Diatom contour analysis using morphological curvature scale spaces

A method for shape analysis of diatoms (single-cell algae with silica shells) based on extraction of features on the contour of the cells by multi-scale mathematical morphology is presented. After building a morphological contour curvature scale space, we present a method for extracting the most prominent features by unsupervised cluster analysis. The number of extracted features matches well with those found visually in 92 % of the 350 diatom images examined

Building shape and texture models of diatoms for analysis and synthesis of drawings and identification

We describe tools for automatic identification of diatoms by comparing their photographs with other photographs and drawings, via a model. Identification of diatoms, i.e. assigning a new specimen to one of the known species, has applications in many disciplines, including ecology, paleoecology and forensic science. The model we build represents life cycle and natural variation of both external shape and internal texture over multiple species and is based on principal curves. The model is also suitable for automatically producing drawings of diatoms at any stage of their life cycle development. Similar drawings are traditionally used for diatom identification, and encapsulate visually salient diatom features. In this article we describe the methods used to analyse photographs and drawings, present our model of diatom shape and texture variation, and illustrate our approach with a collection of drawings synthesised from our model and derived from example photographs. Finally, we present the results of identification experiments using photographs and drawings

Combinatorial CRISPR screen identifies fitness effects of gene paralogues.

Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. Our studies reveal the fitness effects of FAM50A/FAM50B in cancer cells