The article analyzes various clustering approaches that are used in gene expression tasks. The chosen approaches are portrayed and examined from the viewpoint of use of data mining clustering algorithms. The article provides a short description of working principles and characteristics of the examined methods and algorithms and the data sets used in the experiments. The article presents results of the experiments that are directly connected to the use of clustering algorithms in processing of short time series in bioinformatics tasks, solving gene expression problems, as well as provides conclusions and evaluations of each used approach. An analysis of future possibilities to build a new method that is based on data mining approaches and principles but solves bioinformatics tasks that are associated with processing of short time series and the achieved results are interpreted in a way that is easy to perceive for bioinformatics experts, is presented.