Selection of informative genes is an important problem in gene expression studies. The small sample size and the large number data make selection process complex. Further, selected may act as a vital input for co-expression network analysis. Moreover, identification hub module interactions networks yet to be fully explored. This paper presents statistically sound technique based on support vector machine algorithm selecting from high dimensional data. Also, attempt has been made develop...

Molecular epidemiology of Foot-and-mouth disease (FMD) is crucial to implement its control strategies including vaccination and containment, which primarily deals with knowing serotype, topotype, lineage the virus. The existing approaches serotyping are biological in nature, time-consuming risky due live virus handling. Thus, novel computational tools highly required for large-scale molecular FMD This study reported a comprehensive tool epidemiology. Ten learning algorithms were initially...

Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput sequencing technique for studying gene expressions at the cell level. Differential Expression (DE) analysis major downstream of scRNA-seq data. DE in presence noises from different sources remains key challenge scRNA-seq. Earlier practices addressing this involved borrowing methods bulk RNA-seq, which are based on non-zero differences average genes across populations. Later, several specifically designed were developed. To...

Early detection of lung cancer is a crucial factor for increasing its survival rates among the detected patients. The presence carbonyl volatile organic compounds (VOCs) in exhaled breath can play vital role early cancer. Identifying these VOC markers samples through innovative statistical and machine learning techniques an important task research. Therefore, we proposed experimental approach generation molecular concentration data using unique silicon microreactor technology further...

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that capable of generating gene expression data at the resolution individual cell. The scRNA-seq characterized by presence dropout events, which severely bias results if they remain unaddressed. There are limited Differential Expression (DE) approaches consider biological processes, lead to in modeling process. So, we develop, SwarnSeq, an improved method for DE, and other downstream analysis considers molecular capture process...

Background: Three serotypes of Foot-and-mouth disease (FMD) virus have been circulating in Asia, which are commonly identified by serological assays. Such tests timeconsuming and also need a bio-containment facility for execution. To the best our knowledge, no computational solution is available literature to predict FMD serotypes. Thus, this necessitates urgent user-friendly tools serotyping. Methods: We presented based on machine-learning model classification serotype prediction. Besides,...

The onset of dementia is after 65 years. Though there are evidence reported in the past regarding before this age, it very rare. Studies carried out have concentrated on site lesion, genetic base for young and studies focusing cognitive linguistic profiling extremely current study focussed effect activities daily living. findings suggested that deficit was severe had a note-worthy impact This pivotal designing plan intervention deciding course treatment.

Abstract The analysis of gene sets is usually carried out based on ontology terms and known biological pathways. These approaches may not establish any formal relation between genotype trait specific phenotype. In plant biology breeding, with Quantitative Trait Loci (QTL) data are considered as great source for knowledge discovery. Therefore, we proposed an innovative statistical approach called Gene Set Analysis QTLs (GSAQ) interpreting expression in context traits. utility GSAQ was studied...

Selection of biologically relevant genes from high-dimensional expression data is a key research problem in gene genomics. Most the available selection methods are either based on relevancy or redundancy measure, which usually adjudged through post classification accuracy. Through these ranking was conducted single data, led to spuriously associated and redundant genes. Hence, we developed statistical approach combining support vector machine with Maximum Relevance Minimum Redundancy under...

Abstract Foot-and-mouth disease (FMD) is a severe contagious viral of cloven-hoofed animals. In India, vaccination-based official FMD control programme was started, which got expanded progressively to cover entire country in 2019. The serological tests are used determine non-structural protein based sero-prevalence rates for properly implementing and assessing the programme. Since 2008, reporting sero-surveillance limited serum sample-based test results without going population-level...

Selection of biologically relevant genes from high dimensional expression data is a key research problem in gene genomics. Most the available selection methods are either based on relevancy or redundancy measure, which usually adjudged through post classification accuracy. Through these ranking was done single high-dimensional data, leads to spuriously associated and redundant genes. Hence, we developed statistical approach combining Support Vector Machine with Maximum Relevance Minimum...

Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput genomic technology used to study the expression dynamics of genes at single-cell level. Analyzing scRNA-seq data in presence biological confounding factors including dropout events challenging task. Thus, this article presents novel statistical approach for various analyses Unique Molecular Identifier (UMI) counts data. The include modeling and fitting observed UMI data, cell type detection, estimation capture rates, gene...

Single-cell RNA-sequencing (scRNA-seq) technology provides an excellent platform for measuring the expression profiles of genes in heterogeneous cell populations. Multiple tools analysis scRNA-seq data have been developed over years. The require complicated commands and steps to analyze underlying data, which are not easy follow by genome researchers experimental biologists. Therefore, we describe a step-by-step workflow processing analyzing unique molecular identifier (UMI) from Human Lung...