Techniques for integrating -omics data.

The challenge for -omics research is to tackle the problem of fragmentation of knowledge by integrating several sources of heterogeneous information into a coherent entity. It is widely recognized that successful data integration is one of the keys to improve productivity for stored data. Through proper data integration tools and algorithms, researchers may correlate relationships that enable them to make better and faster decisions. The need for data integration is essential for present -omics community, because -omics data is currently spread world wide in wide variety of formats. These formats can be integrated and migrated across platforms through different techniques and one of the important techniques often used is XML. XML is used to provide a document markup language that is easier to learn, retrieve, store and transmit. It is semantically richer than HTML. Here, we describe bio warehousing, database federation, controlled vocabularies and highlighting the XML application to store, migrate and validate -omics data.

Bioinformatic analysis of functional proteins involved in obesity associated with diabetes.

The twin epidemic of diabetes and obesity pose daunting challenges worldwide. The dramatic rise in obesity-associated diabetes resulted in an alarming increase in the incidence and prevalence of obesity an important complication of diabetes. Differences among individuals in their susceptibility to both these conditions probably reflect their genetic constitutions. The dramatic improvements in genomic and bioinformatic resources are accelerating the pace of gene discovery. It is tempting to speculate the key susceptible genes/proteins that bridges diabetes mellitus and obesity. In this regard, we evaluated the role of several genes/proteins that are believed to be involved in the evolution of obesity associated diabetes by employing multiple sequence alignment using ClustalW tool and constructed a phylogram tree using functional protein sequences extracted from NCBI. Phylogram was constructed using Neighbor-Joining Algorithm a bioinformatic tool. Our bioinformatic analysis reports resistin gene as ominous link with obesity associated diabetes. This bioinformatic study will be useful for future studies towards therapeutic inventions of obesity associated type 2 diabetes.

Proteomic analysis in diabetic cardiomyopathy using bioinformatics approach.

Diabetic cardiomyopathy is a distinct clinical entity that produces asymptomatic heart failure in diabetic patients without evidence of coronary artery disease and hypertension. Abnormalities in diabetic cardiomyopathy include: myocardial hypertrophy, impairment of contractile proteins, accumulation of extracellular matrix proteins, formation of advanced glycation end products, and decreased left ventricular compliance. These abnormalities lead to the most common clinical presentation of diabetic cardiomyopathy in the form of diastolic dysfunction.We evaluated the role of various proteins that are likely to be involved in diabetic cardiomyopathy by employing multiple sequence alignment using ClustalW tool and constructed a Phylogenetic tree using functional protein sequences extracted from NCBI. Phylogenetic tree was constructed using Neighbour-Joining Algorithm in bioinformatics approach. These results suggest a causal relationship between altered calcium homeostasis and diabetic cardiomyopathy that implies that efforts directed to normalize calcium homeostasis could form a novel therapeutic approach.

Bioinformatics analysis of diabetic retinopathy using functional protein sequences.

Diabetic retinopathy is the leading cause of blindness among patients with diabetes mellitus. We evaluated the role of several proteins that are likely to be involved in diabetic retinopathy by employing multiple sequence alignment using ClustalW tool and constructed a phylogram tree using functional protein sequences extracted from NCBI. Phylogram was constructed using Neighbor-Joining Algorithm in bioinformatics approach. It was observed that aldose reductase and nitric oxide synthase are closely associated with diabetic retinopathy. It is likely that vascular endothelial growth factor, pro-inflammatory cytokines, advanced glycation end products, and adhesion molecules that also play a role in diabetic retinopathy may do so by modulating the activities of aldose reductase and nitric oxide synthase. These results imply that methods designed to normalize aldose reductase and nitric oxide synthase activities could be of significant benefit in the prevention and treatment of diabetic retinopathy.

Alzheimer's disease care and management: role of information technology.

Alzheimer's disease (AD) an ailment that is supposed to affect people in old age. There are evidences that it might affect others also. The number of elders is increasing as the average life expectancy is increasing. AD afflicts its patients with the dementia and AD might increase in malignance over time. People with cognitive disabilities can be overwhelmed through cognitive prosthetics. With the help of information technology we can enhance the quality of life. Significant achievements are possible with an interdisciplinary approach that includes genomic, genetic, technological and therapeutic measures. The combination and coordination of Bioinformatics facilitates generation of various diagnostic tools for the people who are suffering from Alzheimer's disease. These tools help the care providers also. In this article, we emphasize the literature regarding the use of technology and its methodologies to improve the quality of care for the people with Alzheimer's disease.

Alzheimer's disease and type 2 diabetes mellitus: the cholinesterase connection?

Alzheimer's disease and type 2 diabetes mellitus tend to occur together. We sought to identify protein(s) common to both conditions that could suggest a possible unifying pathogenic role. Using human neuronal butyrylcholinesterase (AAH08396.1) as the reference protein we used BLAST Tool for protein to protein comparison in humans. We found three groups of sequences among a series of 12, with an E-value between 0-12, common to both Alzheimer's disease and diabetes: butyrylcholinesterase precursor K allele (NP_000046.1), acetylcholinesterase isoform E4-E6 precursor (NP_000656.1), and apoptosis-related acetylcholinesterase (1B41|A). Butyrylcholinesterase and acetylcholinesterase related proteins were found common to both Alzheimer's disease and diabetes; they may play an etiological role via influencing insulin resistance and lipid metabolism.