Physical Attributes of Anisotropic Compact Stars in f(R,G)f(R,G) Gravity

Modified gravity is one of the potential candidates to explain the accelerated expansion of the universe. Current study highlights the materialization of anisotropic compact stars in the context of $f(R,G)$ theory of gravity. In particular, to gain insight in the physical behavior of three stars namely, Her $X1$, SAX J $1808$-$3658$ and 4U $1820$-$30$, energy density, and radial and tangential pressures are calculated. The $f(R,G)$ gravity model is split into a Starobinsky like $f(R)$ model and a power law $f(G)$ model. The main feature of the work is a $3$-dimensional graphical analysis in which, anisotropic measurements, energy conditions and stability attributes of these stars are discussed. It is shown that all three stars behave as usual for positive values of $f(G)$ model parameter $n$.Comment: 21 pages, revised version, to appear in EPJ

Mathematical Understanding of Sequence Alignment and Phylogenetic Algorithms: A Comprehensive Review of Computation of Different Methods

Pairwise sequence alignment is one of the ways to position two biological sequences to identify regions of similarity that may suggest the functional, structural and evolutionary relationship among proteins and nucleic acids. There are two strategies in pairwise alignment: local sequence alignment (Smith Waterman algorithm) and global sequence alignment (Needleman Wunsch algorithm). In the prior approach, two sequences that may or may not be related, are aligned to find regions of local similarities in large sequences, whereas in the later one, two sequences of same length are aligned to identify their conserved regions. Moreover, similarities and divergence between biological sequences also has to be rationalized and visualized in the form of phylogenetic trees, so the dendrogram construction approaches were developed and divided into distance-based and character-based methods. In this review article, different algorithms of sequence alignment and phylogenetic tree construction were meditated with examples and compared by looking into the background computation for the better understanding of the algorithms, which will be helpful for molecular biology, computational sciences and mathematics/statistics novices. Phylogenetic trees are constructed through various methods, some are computationally robust but does not provide precise evolutionary insight, whereas some provide accurate evolutionary understandings, but computationally exhaustive and cumbersome. So, there is a need to understand the implicit mathematics and intricate computation behind the dendrogram construction for improving the existing algorithms and developing new methods.  Keywords: Local sequence alignment; Global sequence alignment; UPGMA; Neighbour joining; Fitch Margoliash; Maximum-Parsimony; Maximum-Likelihood  

First Step with R for Life Sciences: Learning Basics of this Tool for NGS Data Analysis

Background: R is one of the renowned programming language which is an open source software developed by the scientific community to compute, analyze and visualize big data of any field including biomedical research for bioinformatics applications.Methods: Here, we outlined R allied packages and affiliated bioinformatics infrastructures e.g. Bioconductor and CRAN. Moreover, basic concepts of factor, vector, data matrix and whole transcriptome RNA-Seq data was analyzed and discussed. Particularly, differential expression workflow on simulated prostate cancer RNA-Seq data was performed through experimental design, data normalization, hypothesis testing and downstream investigations using EdgeR package. A few genes with ectopic expression were retrieved and knowhow to gene enrichment pathway analysis is highlighted using available online tools.Results: Data matrix of (4×3) was constructed, and a complex data matrix of Golub et al., was analyzed through χ2 statistics by generating a frequency table of 15 true positive, 4 false positive, 15 true negative and 4 false negative on gene expression cut-off values, and a test statistics value of 10.52 with 1 df and p= 0.001 was obtained, which reject the null hypothesis and supported the alternative hypothesis of “predicted state of a person by gene expression cut-off values is dependent on the disease state of patient” in our data. Similarly, sequence data of human Zyxingene was selected and a null hypothesis of equal frequencies was rejected.Conclusion: Machine-learning approaches using R statistical package is a supportive tool which can provide systematic prediction of putative causes, present state, future consequences and possible remedies of any problem of modern biology.Keywords: NGS data; R language; Zyxin gen

Insight of Tp53 Mutations and their effect on Protein in Different Feline and Canine Neoplasms

Background: Mutations in the Tp53 gene, a tumor suppressor gene, may cause dysfunction in growing cells and hinder the phenomenon of apoptosis, an alleged cause of tumorigenesis. It is involved in conservation of the genome and DNA repair, mutations of this gene may cause the damaged cells to grow continuously.Methods: The type of molecular changes in Tp53 gene and their effects on physiochemical and structural properties of this protein in various Canine and Feline cancers were observed in this study by using online bioinformatics tools.Results: Our results indicated that lymphomas and perianal adenocarcinomas (PAC) have the same mutation at c. 104, while mammary tumors and canine transmissible venereal tumor (CTVT) contain different mutations. Referring to changes in protein, synonymous mutations in granulomas were observed while certain mutations in squamous cell carcinoma (SCC) and head & neck tumors were detected in Canis familiaris. In Felis catus, the mutant protein was similar to wild type protein with exception of mutant 5 of mammary tumor, which had a deletion at the 287 amino acid position.Conclusion: The insight gathered on the p53 mutant proteins in both species aided our understanding of the in-vivo fate of the p53 protein and its isoforms and the effects that morphological changes can have on the fate of cells. Furthermore, isolation of this protein may augment our understanding about the structural biology of these proteins

Gravastars in f(R, G) gravity

This paper is focused on the study of gravitational vacuum stars or, briefly, gravastars in f(R, G) gravity, where R and G stand for the Ricci scalar and Gauss–Bonnet invariant term, respectively. Due to the involvement of highly non-linear differential equations, solutions are found by using some appropriate numerical techniques. The main structure of gravastars has been discussed according to core, shell, and exterior regions for a well-known f(R, G) gravity cosmological model. Mass–radius evolution is described graphically for the considered gravastar, and it is shown that the mass is directly proportional to the radius.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

A study of some cylindrically symmetric solutions in f(R, G) gravity

In this paper, we present the cylindrically symmetric solutions in a well-known modified theory, namely f(R, G) gravity. After driving the complete system of field equations, six different families of exact solutions using a viable f(R, G) gravity model have been discussed. Moreover, we have investigated the well-known Levi–Civita solution in modified gravity for the model f(R, G) = R2 + αGn for some suitable values of model parameters n and α. Null energy conditions are also calculated for all the obtained solutions. Some regions are observed where the null energy condition is violated, indicating the existence of cylindrical wormholes.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author