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Providing Collaborative Algorithms Support for Personal Health Care

Problem statement: Today, there is a growing interest towards the adoption of novel technology in the field of medical monitoring and personal health care systems in general. This is especially case with certain categories of people suffering from chronicle diseases that need 24 h access to medical care. Approach: To solve this challenging issue, a model of a system containing three levels: bionetwork, social community and primary and secondary health-care centers, was developed. The main purpose of the proposed methodology is to find the dependency of the users� health condition (obtained by bionetwork) and physical activity he/she perform (get by mobile application). To achieve this we consider datasets from the health history of users (obtained from clinical centers) and use classification algorithms on these datasets for grouping the users based on their similarity. Results: Developed model of a system which enables 24 h monitoring of the condition of patients and the possibility of sending an emergency call for sudden deterioration of his/her medical condition. In addition, the system enables the patient (system user) to contact other people with similar condition and exchange their experience. Conclusion: The system improves the terms of home care treatment of the patient and increases the medical capacity of the appropriate healthcare institutions which results in significant reduction of the overall costs for patients and hospitals.

Using Threads to Overcome Synchronization Delays in Parallel Multiple Progressive Alignment Algorithms

Problem statement: The parallelization of multiple progressive alignment algorithms is a difficult task. All known methods have strong bottlenecks resulting from synchronization delays. This is even more constraining in distributed memory systems, where message passing also delays the interprocess communication. Despite these drawbacks, parallel computing is becoming increasingly necessary to perform multiple sequence alignment. Approach: In this study, it is introduced a solution for parallelizing multiple progressive alignments in distributed memory systems that overcomes such delays. Results: The proposed approach uses threads to separate actual alignment from synchronization and communication. It also uses a different approach to schedule independent tasks. Conclusion/Recommendations: The approach was intensively tested, producing a performance remarkably better than a largely used algorithm. It is suggested that it can be applied to improve the performance of some multiple alignment tools, as CLUSTALW and MUSCLE.

Use of Enterobacterial Repetitive Intergenic Consensus PCR in Detecting Target(s) of Hapalindole-T, From a Cyanobacterium, in Escherichia Coli: In Silico Validation

Problem statement: Identification of newer biomolecule as well as targets are a rising concern because of increasing drug resistance in bacteria. We have isolated a broad spectrum antibiotic biomolecule Hapalindole-T from a cyanobacterium, Fisherella sp. growing on local Azadirachta indica tree bark. A model bacterium E. coli was screened spontaneously for Hap-T resistance. These resistant strains of E. coli were used to identify Hap-T target(s). Approach: These strains were subjected to Enterobacterial Repetitive Intergenic Consensus (ERIC) PCR analysis and compared with the sensitive one. We have used different bioinformatic tools like Clustalw, NJ Plot and Docking server. The Swiss-model server was used for homology modelling. Predicted 3D structure was refined by energy minimization and quality was assessed by Procheck. The model protein hailed from fimbrial biogenesis outer membrane usher protein (ADK89122.1). The interaction between the predicted structure of Model-1 protein and Hap-T biomolecule was analysed in silico using Autodock and Mopac parameters. Results: An additional band of DNA fragment (~500 base pairs) was found on agarose gel run after amplified genome of resistant strain. The results indicated that certain residues (Tyr-28), (Phe-54), (Leu-36) and (Val-52) were highly conserved and present in active sites. Conclusion/Recommendations: Thus understanding of microbial adhesion can act as an alternative approach in development of broad spectrum antibiotics.

Bayesian Determination of Disease Associated Differences in Haplotype Blocks

Problem statement: While experimental ascertainment of haplotype blocks in the genome-scale case-control studies is expensive, accurate computational phasing is still a daunting task for bioinformatics approaches. We used a statistical method to determine differences, potentially associated with a certain disease, in linkage disequilibrium block boundaries in whole-genome Single Nucleotide Polymorphisms (SNPs) data. Approach: We utilized a Bayesian model for calculating the posterior probabilities of the block boundaries in the SNPs data and used Metropolis-Hastings algorithm to sample from that posterior distribution. Our method was applied to search for haplotype-block boundary differences associated with two autoimmune diseases: Type I Diabetes (T1D) and Rheumatoid Arthritis (RA). Results: We located the regions on chromosome 6 with significant control-case difference in haplotype blocks around the SNPs and genes that were previously known to be associated with T1D and RA (in the HLA complex), as well as around genes whose association with the autoimmune diseases should be further explored in future studies. Conclusion/Recommendations: The statistical approach explored in this study provides an efficient and accurate way to study connection of haplotype-block differences to multiple important diseases.

Bioinformatics-Assisted Microbiological Research: Tasks, Developments and Upcoming Challenges

Problem statement: Bioinformatics in the present day microbiological research is an inevitable subject area that encompasses biological resources and high end computational skills to unravel the coded and encrypted information within the life. We have produced a brief account of the developments and tasks in the subject and upcoming challenges in the subject. The area has seen tremendous developmental pattern in the last few decades due to the emerging computational technologies dedicated for uncovering the complex but vital biological information that not only essentially constitute the basis of life but entails about the evolutionary diversification and multiphasic interaction among the organisms with their own environment. Now, with the technological advancements, bioinformatics has completely changed microbiological domain for researchers. Conclusion/Recommendations: In Future, the ultimate goal of bioinformatics will be such kind of integration of the biological databases and genomic resources that can result in a computer representation of living cells and organisms whereby any aspect of biology can be examined computationally.

A Sequence Based Validation of Gene Expression Microarray Data

Problem statement: Quantitative Reverse Transcription PCR (RT-qPCR) is often used to validate microarray data. Previous studies show different levels of correlation, without further investigation of influencing factors. Approach: We compared expression levels of 381 genes obtained from microarray hybridizations and from TaqMan based RT-qPCR assays. Correlation of expression levels was determined by comparing: (i) single genes across samples, (ii) all genes within a sample and (iii) the expression ratios of all genes in a sample using another sample as the reference. The influence of several parameters on the correlation was analyzed: (i) variation in transcript set targeted by the microarray probe and the PCR assay, (ii) variation in amplicon probe position relative to 3' end of transcript, (iii) variation in efficiency of the PCR reaction and (iv) normalization of the PCR data. Results: The 381 genes covered by RT-qPCR had 494 matching probes on the microarray. 397 probes with a matching transcript set were identified via a rigid sequence-based validation. Correlation was significantly higher among matching transcript sets and probes closer to the 3' end. Adjustments for different amplification efficiencies had either no influence or decreased correlation. Normalization of qPCR data consistently reduced correlation for all analysis approaches. Conclusion: Current clinical research uses microarrays to select genes of interest and evaluates these genes using qPCR. Therefore, it is important that expression levels measured by both techniques be highly correlated. High correlation can be achieved if the targeted transcript sets match, whereas normalization and efficiency correction can have a negative influence.