scholarly journals Genomic Abelian Finite Groups

2021 ◽  
Author(s):  
Robersy Sanchez ◽  
Jesus Barreto

Experimental studies reveal that genome architecture splits into natural domains suggesting a well-structured genomic architecture, where, for each species, genome populations are integrated by individual mutational variants. Herein, we show that the architecture of population genomes from the same or closed related species can be quantitatively represented in terms of the direct sum of homocyclic abelian groups defined on the genetic code, where populations from the same species lead to the same canonical decomposition into p -groups.  This finding unveils a new ground for the application of the abelian group theory to genomics and epigenomics, opening new horizons for the study of the biological processes (at genomic scale) and provides new lens for genomic medicine.

2008 ◽  
Vol 33 (2) ◽  
pp. 139-147 ◽  
Author(s):  
Chunxiang Zhang

Genomic evidence reveals that gene expression in humans is precisely controlled in cellular, tissue-type, temporal, and condition-specific manners. Completely understanding the regulatory mechanisms of gene expression is therefore one of the most important issues in genomic medicine. Surprisingly, recent analyses of the human and animal genomes have demonstrated that the majority of RNA transcripts are relatively small, noncoding RNAs (sncRNAs), rather than large, protein coding message RNAs (mRNAs). Moreover, these sncRNAs may represent a novel important layer of regulation for gene expression. The most important breakthrough in this new area is the discovery of microRNAs (miRNAs). miRNAs comprise a novel class of endogenous, small, noncoding RNAs that negatively regulate gene expression via degradation or translational inhibition of their target mRNAs. As a group, miRNAs may directly regulate ∼30% of the genes in the human genome. In keeping with the nomenclature of RNomics, which is to study sncRNAs on the genomic scale, “microRNomics” is coined here to describe a novel subdiscipline of genomics that studies the identification, expression, biogenesis, structure, regulation of expression, targets, and biological functions of miRNAs on the genomic scale. A growing body of exciting evidence suggests that miRNAs are important regulators of cell differentiation, proliferation/growth, mobility, and apoptosis. These miRNAs therefore play important roles in development and physiology. Consequently, dysregulation of miRNA function may lead to human diseases such as cancer, cardiovascular disease, liver disease, immune dysfunction, and metabolic disorders. microRNomics may be a newly emerging approach for human disease biology.


2021 ◽  
Vol 17 (2) ◽  
pp. e1008767
Author(s):  
Zutan Li ◽  
Hangjin Jiang ◽  
Lingpeng Kong ◽  
Yuanyuan Chen ◽  
Kun Lang ◽  
...  

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA’s biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.


1961 ◽  
Vol 13 ◽  
pp. 192-200 ◽  
Author(s):  
Christine W. Ayoub

In this paper we consider again the group-theoretic configuration studied in (1) and (2). Let G be an additive group (not necessarily abelian), let M be a system of operators for G, and let ϕ be a family of admissible subgroups which form a complete lattice relative to intersection and compositum. Under these circumstances we call G an M — ϕ group. In (1) we studied the normal chains for an M — ϕ group and the relation between certain normal chains. In (2) we considered the possibility of representing an M — ϕ group as the direct sum of certain of its subgroups, and proved that with suitable restrictions on the M — ϕ group the analogue of the following theorem for finite groups holds: A group is the direct product of its Sylow subgroups if and only if it is nilpotent. Here we show that under suitable hypotheses (hypotheses (I), (II), and (III) stated at the beginning of §3) it is possible to generalize to M — ϕ groups many of the Sylow theorems of classical group theorem.


1991 ◽  
Vol 11 (2) ◽  
pp. 279-307 ◽  
Author(s):  
Gavin Brown ◽  
Anthony H. Dooley

AbstractThe introduction of results from harmonic analysis leads to new methods in the study of the ergodic properties of measures under the action of the direct sum of finite groups. We take the first steps in a systematic development of part of ergodic theory based on the formalism of the Riesz product construction.


1999 ◽  
Vol 52 (5) ◽  
pp. 895 ◽  
Author(s):  
H. Linke

Ratchets are spatially asymmetric devices in which particles can move on average in one direction in the absence of external net forces or gradients. This is made possible by the rectification of fluctuations, which also provide the energy for the process. Interest in the physics of ratchets was revived in recent years when it emerged that the ratchet principle may be a suitable physical model for ‘molecular motors’, which are central to many fundamental biological processes, such as intracellular transport or muscle contraction. Most ratchets studied so far have relied on classical effects, but recently ‘quantum ratchets’, involving quantum effects, have also been studied. In the present article it is pointed out that semiconductor or metal nanostructures are very suitable systems for the realisation of experimental quantum ratchets. Recent experimental studies of a quantum ratchet based on an asymmetric quantum dot are reviewed.


Biomedicines ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 124 ◽  
Author(s):  
Igor Khaliulin ◽  
Maryam Kartawy ◽  
Haitham Amal

Nitric oxide (NO) represents an important signaling molecule which modulates the functions of different organs, including the brain. S-nitrosylation (SNO), a post-translational modification that involves the binding of the NO group to a cysteine residue, is a key mechanism of nitrergic signaling. Most of the experimental studies are carried out on male animals. However, significant differences exist between males and females in the signaling mechanisms. To investigate the sex differences in the SNO-based regulation of biological functions and signaling pathways in the cortices of 6–8-weeks-old mice, we used the mass spectrometry technique, to identify S-nitrosylated proteins, followed by large-scale computational biology. This work revealed significant sex differences in the NO and SNO-related biological functions in the cortices of mice for the first-time. The study showed significant SNO-induced enrichment of the synaptic processes in female mice, but enhanced SNO-related cytoskeletal processes in the male mice. Proteins, which were S-nitrosylated in the cortices of mice of both groups, were more abundant in the female brain. Finally, we investigated the shared molecular processes that were found in both sexes. This study presents a mechanistic insight into the role of S-nitrosylation in both sexes and provides strong evidence of sex difference in many biological processes and signalling pathways, which will open future research directions on sex differences in neurological disorders.


2019 ◽  
Vol 20 (12) ◽  
pp. 2939 ◽  
Author(s):  
Saghafi ◽  
Taheri ◽  
Parkkila ◽  
Emameh

Long non-coding RNAs (lncRNAs) are classified as a group of transcripts which regulate various biological processes, such as RNA processing, epigenetic control, and signaling pathways. According to recent studies, lncRNAs are dysregulated in cancer and play an important role in cancer incidence and spreading. There is also an association between lncRNAs and the overexpression of some tumor-associated proteins, including carbonic anhydrases II, IX, and XII (CA II, CA IX, and CA XII). Therefore, not only CA inhibition, but also lncRNA modulation, could represent an attractive strategy for cancer prevention and therapy. Experimental studies have suggested that herbal compounds regulate the expression of many lncRNAs involved in cancer, such as HOTAIR (HOX transcript antisense RNA), H19, MALAT1 (metastasis-associated lung adenocarcinoma transcript 1), PCGEM1 (Prostate cancer gene expression marker 1), PVT1, etc. These plant-derived drugs or phytochemicals include resveratrol, curcumin, genistein, quercetin, epigallocatechin-3-galate, camptothcin, and 3,3′-diindolylmethane. More comprehensive information about lncRNA modulation via phytochemicals would be helpful for the administration of new herbal derivatives in cancer therapy. In this review, we describe the state-of-the-art and potential of phytochemicals as modulators of lncRNAs in different types of cancers.


2021 ◽  
Vol 76 (1) ◽  
pp. 75-85
Author(s):  
Victoria O. Bitsadze ◽  
Ekaterina V. Slukhanchuk ◽  
Jamilya H. Khizroeva ◽  
Maria V. Tretyakova ◽  
Andrei S. Shkoda ◽  
...  

This article summarizes numerous studies on the relationship of biological processes such as inflammation and thrombosis. The huge role of neutrophils and the extracellular neutrophil traps (NETs) secreted by them has been demonstrated. The discovery of NETs has opened new horizons in the understanding of neutrophil biology and the role of these cells in the body. The use of chromatin in combination with the intracellular proteins, as an effective antimicrobial agent has ancient roots and changes our understanding of chromatin only as a carrier of genetic information. Through NETs, neutrophils can contribute to the development of pathological venous and arterial thrombosis or immunothrombosis, as well as atherosclerosis. NETs release has been shown to be one of the causes of thrombosis in conditions such as sepsis and cancer. The presence of NETs in these diseases and conditions makes it possible to use them or individual components as potential biomarkers. NETs and their components may be attractive as therapeutic targets. Further studies of neutrophils and NETs are needed to develop new approaches to the diagnosis and treatment of inflammatory and thrombotic conditions. Perhaps long-forgotten drugs will find a new area for effective use.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Haochen Zhao ◽  
Linai Kuang ◽  
Lei Wang ◽  
Zhanwei Xuan

Recently, accumulating laboratorial studies have indicated that plenty of long noncoding RNAs (lncRNAs) play important roles in various biological processes and are associated with many complex human diseases. Therefore, developing powerful computational models to predict correlation between lncRNAs and diseases based on heterogeneous biological datasets will be important. However, there are few approaches to calculating and analyzing lncRNA-disease associations on the basis of information about miRNAs. In this article, a new computational method based on distance correlation set is developed to predict lncRNA-disease associations (DCSLDA). Comparing with existing state-of-the-art methods, we found that the major novelty of DCSLDA lies in the introduction of lncRNA-miRNA-disease network and distance correlation set; thus DCSLDA can be applied to predict potential lncRNA-disease associations without requiring any known disease-lncRNA associations. Simulation results show that DCSLDA can significantly improve previous existing models with reliable AUC of 0.8517 in the leave-one-out cross-validation. Furthermore, while implementing DCSLDA to prioritize candidate lncRNAs for three important cancers, in the first 0.5% of forecast results, 17 predicted associations are verified by other independent studies and biological experimental studies. Hence, it is anticipated that DCSLDA could be a great addition to the biomedical research field.


2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Nicola Barbarini ◽  
Luca Simonelli ◽  
Alberto Azzalin ◽  
Sergio Comincini ◽  
Riccardo Bellazzi

Protein interactions are crucial in most biological processes. Several in silico methods have been recently developed to predict them. This paper describes a bioinformatics method that combines sequence similarity and structural information to support experimental studies on protein interactions. Given a target protein, the approach selects the most likely interactors among the candidates revealed by experimental techniques, but not yet in vivo validated. The sequence and the structural information of the in vivo confirmed proteins and complexes are exploited to evaluate the candidate interactors. Finally, a score is calculated to suggest the most likely interactors of the target protein. As an example, we searched for GRB2 interactors. We ranked a set of 46 candidate interactors by the presented method. These candidates were then reduced to 21, through a score threshold chosen by means of a cross-validation strategy. Among them, the isoform 1 of MAPK14 was in silico confirmed as a GRB2 interactor. Finally, given a set of already confirmed interactors of GRB2, the accuracy and the precision of the approach were 75% and 86%, respectively. In conclusion, the proposed method can be conveniently exploited to select the proteins to be experimentally investigated within a set of potential interactors.


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