Comparison of bioinspired algorithms applied to cancer database

Cancer is not just a disease; it is a set of diseases. Breast cancer is the second most common cancer worldwide after lung cancer, and it represents the most frequent cause of cancer death in women (Thurtle et al. in: PLoS Med 16(3):e1002758, 2019, 1]). If it is diagnosed at an early age, the chances of survival are greater. The objective of this research is to compare the performance of method predictions: (i) Logistic Regression, (ii) K-Nearest Neighbor, (iii) K-means, (iv) Random Forest, (v) Support Vector Machine, (vi) Linear Discriminant Analysis, (vii) Gaussian Naive Bayes, and (viii) Multilayer Perceptron within a cancer database

High resolution imaging reveals heterogeneity in chromatin states between cells that is not inherited through cell division

BACKGROUND: Genomes of eukaryotes exist as chromatin, and it is known that different chromatin states can influence gene regulation. Chromatin is not a static structure, but is known to be dynamic and vary between cells. In order to monitor the organisation of chromatin in live cells we have engineered fluorescent fusion proteins which recognize specific operator sequences to tag pairs of syntenic gene loci. The separation of these loci was then tracked in three dimensions over time using fluorescence microscopy. RESULTS: We established a work flow for measuring the distance between two fluorescently tagged, syntenic gene loci with a mean measurement error of 63 nm. In general, physical separation was observed to increase with increasing genomic separations. However, the extent to which chromatin is compressed varies for different genomic regions. No correlation was observed between compaction and the distribution of chromatin markers from genomic datasets or with contacts identified using capture based approaches. Variation in spatial separation was also observed within cells over time and between cells. Differences in the conformation of individual loci can persist for minutes in individual cells. Separation of reporter loci was found to be similar in related and unrelated daughter cell pairs. CONCLUSIONS: The directly observed physical separation of reporter loci in live cells is highly dynamic both over time and from cell to cell. However, consistent differences in separation are observed over some chromosomal regions that do not correlate with factors known to influence chromatin states. We conclude that as yet unidentified parameters influence chromatin configuration. We also find that while heterogeneity in chromatin states can be maintained for minutes between cells, it is not inherited through cell division. This may contribute to cell-to-cell transcriptional heterogeneity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12860-016-0111-y) contains supplementary material, which is available to authorized users

Synthetic Cathinones—Prevalence and Motivations for Use

This book chapter reviews the prevalence and motivations for use of synthetic cathinones with respect to their availability, legal status, numbers and seized amounts

Genome-Wide Distribution of RNA-DNA Hybrids Identifies RNase H Targets in tRNA Genes, Retrotransposons and Mitochondria

During transcription, the nascent RNA can invade the DNA template, forming extended RNA-DNA duplexes (R-loops). Here we employ ChIP-seq in strains expressing or lacking RNase H to map targets of RNase H activity throughout the budding yeast genome. In wild-type strains, R-loops were readily detected over the 35S rDNA region, transcribed by Pol I, and over the 5S rDNA, transcribed by Pol III. In strains lacking RNase H activity, R-loops were elevated over other Pol III genes, notably tRNAs, SCR1 and U6 snRNA, and were also associated with the cDNAs of endogenous TY1 retrotransposons, which showed increased rates of mobility to the 5'-flanking regions of tRNA genes. Unexpectedly, R-loops were also associated with mitochondrial genes in the absence of RNase H1, but not of RNase H2. Finally, R-loops were detected on actively transcribed protein-coding genes in the wild-type, particularly over the second exon of spliced ribosomal protein genes