Research

Publications (Journal)

1. Tushar Ranjan Sahoo, Sabyasachi Patra, Swati Vipsita, Decision tree classifier based on topological characteristics of subgraph for the mining of protein complexes from large scale PPI networks, Computational Biology and Chemistry, Volume 106,2023,107935, ISSN 1476-9271, doi.org/10.1016/j.compbiolchem.2023.107935. 

2. Routray, M., Vipsita, S. Protein remote homology detection combining PCA and multiobjective optimization tools. Evol. Intel. 16, 67–76 (2023). 

doi.org/10.1007/s12065-021-00642-6 

3. Sahoo, T.R., Vipsita, S. and Patra, S. Complex Prediction in Large PPI Networks Using Expansion and Stripe of Core Cliques. Interdiscip Sci Comput Life Sci 15, 331–348 (2023). doi.org/10.1007/s12539-022-00541-z 

4. Mukti Routray, Swati Vipsita, Amrita Sundaray, Srinidhi Kulkarni, DeepRHD: An efficient hybrid feature extraction technique for protein remote homology detection using deep learning strategies, Computational Biology and Chemistry, Volume 100,2022,107749, ISSN 1476-9271,doi.org/10.1016/j.compbiolchem.2022.107749. 

5. Bhawani Sankar Biswal, Anjali Mohapatra, Swati Vipsita, Ensemble Neighborhood Search (ENS) for biclustering of gene expression microarray data and single cell RNA sequencing data, Journal of King Saud University - Computer and Information Sciences, Volume 34, Issue 5,2022,Pages 2244-2251,ISSN 1319-1578, doi.org/10.1016/j.jksuci.2019.11.011 

6. Sahoo, Tushar Ranjan, Swati Vipsita, and Sabyasachi Patra. Protein complex prediction based on dense sub-graph merging, International Journal of Data Mining and Bioinformatics 26.3-4 (2021): 129-150. doi.org/10.1504/IJDMB.2021.126837 

7. Biswal, B. S, Patra, S., Mohapatra, A. and Vipsita, S. (2020). TriRNSC: triclustering of gene expression microarray data using restricted neighbourhood search. IET Systems Biology, 14(6), 323-333.doi.org/10.1049/iet-syb.2020.0024 

8. Santos Kumar Baliarsingh, Swati Vipsita, Amir H. Gandomi, Abhijeet Panda, Sambit Bakshi, Somula Ramasubbareddy,,Analysis of high-dimensional genomic data using MapReduce based probabilistic neural network, Computer Methods and Programs in Biomedicine,Volume 195,2020,105625,ISSN 0169-2607,doi.org/10.1016/j.cmpb.2020.105625.  

9. Biswal, B.S., Mohapatra, A. & Vipsita, S. Triclustering of gene expression microarray data using coarse grained and dynamic deme based parallel genetic approach. Evol. Intel. 13, 475–495 (2020). doi.org/10.1007/s12065-019-00330-6 

10. Baliarsingh, S.K., Vipsita, S. & Dash, B. A new optimal gene selection approach for cancer classification using enhanced Jaya-based forest optimization algorithm. Neural Comput & Applic 32, 8599–8616 (2020). doi.org/10.1007/s00521-019-04355-x 

11. Baliarsingh, Santos Kumar, and Swati Vipsita. Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification, IET Systems Biology 14.2 (2020): 85-95. doi.org/10.1049/iet-syb.2019.0028 

12. Santos Kumar Baliarsingh, Weiping Ding, Swati Vipsita, Sambit Bakshi, A memetic algorithm using emperor penguin and social engineering optimization for medical data classification, Applied Soft Computing, Volume 85,2019,105773,ISSN 1568-4946, doi.org/10.1016/j.asoc.2019.105773. 

13. Santos Kumar Baliarsingh, Swati Vipsita, Khan Muhammad, Sambit Bakshi, Analysis of high-dimensional biomedical data using an evolutionary multi-objective emperor penguin optimizer, Swarm and Evolutionary Computation, Volume 48, 2019, Pages 262-273,ISSN 2210-6502, doi.org/10.1016/j.swevo.2019.04.010. 

14. Santos Kumar Baliarsingh, Swati Vipsita, Khan Muhammad, Bodhisattva Dash, Sambit Bakshi, Analysis of high-dimensional genomic data employing a novel bio-inspired algorithm, Applied Soft Computing, Volume 77,2019, Pages 520-532,ISSN 1568-4946, doi.org/10.1016/j.asoc.2019.01.007. 

15. Biswal, Bhawani Sankar, Anjali Mohapatra, and Swati Vipsita. A review on biclustering of gene expression microarray data: algorithms, effective measures and validations, International Journal of Data Mining and Bioinformatics 21.3 (2018): 230-268.doi.org/10.1504/IJDMB.2018.097683 

16. Vipsita, Swati, and Santanu Kumar Rath. Sequence–based protein superfamily classification using computational intelligence techniques: a review, International Journal of Data Mining and Bioinformatics 11.4 (2015): 424-457.doi.org/10.1504/IJDMB.2015.067957 

17. Swati Vipsita, Santanu Ku. Rath, Two-Stage Approach for Protein Superfamily Classification, Computational Biology Journal, vol. 2013, Article ID 898090,  2013. doi.org/10.1155/2013/898090 

18. Vipsita, Swati, and Santanu Ku Rath. Protein superfamily classification using adaptive evolutionary radial basis function network, International Journal of Computational Intelligence and Applications 11.04 (2012): 1250026.doi.org/10.1142/S1469026812500265 

Publications (Conferences)

1. P. Mishra, S. Vipsita and T. K. Sahoo, Molecular Docking on SARSCOV2 Target Protein, 2023 2nd International Conference on Ambient Intelligence in Health Care (ICAIHC), Bhubaneswar, India, 2023, pp. 01-04, doi: 10.1109/ICAIHC59020.2023.10431457. 

2. Priya Mishra, Swati Vipsita and Tapan Kumar Sahoo , Ligand-Based Drug Discovery on SARSCOV2 Target Protein, 2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON)Mysuru, 5 th - 7 th August 2023.

3. Baliarsingh, Santos Kumar, Chinmayee Dora, and Swati Vipsita. Jaya optimized extreme learning machine for breast cancer data classification, Intelligent and Cloud Computing: Proceedings of ICICC 2019, Volume 2. Springer Singapore, 2021.

4. Shreya, Ankita, Swati Vipsita, and Santos Kumar Baliarsingh. Cancer classification using improved extreme learning machine, 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2019.

5. Mamgain, S., Kumar, S., Nayak, K. M., & Vipsita, S. (2018, August). Car Popularity Prediction: A Machine Learning Approach. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) (pp. 1-5). IEEE.

6. Routray, Mukti, and Swati Vipsita. Remote Homology Detection Using Physicochemical Parameters and Physicochemical Properties, 2017 International Conference on Information Technology (ICIT). IEEE, 2017.

7. Acharya, Reshma, Swati Vipsita, and Santos Kumar Baliarsingh, Biclustering of microarray data employing multiobjective Genetic Algorithm, 2017 14th IEEE India Council International Conference (INDICON). IEEE, 2017.

8. Mishra, Shreya, and Swati Vipsita. Triclustering of gene expression microarray data using evolutionary approach, 2017 14th IEEE India Council International Conference (INDICON). IEEE, 2017.

9. Mishra, Shreya, and Swati Vipsita. Biclustering of gene expression microarray data using dynamic deme parallelized genetic algorithm (DdPGA), 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2017.

10. Biswal, B. S., Mishra, P., Mohapatra, A., & Vipsita, S. (2016, December). A survey on greedy based algorithms for biclustering of gene expression microarray data. In 2016 international conference on information technology (ICIT) (pp. 124-128). IEEE.

11. Mishra, A., Biswal, B. S., Mohapatra, A., & Vipsita, S. (2016, July). Biclustering of gene expression patterns with an advanced overlapping control strategy. In 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES) (pp. 1-5). IEEE.

12. Laishram, Ayangleima, and Swati Vipsita. Bi-clustering of gene expression microarray using coarse grained parallel genetic algorithm (cgpga) with migration, 2015 annual IEEE India conference (INDICON). IEEE, 2015.

13. Sreepada, Rama Syamala, Swati Vipsita, and Puspanjali Mohapatra. An efficient approach for microarray data classification using filter wrapper hybrid approach., 2015 IEEE International Advance Computing Conference (IACC). IEEE, 2015.

14. Sreepada, Rama Syamala, Swati Vipsita, and Puspanjali Mohapatra. An efficient approach for classification of gene expression microarray data, 2014 Fourth International Conference of Emerging Applications of Information Technology. IEEE, 2014.