ChemTextMiner: An open source tool kit for mining medical literature abstracts

Text mining involves recognizing patterns from a wealth of information hidden latent in unstructured text and deducing explicit relationships among data entities by using data mining tools. Text mining of Biomedical literature is essential for building biological network connecting genes, proteins, drugs, therapeutic categories, side effects etc. related to diseases of interest. We present an approach for textmining biomedical literature mostly in terms of not so obvious hidden relationships and build biological network applied for the textmining of important human diseases like MTB, Malaria, Alzheimer and Diabetes. The methods, tools and data used for building biological networks using a distributed computing environment previously used for ChemXtreme[1] and ChemStar[2] applications are also described

Context specific text mining for annotating protein interactions with experimental evidence

Indiana University-Purdue University Indianapolis (IUPUI)Proteins are the building blocks in a biological system. They interact with other proteins to make unique biological phenomenon. Protein-protein interactions play a valuable role in understanding the molecular mechanisms occurring in any biological system. Protein interaction databases are a rich source on protein interaction related information. They gather large amounts of information from published literature to enrich their data. Expert curators put in most of these efforts manually. The amount of accessible and publicly available literature is growing very rapidly. Manual annotation is a time consuming process. And with the rate at which available information is growing, it cannot be dealt with only manual curation. There need to be tools to process this huge amounts of data to bring out valuable gist than can help curators proceed faster. In case of extracting protein-protein interaction evidences from literature, just a mere mention of a certain protein by look-up approaches cannot help validate the interaction. Supporting protein interaction information with experimental evidence can help this cause. In this study, we are applying machine learning based classification techniques to classify and given protein interaction related document into an interaction detection method. We use biological attributes and experimental factors, different combination of which define any particular interaction detection method. Then using predicted detection methods, proteins identified using named entity recognition techniques and decomposing the parts-of-speech composition we search for sentences with experimental evidence for a protein-protein interaction. We report an accuracy of 75.1% with a F-score of 47.6% on a dataset containing 2035 training documents and 300 test documents

Biometric Personal Identification based on Iris Patterns

This paper discusses an analysis of human iris patterns for recognition of biometric system which consists of a segmentation system that is based on the Hough transform, and is able to localize the circular iris and pupil region, occluding eyelids and eyelashes, and reflections. The extracted iris region is then normalized into a rectangular block with constant dimensions to account for imaging inconsistencies. To encode the unique pattern of the iris into a bit-wise biometric template, 1D Log-Gabor filter is used.Finally to match two iris templates hamming distance is used as matching metric. The system performance is analyzed on 312 iris images taken from standard CASIA Iris Interval database version 4. To establish the verification accuracy of iris representation and matching approach, each iris image in the database is matched with all the other iris images in the database and genuine and imposter distribution is found .The performance of the system is implemented by evaluating the Decidability Index (DI), False match rate (FMR), False Non-match rate (FNMR), Genuine Accept Rate (GAR) and Equal error rate (EER)

Hypophosphatemic Rickets/ Osteomalacia: A Case Report and Review of Literature

Hypophosphatemic rickets/ osteomalacia comprises of a group of disorders of bone mineralization caused due to defect in renal handling of phosphorus. The group includes X linked hypophosphatemic rickets, autosomal dominant hypophosphatemic rickets and tumor induced osteomalacia. Here, we report the case of a young male who presented with mechanical low backache, muscular pains and proximal muscle weakness resulting in severe debility. He was diagnosed to have hypophosphatemic osteomalacia on the basis of hypophosphatemia, hyperphosphaturia, normal 25 hydroxy- and 1, 25 dihydroxy- vitamin D, normal intact PTH and raised serum FGF23 levels. Despite extensive search, no tumor was localized. He showed marked improvement with oral phosphate and calcitriol replacement and is under follow up

The Effect of Modifications of Activated Carbon Materials on the Capacitive Performance: Surface, Microstructure, and Wettability

none7siopenKouao Dujearic-Stephane; Meenal Gupta; Ashwani Kumar; Vijay Sharma; Soumya Pandit; Patrizia Bocchetta; Yogesh KumarDujearic-Stephane, Kouao; Gupta, Meenal; Kumar, Ashwani; Sharma, Vijay; Pandit, Soumya; Bocchetta, Patrizia; Kumar, Yoges

Decision Support System For Geriatric Care

poster abstractGeriatrics is a branch in medicine that focuses on the healthcare of the elderly. We propose to build a decision support system for the elderly care based on a knowledgebase system that incorporates best practices that are reported in the literature. A Bayesian network model is then used for decision support for the geriatric care tool that we develop

On Tests for Special Two-Sample Location Problem Based on Subsample Minimum and Median

Shetty and Umarani(2005) considered a special type of two-sample location problem which has some potential applications, particularly in comparing the performances of two packing machines. In this paper, a new class of test statistics is proposed which is based on sub-sample minima of first sample and sub-sample median of second sample. The performance of members of the new class is evaluated in terms of Pitman asymptotic relative efficiency in comparision with Shetty and Umarani(2005). It can be concluded that the performance of the new proposed class of tests is better for medium and heavy tailed distributions such as Normal, Logistic, Laplace and Cauchy. For light tailed distributions the performance of new testis better in specific cases. It is proved that the test is consistent for one-sided alternatives

Awareness and practice about preventive method against mosquito bite in Gujarat

Mosquito borne diseases are major public health problems in India. Gujarat is endemic for malaria and other mosquito borne diseases. Anopheles, Aedes and Culex are commonly seen in Gujarat. Therefore the efforts have been consistently made to educate the citizens of State on danger of mosquito bites. The present study was conducted to assess the awareness and practices of mosquito bite prevention methods among households of Central Gujarat district Vadodara. Total 311 families have participated in the study from UHTC area of the Medical college. Door to door visit was conducted to visit the all households. The study was conducted in the month of June 2009, which is observed as Anti-Malaria month in Gujarat. The pilot pre-tested structure questionnaire was used to collect the data. Study respondents were 57% male and 43% female. Almost 99% had knowledge about breeding places of mosquito, but poor knowledge about biting time (20%). 71% of participants knew that mosquito bite causes malaria. 39% 0f households were using mosquito net as protection against the bite, but only 10% were using insecticide treated bed net. There is need of increasing use of insecticide treated bed nets and continuous updating of knowledge about various aspects of mosquito bite

Mixing time studies in bubble column reactor with and without internals

Sectionalized bubble columns are finding a wide use in the case of FT synthesis, petroleum refining, wastewater treatments, extraction, absorption, leaching, ion exchange etc., due to their superiority in terms of reduced liquid phase back-mixing. The present work covers a mixing aspect in a 0.41 m id. sectionalized bubble column over a wide range of superficial gas velocity, liquid height to column diameter ratio, percent free area of the sectionalizing plates and electrolyte concentration for Air-water system. The acquired conductivity data was optimized using a compartmental and axial dispersion models and the model parameters have been estimated. For a given Hc/D ratio; mixing time was found to decrease with an increase in gas superficial velocity and free area of the sectionalizing plate. The compartmental model successfully predicts the tracer concentration profile and the longitudinal dispersion coefficient. The mixing time in a sectionalized bubble column was also compared with a non-sectionalized bubble column and was found to be order of magnitude higher