20%   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 