39 research outputs found
In silico estimation of annealing specificity of query searches in DNA databases
No full textWe consider DNA implementations of databases for digital signals with retrieval and mining capabilities. Digital signals are encoded in DNA sequences and retrieved through annealing between query DNA primers and data carrying DNA target sequences. The hybridization between query and target can be non-specific containing multiple mismatches thus implementing similarity-based searches. In this paper we examine theoretically and by simulation the efficiency of such a system by estimating the concentrations of query-target duplex formations at equilibrium. A coupled kinetic model is used to estimate the concentrations. We offer a derivation that results in an equation that is guaranteed to have a solution and can be easily and accurately solved computationally with bi-section root-finding methods. Finally, we also provide an approximate solution at dilute query concentrations that results in a closed form expression. This expression is used to improve the speed of the bi-section algorithm and also to find a closed form expression for the specificity ratios
Epigenetic chromatin modifiers in barley: IV. The study of barley Polycomb group (PcG) genes during seed development and in response to external ABA
No full textAbstract Background Epigenetic phenomena have been associated with the regulation of active and silent chromatin states achieved by modifications of chromatin structure through DNA methylation, and histone post-translational modifications. The latter is accomplished, in part, through the action of PcG (Polycomb group) protein complexes which methylate nucleosomal histone tails at specific sites, ultimately leading to chromatin compaction and gene silencing. Different PcG complex variants operating during different developmental stages have been described in plants. In particular, the so-called FIE/MEA/FIS2 complex governs the expression of genes important in embryo and endosperm development in Arabidopsis. In our effort to understand the epigenetic mechanisms regulating seed development in barley (Hordeum vulgare), an agronomically important monocot plant cultivated for its endosperm, we set out to characterize the genes encoding barley PcG proteins. Results Four barley PcG gene homologues, named HvFIE, HvE(Z), HvSu(z)12a, and HvSu(z)12b were identified and structurally and phylogenetically characterized. The corresponding genes HvFIE, HvE(Z), HvSu(z)12a, and HvSu(z)12b were mapped onto barley chromosomes 7H, 4H, 2H and 5H, respectively. Expression analysis of the PcG genes revealed significant differences in gene expression among tissues and seed developmental stages and between barley cultivars with varying seed size. Furthermore, HvFIE and HvE(Z) gene expression was responsive to the abiotic stress-related hormone abscisic acid (ABA) known to be involved in seed maturation, dormancy and germination. Conclusion This study reports the first characterization of the PcG homologues, HvFIE, HvE(Z), HvSu(z)12a and HvSu(z)12b in barley. All genes co-localized with known chromosomal regions responsible for malting quality related traits, suggesting that they might be used for developing molecular markers to be applied in marker assisted selection. The PcG differential expression pattern in different tissues and seed developmental stages as well as in two barley cultivars with different seed size is suggestive of a role for these genes in barley seed development. HvFIE and HvE(Z) were also found to be induced by the plant hormone ABA implying an association with ABA-mediated processes during seed development, germination and stress response.</p
Causal deep learning on images
No full textUnderstanding cause-effect relationships is paramount in data-driven decision-making. Causality offers tools to investigate how systems react to interventions, such as predicting outcomes following treatments. Quantifying intervention effects enables actionable, robust decisions, even with confounding factors. However, foundational causality studies focus on low-dimensional data and linear relationships. Deriving causal insights from high-dimensional and unstructured data, like images, audio, text, or genomics, remains challenging due to the complexity of these relationships. Conversely, deep learning has shown success in predictive tasks over high-dimensional data. Deep learning uses multiple layers of neural networks to process information. Traditional deep learning does not understand causal relationships, resulting in failure modes due to biases and domain shifts.
This thesis merges concepts from causality and deep learning to overcome the main weaknesses of each field. The aim is to facilitate robust decision-making using high-dimensional and unstructured data. We divide causal deep learning into three main areas of research: (1) causal reasoning, analysing system reactions to interventions with known variable relationships; (2) causal discovery, identifying these relationships given a set of variables; and (3) causal representation learning, utilising causal techniques to enhance deep representations. The main contributions involve using neural networks trained via the score of distributions (or denoising diffusion) for processing high-dimensional variables.
We apply our methods to medical imaging where possible. In healthcare, understanding high-dimensional causal relationships is vital. Our techniques enable lesion localisation in brain scans, creating synthetic images without biases, understanding causal structures in high-dimensional datasets, and learning of causally ordered latent spaces. This thesis merges causality with deep learning, unlocking robust decision-making for high-dimensional data
Τhe Role of a Gibberellin 20-Oxidase Gene in Fruit Development in Pepper (Capsicum annuum)
No full text
Multiple evidence for the role of an <it>Ovate</it>-like gene in determining fruit shape in pepper
No full textAbstract Background Grafting is a widely used technique contributing to sustainable and ecological production of many vegetables, but important fruit quality characters such as taste, aroma, texture and shape are known for years to be affected by grafting in important vegetables species including pepper. From all the characters affected, fruit shape is the most easily observed and measured. From research in tomato, fruit shape is known to be controlled by many QTLs but only few of them have larger effect on fruit shape variance. In this study we used pepper cultivars with different fruit shape to study the role of a pepper Ovate-like gene, CaOvate, which encodes a negative regulator protein that brings significant changes in tomato fruit shape. Results We successfully cloned and characterized Ovate-like genes (designated as CaOvate) from two pepper cultivars of different fruit shape, cv. "Mytilini Round" and cv. "Piperaki Long", hereafter referred to as cv. "Round" and cv. "Long" after the shape of their mature fruits. The CaOvate consensus contains a 1008-bp ORF, encodes a 335 amino-acid polypeptide, shares 63% identity with the tomato OVATE protein and exhibits high similarity with OVATE sequences from other Solanaceae species, all placed in the same protein subfamily as outlined by expert sequence analysis. No significant structural differences were detected between the CaOvate genes obtained from the two cultivars. However, relative quantitative expression analysis showed that the expression of CaOvate followed a different developmental profile between the two cultivars, being higher in cv. "Round". Furthermore, down-regulation of CaOvate through VIGS in cv. "Round" changes its fruit to a more oblong form indicating that CaOvate is indeed involved in determining fruit shape in pepper, perhaps by negatively affecting the expression of its target gene, CaGA20ox1, also studied in this work. Conclusions Herein, we clone, characterize and study CaOvate and CaGA20ox1 genes, very likely involved in shaping pepper fruit. The oblong phenotype of the fruits in a plant of cv. "Round", where we observed a significant reduction in the expression levels of CaOvate, resembled the change in shape that takes place by grafting the round-fruited cultivar cv. "Round" onto the long-fruited pepper cultivar cv. "Long". Understanding the role of CaOvate and CaGA20ox1, as well as of other genes like Sun also involved in controlling fruit shape in Solanaceae plants like tomato, pave the way to better understand the molecular mechanisms involved in controlling fruit shape in Solanaceae plants in general, and pepper in particular, as well as the changes in fruit quality induced after grafting and perhaps the ways to mitigate them.</p
Sequence Characterization and Expression Analysis of Three APETALA2-like Genes from Saffron Crocus
No full textEPIGENETIC MODIFICATIONS IN MAIZE PARENTAL INBREDS AND HYBRIDS AND THEIR RELATIONSHIP TO HYBRID VIGOR AND STABILITY
No full textRolling circle amplification-RACE: a method for simultaneous isolation of 5′ and 3′ cDNA ends from amplified cDNA templates
No full text
