Natural Language Processing Semantical and Syntactical Analysis for English

Natural language is to facilitate the user to exchange the ideas among people. These ideas converge to form the "meaning" of an utterance or text in the form of a series of sentences. The meaning of sentences describes as semantics. The input/output of a NLP can be a written text or a speech. There are two major components of natural language processing, namely: natural language understanding which describes mapping of given input in the natural language into a useful representation and the other is natural language generation which produce natural language as output on basis of input data as text. This paper deals with natural language understanding mainly on semantic

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Not AvailableRecent outbreak of Coronavirus disease (COVID-19) pandemic around the world is associated with ‘severe acute respiratory syndrome’ (SARS-CoV2) in humans. SARS-CoV2 is an enveloped virus and E proteins present in them are reported to form ion channels, which is mainly associated with pathogenesis. Thus, there is always a quest to inhibit these ion channels, which in turn may help in controlling diseases caused by SARS-CoV2 in humans. Considering this, in the present study, authors employed computational approaches for studying the structure as well as function of the human ‘SARS-CoV2 E’ protein as well as its interaction with various phytochemicals. Result obtained revealed that a-helix and loops present in this protein experience random movement under optimal condition, which in turn modulate ion channel activity; thereby aiding the pathogenesis caused via SARS-CoV2 in human and other vertebrates. However, after binding with Belachinal, Macaflavanone E, and Vibsanol B, the random motion of the human ‘SARS-CoV2 E’ protein gets reduced, this, in turn, inhibits the function of the ‘SARS-CoV2 E’ protein. It is pertinent to note that two amino acids, namely VAL25 and PHE26, play a key role while interacting with these three phytochemicals. As these three phytochemicals, namely, Belachinal, Macaflavanone E & Vibsanol B, have passed the ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) property as well as ‘Lipinski’s Rule of 5s’, they may be utilized as drugs in controlling disease caused via SARS-COV2, after further investigation.Not Availabl

The impact of natural selection on gene associated with panicle number formation in Oryza sativa

Panicle number is directly associated with grain number in rice. As the panicle number increases, it affects the total yield of rice. We examined the evolution of genes associated with panicle number formation in Oryza sativa. Intramural program written in JAVA script and fastPHASE software used for the generation of genotype and haplotype file of SNPs of 11 individual genes associated with panicle number formation utilizing VCF file obtained from RiceCAP project (USDA/CSREES http://www.uark.edu/ua/ricecap/).Tests for natural selection executed on these genes using the Haplotype data. Tajima’s D and Fu Li’s D* analysis were performed using DNASP v4.0. Rates of non-synonymous Vs synonymous changes were calculated according to the dN/dS algorithm of Nei and Gojobori.dN/dS calculation compared with the ancestral (Oryza meridionalis) sequence individually showed that out of 11, almost all genes responsible for grain number formation, Os01g0746400, Os03g0203200, Os03g0706500, Os04g0550600, Os06g0127800, Os06g0154200, Os06g0610350, Os06g0660200, Os08g0162100 and Os11g0528700 are negatively selected throughout evolution., Although Tajima’s D was not found significant, the negative value for 8 genes, Os01g0746400, Os03g0123300, Os03g0706500, Os06g0127800, Os06g0610350, Os06g0660200, Os08g0162100 and Os11g0528700 indicated that  low frequency variants are more in number than high frequency variants. For Fu Li’s D*, the significantly negative values in most of the genes, Os01g0746400, Os03g0123300, Os03g0706500, Os06g0127800, Os06g0610350, Os08g0162100 and Os11g0528700, indicated that the high frequency variants detected through Tajima’s D are predominantly singletons. Thus, result from dN/dS, Tajima’s D and Fu Li indicated that negative (purifying) selection acts on genes responsible for panicle number formation.These results will be useful for further investigation on  how the genes associated with panicle number and how purifying selection result in stabilizing selection through the purging of deleterious variations that arise

In silico identification and characterization of differential expressed genes (DEGs) associated with grain and panicle number in rice

Grain number is an important trait for yield in rice. Several genes have been identified controlling grain and panicle number, which has direct or indirect effect on yield. Some genes play a key role for panicle formation and number of panicles per plant. The number of panicles per plant is directly regulating the grain number per plant. In present study, in silico approach was adopted for identifying differentially expressed genes associated with grain number and panicle number. Further, pathway enrichment analysis of these genes performed. The microarray data, GSE51616, downloaded from the GEO database originally submitted by Wang et al. (2014).Young leaves in vegetative stage (35-days old) and developing panicles (0.1cm) from field-grown OX-Ghd7HJ19 transgenic and wild-type plants with two biological replicates were used to isolate RNA for chip analysis. Background correction and normalization of raw microarray data was carried out using the Robust Multichip Averaging (RMA) method of affy packages of R (v. 3.1.3). The linear regression model package, limma was utilized to classify chips into two groups. The Bayes method (Benjamini and Hochberg) was used to correct for multiple testing. Adjusted P-value < 0.01 and |logFC| > 2 was used as a cut-off to identify differentially expressed genes. We identified 393 differentially expressed genes, which mainly belongs to either Phosphatidylethanolamine-binding protein family or DUF3778 domain family. Proteins of these two families regulate formation of high grain number as well as panicle number. These genes like Ghd7, Ehd1, Dep1, Os10g0463400, Os03g0752800, Os03g0215400, Os06g0157700 and Os06g0157500 function to integrate the dynamic environmental inputs with phase transition, architecture regulation, and stress response to maximize the reproductive success of the rice plant. Thus, these genes can act as potential target protein for increasing grain and panicle number in rice plant, which will lead to increase in yield of rice grain