Screening Cellular Feature Measurements for Image-Based Assay Development

The typical “design” approach to image-based assay development involves choosing measurements that are likely to correlate with the phenotype of interest, based on the researcher’s intuition and knowledge of image analysis. An alternate “screening” approach is to measure a large number of cellular features and systematically test each feature to identify those that are best able to distinguish positive and negative controls while taking precautions to avoid overfitting the available data. The cell measurement software the authors previously developed, CellProfiler, makes both approaches straightforward, easing the process of assay development. Here, they demonstrate the use of the screening approach to image assay development to select the best measures for scoring publicly available image sets of 2 cytoplasm-to-nucleus translocation assays and 2 Transfluor assays. The authors present the resulting assay quality measures as a baseline for future algorithm comparisons, and all software, methods, and images they present are freely available

Enhanced CellClassifier: a multi-class classification tool for microscopy images

BACKGROUND: Light microscopy is of central importance in cell biology. The recent introduction of automated high content screening has expanded this technology towards automation of experiments and performing large scale perturbation assays. Nevertheless, evaluation of microscopy data continues to be a bottleneck in many projects. Currently, among open source software, CellProfiler and its extension Analyst are widely used in automated image processing. Even though revolutionizing image analysis in current biology, some routine and many advanced tasks are either not supported or require programming skills of the researcher. This represents a significant obstacle in many biology laboratories. RESULTS: We have developed a tool, Enhanced CellClassifier, which circumvents this obstacle. Enhanced CellClassifier starts from images analyzed by CellProfiler, and allows multi-class classification using a Support Vector Machine algorithm. Training of objects can be done by clicking directly "on the microscopy image" in several intuitive training modes. Many routine tasks like out-of focus exclusion and well summary are also supported. Classification results can be integrated with other object measurements including inter-object relationships. This makes a detailed interpretation of the image possible, allowing the differentiation of many complex phenotypes. For the generation of the output, image, well and plate data are dynamically extracted and summarized. The output can be generated as graphs, Excel-files, images with projections of the final analysis and exported as variables. CONCLUSION: Here we describe Enhanced CellClassifier which allows multiple class classification, elucidating complex phenotypes. Our tool is designed for the biologist who wants both, simple and flexible analysis of images without requiring programming skills. This should facilitate the implementation of automated high-content screening

Comparative regionalization of Northern Eurasia by woody plants and ground vertebrates

According to the data borrowed from the Biodat base on areas of 536 species of wood plants by means of one of methods of the cluster analysis floristic classification is made and division into districts of Northern Eurasia is executed. Three regions that, in turn, are divided into provinces and districts, are as a result allocated. The border between Southwest and Northeast regions passes diagonally from the northwest on the southeast from the Gulf of Finland of the Baltic Sea to Altai. Such arrangement of border is caused by incomplete postglacial restoration of areas of broad-leaved tree species and modern distinctions in the hydrothermal mode. Considerable similarity of this border with carried out earlier as a result of the similar analysis of fauna of vertebrate animals though on land vertebrata it runs North – from the Kola Peninsula to Baikal is shown. Estimates of communication of variability of communities with various factors of the environment are similar, but usually on land vertebrata they are slightly higher, except for provinciality (35 and 19 % of dispersion). It testifies to more accurate reaction of animals to distinctions in the environment. The exception on provinciality is connected with more coincidence to its accepted gradation on plants (The European, West and East Siberian provinces). It is confirmed by estimates of communication with regionality – division into groups of provinces (regions) that differ on fauna and flora (29 and 38 %) less. The regime explanation of heterogeneity of flora, on the contrary, is slightly fuller, than on fauna (73 and 64 %) though the total assessment on general concepts is approximately identical (80 and 81 % of dispersion)