Global, highly specific and fast filtering of alignment seeds.

BACKGROUND: An important initial phase of arguably most homology search and alignment methods such as required for genome alignments is seed finding. The seed finding step is crucial to curb the runtime as potential alignments are restricted to and anchored at the sequence position pairs that constitute the seed. To identify seeds, it is good practice to use sets of spaced seed patterns, a method that locally compares two sequences and requires exact matches at certain positions only. RESULTS: We introduce a new method for filtering alignment seeds that we call geometric hashing. Geometric hashing achieves a high specificity by combining non-local information from different seeds using a simple hash function that only requires a constant and small amount of additional time per spaced seed. Geometric hashing was tested on the task of finding homologous positions in the coding regions of human and mouse genome sequences. Thereby, the number of false positives was decreased about million-fold over sets of spaced seeds while maintaining a very high sensitivity. CONCLUSIONS: An additional geometric hashing filtering phase could improve the run-time, accuracy or both of programs for various homology-search-and-align tasks.

On the use of contrastive learning for standard-plane classification in fetal ultrasound imaging.

BACKGROUND: To investigate the effectiveness of contrastive learning, in particular SimClr, in reducing the need for large annotated ultrasound (US) image datasets for fetal standard plane identification. METHODS: We explore SimClr advantage in the cases of both low and high inter-class variability, considering at the same time how classification performance varies according to different amounts of labels used. This evaluation is performed by exploiting contrastive learning through different training strategies. We apply both quantitative and qualitative analyses, using standard metrics (F1-score, sensitivity, and precision), Class Activation Mapping (CAM), and t-Distributed Stochastic Neighbor Embedding (t-SNE). RESULTS: When dealing with high inter-class variability classification tasks, contrastive learning does not bring a significant advantage; whereas it results to be relevant for low inter-class variability classification, specifically when initialized with ImageNet weights. CONCLUSIONS: Contrastive learning approaches are typically used when a large number of unlabeled data is available, which is not representative of US datasets. We proved that SimClr either as pre-training with backbone initialized via ImageNet weights or used in an end-to-end dual-task may impact positively the performance over standard transfer learning approaches, under a scenario in which the dataset is small and characterized by low inter-class variability.

The macronuclear genome of the Antarctic psychrophilic marine ciliate Euplotes focardii reveals new insights on molecular cold adaptation.

The macronuclear (MAC) genomes of ciliates belonging to the genus Euplotes species are comprised of numerous small DNA molecules, nanochromosomes, each typically encoding a single gene. These genomes are responsible for all gene expression during vegetative cell growth. Here, we report the analysis of the MAC genome from the Antarctic psychrophile Euplotes focardii. Nanochromosomes containing bacterial sequences were not found, suggesting that phenomena of horizontal gene transfer did not occur recently, even though this ciliate species has a substantial associated bacterial consortium. As in other euplotid species, E. focardii MAC genes are characterized by a high frequency of translational frameshifting. Furthermore, in order to characterize differences that may be consequent to cold adaptation and defense to oxidative stress, the main constraints of the Antarctic marine microorganisms, we compared E. focardii MAC genome with those available from mesophilic Euplotes species. We focussed mainly on the comparison of tubulin, antioxidant enzymes and heat shock protein (HSP) 70 families, molecules which possess peculiar characteristic correlated with cold adaptation in E. focardii. We found that α-tubulin genes and those encoding SODs and CATs antioxidant enzymes are more numerous than in the mesophilic Euplotes species. Furthermore, the phylogenetic trees showed that these molecules are divergent in the Antarctic species. In contrast, there are fewer hsp70 genes in E. focardii compared to mesophilic Euplotes and these genes do not respond to thermal stress but only to oxidative stress. Our results suggest that molecular adaptation to cold and oxidative stress in the Antarctic environment may not only be due to particular amino acid substitutions but also due to duplication and divergence of paralogous genes.