The epigenetics methylation of cytosine is the most common epigenetic form in DNA sequences. It is highly concentrated in the promoter regions of the genes, leading to an inactivation of tumor suppressors regardless of their initial function. In this work, we aim to identify the highly methylated regions; the cytosine-phosphate-guanine (CpG) island located on the promoters and/or the first exon gene known for their key roles in the cell cycle, hence the need to study gene-gene interactions. The Frommer and hidden Markov model algorithms are used as computational methods to identify CpG islands with specificity and sensitivity up to 76% and 80%, respectively. The results obtained show, on the one hand, that the genes studied are suspected of developing hypermethylation in the promoter region of the gene involved in the case of a cancer. We then showed that the relative richness in CG results from a high level of methylation. On the other hand, we observe that the gene-gene interaction exhibits co-expression between the chosen genes. This let us to conclude that the hidden Markov model algorithm predicts more specific and valuable information about the hypermethylation in gene as a preventive and diagnostics tools for the personalized medicine; as that the tumor-suppresser-genes have relative co-expression and complementary relations which the hypermethylation affect in the samples studied in our work.
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http://dx.doi.org/10.1016/j.gene.2018.01.082 | DOI Listing |
PLoS One
January 2025
Center for Innovation in Brain Science, University of Arizona Health Sciences, Tucson, Arizona, United States of America.
Translational validity of mouse models of Alzheimer's disease (AD) is variable. Because change in weight is a well-documented precursor of AD, we investigated whether diversity of human AD risk weight phenotypes was evident in a longitudinally characterized cohort of 1,196 female and male humanized APOE (hAPOE) mice, monitored up to 28 months of age which is equivalent to 81 human years. Autoregressive Hidden Markov Model (AHMM) incorporating age, sex, and APOE genotype was employed to identify emergent weight trajectories and phenotypes.
View Article and Find Full Text PDFMar Drugs
December 2024
Biotechnology Unit, University of Ribeirão Preto/UNAERP, Ribeirão Preto 14096-900, SP, Brazil.
Lectins are non-covalent glycan-binding proteins found in all living organisms, binding specifically to carbohydrates through glycan-binding domains. Lectins have various biological functions, including cell signaling, molecular recognition, and innate immune responses, which play multiple roles in the physiological and developmental processes of organisms. Moreover, their diversity enables biotechnological exploration as biomarkers, biosensors, drug-delivery platforms, and lead molecules for anticancer, antidiabetic, and antimicrobial drugs.
View Article and Find Full Text PDFMicroscopy (Oxf)
January 2025
The Ultramicroscopy Research Center, Kyushu University, 744 Motooka, Fukuoka 819-0395, Japan.
The precision in electron holography studies on electrostatic and magnetic fields depends on the image quality of an electron hologram. Enhancing the image quality of electron holograms is essential for the comprehensive analysis of weak electromagnetic fields; however, extended electron beam irradiation can lead to undesirable radiation damage and contamination. Recent studies have demonstrated that noise reduction using the wavelet hidden Markov model (WHMM) can improve the precision of phase analysis for limited thin-foiled crystals.
View Article and Find Full Text PDFElife
January 2025
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University & IDG/McGovern Institute for Brain Research, Beijing, China.
Speech comprehension involves the dynamic interplay of multiple cognitive processes, from basic sound perception, to linguistic encoding, and finally to complex semantic-conceptual interpretations. How the brain handles the diverse streams of information processing remains poorly understood. Applying Hidden Markov Modeling to fMRI data obtained during spoken narrative comprehension, we reveal that the whole brain networks predominantly oscillate within a tripartite latent state space.
View Article and Find Full Text PDFLight Sci Appl
January 2025
Spin-Optics laboratory, St. Petersburg State University, St. Petersburg, 198504, Russia.
We introduce a novel neuromorphic network architecture based on a lattice of exciton-polariton condensates, intricately interconnected and energized through nonresonant optical pumping. The network employs a binary framework, where each neuron, facilitated by the spatial coherence of pairwise coupled condensates, performs binary operations. This coherence, emerging from the ballistic propagation of polaritons, ensures efficient, network-wide communication.
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