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Your search keyword '"Sharmila S. Mary"' showing total 7 results
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7 results on '"Sharmila S. Mary"'

1. Greenhouse Gases Emission from Municipal Solid Waste in Thanjavur

Author

Deepa, D., Sharmila, P., Sharmila, S. Mary Rebekah, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Loon, Lee Yee, editor, Subramaniyan, Muthulingam, editor, and Gunasekaran, K., editor

Published
2022
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3. An experimental investigation on corrosion impediment in R.C. slabs using anti-corrosive agents.

Author

Loganathan, P., Gracy, A. Fathima Darras, and Sharmila, S. Mary Rebekah

Subjects
CONCRETE slabs, DETERIORATION of materials, STEEL corrosion, SLABS (Structural geology)
Abstract

Most of the structures were subjected to aggressive influences of environment, these corrosion attacks on structures cause damage and lead to failure of the structural element or the whole structure [1]. Corrosion causes deterioration of material and leads to destruction of structures, especially in coastal and industrial area [8]. Corrosion of steel is an electro-chemical phenomenon. Electro-chemical corrosion result because of the existence of different metals of non-uniformities in steel or non- uniformities in chemical or physical environment, afforded by the surrounding concrete. This paper aimed at preventing corrosion in RC slabs using anti-corrosive agents such as providing zinc coating to the steel rods. The casted RC slabs with set of controlled specimen and slabs with anti-corrosive steel rods were tested. The Rebaklens coating (RC) is used by Galvanostatic Method (AM1) and Half Cell Method (AM2). The results are compared with uncoated bars. Rebaklens coating gives the better result to resist the corrosion. It is premeditated to radiate RC slabs with set of controlled specimen and slabs with anti-corrosive steel rods. The results provided comparative analysis of both sets of slabs. [ABSTRACT FROM AUTHOR]

Published
2022
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6. MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactions

Author

Peter Uetz, Svetlana Shtivelband, Srinivas Ramachandra, Naresh Raviswaran, Björn Titz, Julia Hofmann, Seesandra V. Rajagopala, Kumar C. Sunil, Johannes B. Goll, N.D. Deve Gowda, Stephen M Blazie, Sharmila S. Mary, Chetan S. Poojari, and Arnab Mukherjee

Subjects
Statistics and Probability, Context (language use), Computational biology, Biology, computer.software_genre, Biochemistry, Protein–protein interaction, Bacterial protein, Set (abstract data type), Bacterial Proteins, Protein Interaction Mapping, Databases, Protein, Molecular Biology, String database, Supplementary data, Microbial interaction, Computational Biology, Original Papers, Computer Science Applications, Computational Mathematics, ComputingMethodologies_PATTERNRECOGNITION, Computational Theory and Mathematics, Data mining, Experimental methods, computer, Protein Binding
Abstract

Prokaryotic protein–protein interactions are underrepresented in currently available databases. Here, we describe a ‘gold standard’ dataset (MPI-LIT) focusing on microbial binary protein–protein interactions and associated experimental evidence that we have manually curated from 813 abstracts and full texts that were selected from an initial set of 36 852 abstracts. The MPI-LIT dataset comprises 1237 experimental descriptions that describe a non-redundant set of 746 interactions of which 659 (88%) are not reported in public databases. To estimate the curation quality, we compared our dataset with a union of microbial interaction data from IntAct, DIP, BIND and MINT. Among common abstracts, we achieve a sensitivity of up to 66% for interactions and 75% for experimental methods. Compared with these other datasets, MPI-LIT has the lowest fraction of interaction experiments per abstract (0.9) and the highest coverage of strains (92) and scientific articles (813). We compared methods that evaluate functional interactions among proteins (such as genomic context or co-expression) which are implemented in the STRING database. Most of these methods discriminate well between functionally relevant protein interactions (MPI-LIT) and high-throughput data. Availability: http://www.jcvi.org/mpidb/interaction.php?dbsource=MPI-LIT. Contact: raja@jcvi.org Supplementary information: Supplementary data are available at Bioinformatics online.

Published
2008
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7. MPI-LIT: a literature-curated dataset of microbial binary protein--protein interactions.

Author

Seesandra V. Rajagopala, Johannes Goll, N.D. Deve Gowda, Kumar C. Sunil, Björn Titz, Arnab Mukherjee, Sharmila S. Mary, Naresh Raviswaran, Chetan S. Poojari, Srinivas Ramachandra, Svetlana Shtivelband, Stephen M. Blazie, Julia Hofmann, and Peter Uetz

Subjects
PROTEIN-protein interactions, PROKARYOTES, MICROBIAL proteins, GENOMICS, DATABASES, BIOINFORMATICS
Abstract

Prokaryotic protein–protein interactions are underrepresented in currently available databases. Here, we describe a ‘gold standard’ dataset (MPI-LIT) focusing on microbial binary protein–protein interactions and associated experimental evidence that we have manually curated from 813 abstracts and full texts that were selected from an initial set of 36 852 abstracts. The MPI-LIT dataset comprises 1237 experimental descriptions that describe a non-redundant set of 746 interactions of which 659 (88%) are not reported in public databases. To estimate the curation quality, we compared our dataset with a union of microbial interaction data from IntAct, DIP, BIND and MINT. Among common abstracts, we achieve a sensitivity of up to 66% for interactions and 75% for experimental methods. Compared with these other datasets, MPI-LIT has the lowest fraction of interaction experiments per abstract (0.9) and the highest coverage of strains (92) and scientific articles (813). We compared methods that evaluate functional interactions among proteins (such as genomic context or co-expression) which are implemented in the STRING database. Most of these methods discriminate well between functionally relevant protein interactions (MPI-LIT) and high-throughput data. Availability: http://www.jcvi.org/mpidb/interaction.php?dbsource=MPI-LIT. Contact: raja@jcvi.org Supplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2008
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