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Gowrishankar, J.
- Gene Biclustering On Large Datasets Using Fuzzy C-means Clustering
Abstract Views :336 |
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Authors
Affiliations
1 Department of Computer Science and Engineering, HKBK College of Engineering, IN
2 Department of Computer Science and Engineering, Jain University, IN
3 Department of Computer Science and Engineering, Presidency University, IN
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, OM
1 Department of Computer Science and Engineering, HKBK College of Engineering, IN
2 Department of Computer Science and Engineering, Jain University, IN
3 Department of Computer Science and Engineering, Presidency University, IN
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, OM
Source
ICTACT Journal on Soft Computing, Vol 12, No 2 (2022), Pagination: 2578-2582Abstract
The current study employs biclustering to alleviate some of the drawbacks associated with gene expression data grouping. Different biclustering algorithms are used in this study to detect unique gene activity in various contexts and reduce the duplication of broad gene information. Furthermore, machine learning or heuristic algorithms have become widely utilised for biclustering due to their suitability in problems where populations of potential solutions allow examination of a larger percentage of the research area. To begin with, gene expression data biclusters frequently contain data that is the same under a variety of different situations of gene expression. Therefore, the biclustering technique is particularly effective if the matrix lines and columns are merged immediately. Submatrices can be identified using the Large Average Sub matrix. A Fuzzy C-Means algorithm is also used to ensure that the sub-matrix can be expanded to include more rows and columns for further analysis. The sub-matrices and component precision and strength are factored into the system design. It uses biclustering techniques to differentiate gene expression information. On the Garber dataset, the simulation is run in Java. Using the average match score for non-overlapping modules, the influence of noise on overlapping modules using constant bicluster and additive bicluster, and the overall run duration, the study is assessed.Keywords
Heuristic Algorithm, Gene Expression, Data Biclusters, Fuzzy C-Means
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- Suggestions for a National Framework for Publication of and Access to Literature in Science and Technology in India
Abstract Views :498 |
PDF Views:198
Authors
S. Chakraborty
1,
J. Gowrishankar
2,
A. Joshi
3,
P. Kannan
4,
R. K. Kohli
4,
S. C. Lakhotia
5,
G. Misra
6,
C. M. Nautiyal
7,
K. Ramasubramanian
8,
N. Sathyamurthy
3,
A. K. Singhvi
9
Affiliations
1 National Institute of Plant Genome Research, New Delhi, IN
2 Indian Institute of Science Education and Research Mohali, IN
3 Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, IN
4 Central University of Punjab, Bathinda, IN
5 Banaras Hindu University, Varanasi, IN
6 Indian Institute of Science, Bengaluru, IN
7 Indira Nagar, New Delhi, IN
8 Indian Institute of Technology, Mumbai, IN
9 Physical Research Laboratory, Ahmedabad, IN
1 National Institute of Plant Genome Research, New Delhi, IN
2 Indian Institute of Science Education and Research Mohali, IN
3 Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, IN
4 Central University of Punjab, Bathinda, IN
5 Banaras Hindu University, Varanasi, IN
6 Indian Institute of Science, Bengaluru, IN
7 Indira Nagar, New Delhi, IN
8 Indian Institute of Technology, Mumbai, IN
9 Physical Research Laboratory, Ahmedabad, IN
Source
Current Science, Vol 118, No 7 (2020), Pagination: 1026-1034Abstract
The outcome of deliberation on various aspects of publication and free access to scientific literature by a panel of nominated fellows from three science academies, viz. Indian National Science Academy, Indian Academy of Sciences, The National Academy of Sciences India, and expert invitees are presented.Full Text
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- Public Ownership of Research Journals
Abstract Views :512 |
PDF Views:211
Authors
Affiliations
1 Indian Institute of Science Education and Research, Sector 81, Mohali 140 306, IN
1 Indian Institute of Science Education and Research, Sector 81, Mohali 140 306, IN
Source
Current Science, Vol 119, No 4 (2020), Pagination: 583-584Abstract
No Abstract.Full Text
- Annual Review of Microbiology, 2022. Susan Gottesman, Andrew L. Goodman and Caroline S. Harwood (eds)
Abstract Views :229 |
Authors
Affiliations
1 Indian Institute of Science Education and Research, Sector 81, SAS Nagar, Mohali 140 306, IN
1 Indian Institute of Science Education and Research, Sector 81, SAS Nagar, Mohali 140 306, IN
Source
Current Science, Vol 125, No 10 (2023), Pagination: 1136-1137Abstract
No Abstract.Keywords
No Keywords.Full Text