On Generation of Firewall Log Status Reporter (SRr) Using Perl

Computer System Administration and Network Administration are few such areas where Practical Extraction Reporting Language (Perl) has robust utilization these days apart from Bioinformatics. The key role of a System/Network Administrator is to monitor log files. Log file are updated every day. To scan the summary of large log files and to quickly determine if there is anything wrong with the server or network we develop a Firewall Log Status Reporter (SRr). SRr helps to generate the reports based on the parameters of interest. SRr provides the facility to admin to generate the individual firewall report or all reports in one go. By scrutinizing the results of the reports admin can trace how many times a particular request has been made from which source to which destination and can track the errors easily. Perl scripts can be seen as the UNIX script replacement in future arena and SRr is one development with the same hope that we can believe in. SRr is a generalized and customizable utility completely written in Perl and may be used for text mining and data mining application in Bioinformatics research and development too.Comment: 10Page

Gas Discharge Visualization: An Imaging and Modeling Tool for Medical Biometrics

The need for automated identification of a disease makes the issue of medical biometrics very current in our society. Not all biometric tools available provide real-time feedback. We introduce gas discharge visualization (GDV) technique as one of the biometric tools that have the potential to identify deviations from the normal functional state at early stages and in real time. GDV is a nonintrusive technique to capture the physiological and psychoemotional status of a person and the functional status of different organs and organ systems through the electrophotonic emissions of fingertips placed on the surface of an impulse analyzer. This paper first introduces biometrics and its different types and then specifically focuses on medical biometrics and the potential applications of GDV in medical biometrics. We also present our previous experience with GDV in the research regarding autism and the potential use of GDV in combination with computer science for the potential development of biological pattern/biomarker for different kinds of health abnormalities including cancer and mental diseases

Contextual motivation in physical activity by means of association rule mining

The primary thrust of this work is to demonstrate the applicability of association rule mining in public health domain, focusing on physical activity and exercising. In this paper, the concept of association rule mining is shown assisting to promote the physical exercise as regular human activity. Specifically, similar to the prototypical example of association rule mining, market basket analysis, our proposed novel approach considers two events – exercise (sporadic) and sleep (regular) as the two items of the frequent set; and associating the former, exercise event, with latter, the daily occurring activity sleep at night, helps strengthening the frequency of the exercise patterns. The regularity can further be enhanced, if the exercising instruments are kept in the vicinity of the bed and are within easy reach

Identification of Drought-Responsive Universal Stress Proteins in Viridiplantae

Genes encoding proteins that contain the universal stress protein (USP) domain are known to provide bacteria, archaea, fungi, protozoa, and plants with the ability to respond to a plethora of environmental stresses. Specifically in plants, drought tolerance is a desirable phenotype. However, limited focused and organized functional genomic datasets exist on drought-responsive plant USP genes to facilitate their characterization. The overall objective of the investigation was to identify diverse plant universal stress proteins and Expressed Sequence Tags (ESTs) responsive to water-deficit stress. We hypothesize that cross-database mining of functional annotations in protein and gene transcript bioinformatics resources would help identify candidate drought-responsive universal stress proteins and transcripts from multiple plant species. Our bioinformatics approach retrieved, mined and integrated comprehensive functional annotation data on 511 protein and 1561 ESTs sequences from 161 viridiplantae taxa. A total of 32 drought-responsive ESTs from 7 plant genera Glycine, Hordeum, Manihot, Medicago, Oryza, Pinus and Triticum were identified. Two Arabidopsis USP genes At3g62550 and At3g53990 that encode ATP-binding motif were up-regulated in a drought microarray dataset. Further, a dataset of 80 simple sequence repeats (SSRs) linked to 20 singletons and 47 transcript assembles was constructed. Integrating the datasets on SSRs and drought-responsive ESTs identified three drought-responsive ESTs from bread wheat (BE604157), soybean (BM887317) and maritime pine (BX682209). The SSR sequence types were CAG, ATA and AT respectively. The datasets from cross-database mining provide organized resources for the characterization of USP genes as useful targets for engineering plant varieties tolerant to unfavorable environmental conditions

Aberrantly Expressed Genes in HaCaT Keratinocytes Chronically Exposed to Arsenic Trioxide

Inorganic arsenic is a known environmental toxicant and carcinogen of global public health concern. Arsenic is genotoxic and cytotoxic to human keratinocytes. However, the biological pathways perturbed in keratinocytes by low chronic dose inorganic arsenic are not completely understood. The objective of the investigation was to discover the mechanism of arsenic carcinogenicity in human epidermal keratinocytes. We hypothesize that a combined strategy of DNA microarray, qRT-PCR and gene function annotation will identify aberrantly expressed genes in HaCaT keratinocyte cell line after chronic treatment with arsenic trioxide. Microarray data analysis identified 14 up-regulated genes and 21 down-regulated genes in response to arsenic trioxide. The expression of 4 up-regulated genes and 1 down-regulated gene were confirmed by qRT-PCR. The up-regulated genes were AKR1C3 (Aldo-Keto Reductase family 1, member C3), IGFL1 (Insulin Growth Factor-Like family member 1), IL1R2 (Interleukin 1 Receptor, type 2), and TNFSF18 (Tumor Necrosis Factor [ligand] SuperFamily, member 18) and down-regulated gene was RGS2 (Regulator of G-protein Signaling 2). The observed over expression of TNFSF18 (167 fold) coupled with moderate expression of IGFL1 (3.1 fold), IL1R2 (5.9 fold) and AKR1C3 (9.2 fold) with a decreased RGS2 (2.0 fold) suggests that chronic arsenic exposure could produce sustained levels of TNF with modulation by an IL-1 analogue resulting in chronic immunologic insult. A concomitant decrease in growth inhibiting gene (RGS2) and increase in AKR1C3 may contribute to chronic inflammation leading to metaplasia, which may eventually lead to carcinogenicity in the skin keratinocytes. Also, increased expression of IGFL1 may trigger cancer development and progression in HaCaT keratinocytes

Autism from a Biometric Perspective

Purpose:The aim of this pilot study was to test autistic children, siblings and their parents using a biometric device based on the gas discharge visualization (GDV) technique in order to assess their psycho-emotional and physiological functional state based on the activity of the autonomic nervous system. Hypothesis: We hypothesize that the biometric assessment based on GDV will enable us: (1) to evaluate some specific features associated with autism spectrum disorder (ASD) as well as to compare autistic children to their siblings and to controls; (2) to analyze the differences in individual values of parents of autistic children versus parents of normal children. Results: Out of total of 48 acupuncture points present on ten fingertips of both hands and associated to organs/organ systems, autistic children differed significantly from controls (p < 0.05) in 36 (images without filter) and 12 (images with filter), siblings differed significantly from controls (p < 0.05) in 12 (images without filter) and seven (images with filter), autistic children differed significantly (p < 0.05) from siblings in eight (images without filter) and one (images with filter), fathers of autistic children differed significantly (p < 0.05) from controls in 14 (images without filter) and three (images with filter) and mothers of autistic children differed significantly (p < 0.05) from controls in five (images without filter) and nine (images with filter) acupuncture points. Conclusions: All compared groups have shown significant difference on both psycho-emotional (images without filter) and physiological (images with filter) levels. However, the differences between autistic children and controls expressed on psycho-emotional level were the most significant as compared to the other groups. Therefore, the activity of the sympathetic autonomic nervous system is significantly altered in children with autism. The biometric method based on GDV is a promising step in autism research that may lead towards creating a disease profile and identify unique signature/biomarker for autism. Further work should involve more participants in order to augment our findings

Functional Annotation Analytics of Rhodopseudomonas palustris Genomes

Rhodopseudomonas palustris, a nonsulphur purple photosynthetic bacteria, has been extensively investigated for its metabolic versatility including ability to produce hydrogen gas from sunlight and biomass. The availability of the finished genome sequences of six R. palustris strains (BisA53, BisB18, BisB5, CGA009, HaA2 and TIE-1) combined with online bioinformatics software for integrated analysis presents new opportunities to determine the genomic basis of metabolic versatility and ecological lifestyles of the bacteria species. The purpose of this investigation was to compare the functional annotations available for multiple R. palustris genomes to identify annotations that can be further investigated for strain-specific or uniquely shared phenotypic characteristics. A total of 2,355 protein family Pfam domain annotations were clustered based on presence or absence in the six genomes. The clustering process identified groups of functional annotations including those that could be verified as strain-specific or uniquely shared phenotypes. For example, genes encoding water/glycerol transport were present in the genome sequences of strains CGA009 and BisB5, but absent in strains BisA53, BisB18, HaA2 and TIE-1. Protein structural homology modeling predicted that the two orthologous 240 aa R. palustris aquaporins have water-specific transport function. Based on observations in other microbes, the presence of aquaporin in R. palustris strains may improve freeze tolerance in natural conditions of rapid freezing such as nitrogen fixation at low temperatures where access to liquid water is a limiting factor for nitrogenase activation. In the case of adaptive loss of aquaporin genes, strains may be better adapted to survive in conditions of high-sugar content such as fermentation of biomass for biohydrogen production. Finally, web-based resources were developed to allow for interactive, user-defined selection of the relationship between protein family annotations and the R. palustris genomes

The Case for Visual Analytics of Arsenic Concentrations in Foods

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species