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Search Results: 1 - 10 of 41 matches for " Hanuman Thota "
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Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach
Allam Appa Rao,Hanuman Thota,Ramamurthy Adapala,Suresh Babu Changalasetty
Bioinformatics and Biology Insights , 2008,
Abstract: 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.
Alzheimer’s disease care and management: Role of information technology
Hanuman Thota,Allam Appa Rao,Kiran kumar Reddi,Sivaprasad Akula
Bioinformation , 2007,
Abstract: 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.
Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach
Allam Appa Rao,Hanuman Thota,Ramamurthy Adapala,Suresh Babu Changalasetty
Bioinformatics and Biology Insights , 2008,
Alzheimer's disease and Type 2 diabetes mellitus: the cholinesterase connection?
Appa Rao Allam, Gumpeny Sridhar, Hanuman Thota, Changalasetty Suresh Babu, Akula Siva Prasad, Ch Divakar
Lipids in Health and Disease , 2006, DOI: 10.1186/1476-511x-5-28
Abstract: Alzheimer's disease and type 2 diabetes mellitus occur with increasing frequency as age advances. Besides, the development of one increases the risk of the other [1]. Epidemiological studies have shown an association of diabetes mellitus and Alzheimer's disease. A population-based historical cohort study estimated that the risk of Alzheimer's disease increased with adult onset diabetes mellitus [2] A longitudinal study of 1,262 elderly subjects without dementia at baseline, adjusted relative risk of Alzheimer's disease among persons with diabetes was 1.3 [95% CI: 0.8, 1.9], [3]. In a more recent community-based study among 1301 dementia-free persons aged 75 and above, diabetes mellitus was associated with subsequent development of Alzheimer's disease [4]. Similarly patients with Alzheimer's disease were more vulnerable to developing impaired fasting glucose and type 2 diabetes mellitus [5]. A variety of mechanisms has been postulated in the risk of Alzheimer's disease and type 2 diabetes mellitus: metabolic abnormalities of insulin resistance (dyslipidemia, hypertension), hyperglycemia per se or insulin, by disturbing synaptic plasticity, learning and memory [6].The enzyme butyrylcholinesterase (EC does not have a well-defined physiological function, although it may modulate the phenotypic expression of dyslipidemia and insulin resistance. It is affected by dietary factors, obesity, and dyslipidemia [5,7,8]While acetylcholinesterase in the brain is chiefly localized to neurons, butyrylcholinesterase is primarily associated with glial cells and endothelial cells [9].Butyrylcholinesterase was studied in relation to both type 2 diabetes mellitus and Alzheimer's disease in different ethnic groups [10-13].Despite originating from the endoderm, the pancreas is highly innervated and shares molecular similarities with brain at the level of transcriptome and proteome [14]. Localized and progressive amyloidosis is characteristic of both type 2 diabetes and Alzheime
Techniques for integrating -omics data
Siva Prasad Akula,Raghava Naidu Miriyala,Hanuman Thota,Allam Appa Rao
Bioinformation , 2009,
Abstract: 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
Allam Appa Rao,N. Manga Tayaru,Hanuman Thota,Suresh Babu Changalasetty
International Journal of Biomedical Science , 2008,
Abstract: 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.
Ag(I) Catalyzed Grafting of Acrylonitrile onto Gum Arabic by Ce(IV) in H2SO4 Medium: A Kinetic Study
Geeta Thota,P. Srinivas
ISRN Physical Chemistry , 2012, DOI: 10.5402/2012/942398
Rusty pipe syndrome: A case report  [PDF]
Usharani Thota, Vasudeva Murali Machiraju, Venkateswara Rao Jampana
Health (Health) , 2013, DOI: 10.4236/health.2013.51020

Bloody discharge from the breasts in a lactating woman can be caused by various conditions like cracked nipples, mastitis, trauma or ductal papilloma [1]. A physiological condition called rusty pipe syndrome can also cause bilateral bloody discharge in lactating mothers [2].

Configuration of FPGA For Computerized Speech/Sound Processing For Bio-Computing Systems
V. Hanuman Kumar,P. Seetha Ramaiah
International Journal of Computer Science Issues , 2011,
Abstract: The development of Embedded Computer based bio-computing systems mimicking the natural functionality of human parts, is in continuous research because of advent of technology that used Very Large Scale Integration (VLSI) devices such as Field Programmable Gate Array (FPGA) to meet the challenging requirement of providing 100% functionality of the damaged human parts. The evolution of Field Programmable Gateway Array (FPGA) devices to the current state- of-art System-On-Chip (SOC) devices poses considerable problems in terms of ensuring designer productivity in developing high end Computerized Biomedical Speech Processing applications to these devices. Modern Programmable FPGA structures are equipped with specialized Digital Speech Processing embedded blocks that allow implementing digital speech processing algorithms with use of the methodology known from digital signal processor these programmable FPGA architectures give the designer the possibility to increase efficiency of the designed system. This paper presents the details of design and development of one of the bio-computing systems such as Bionic Ear or Cochlear Implant (CI) system with greater emphasis on configuration of FPGA with efficient processing algorithm. Bio-computing system incorporates Xilinx Spartan3 FPGA as the main chip for DSP IP cores, 32k words of memory, a 16-bit Analog to Digital converter fixed gain amplifier and programmable gain amplifier and transmitter which convey control codes to the receiver stimulator of the cochlear implant .The processor is battery powered and has been programmed to emulate the continuous interleaved sampling speech processor of 8 electrode implant. Here the Bio-computing system is a Real-Time Embedded Computing System (RTECS) that is required to collect the real-time speech/sound data, process the data by using speech/sound processing algorithm(s) and send the processed speech data to the electrode array inserted in the damaged inner ear (cochlea) for providing the speech recognition to the deafened person via inductive transcutaneous RF link. This process should run continuously without loss of speech/sound information.
Lalitha Saroja Thota,Suresh Babu Changalasetty
International Journal of Advances in Engineering and Technology , 2013,
Abstract: Neural networks have been used effectively in a number of applications including remote sensing, expert systems, image processing, data mining, decision systems etc. Back Propagation networks are a popular type of network that can be trained to recognize different patterns. Most of these applications have used the MLP back-propagation algorithm as the learning algorithm. One of the major problems with this algorithm is that its convergence time is usually very long since the training set must be presented many times to the network. If the learning rate is too low, the network will take longer to converge. On the other hand, if high, the network may never converge. The learning rate has to be selected very carefully. Up to now, designers of neural network applications had to find an appropriate learning rate for their systems by trial and error. We carry experiments on classification in data mining WEKA toolbox with multi-layer perception model using back propagation algorithm with diabetic dataset. In this paper, we try to find an optimum learning rate which is stable and takes less time for convergence.
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