Academic Profile of Prof. Piyali Chatterjee
Academic Profile of Prof. Piyali Chatterjee
Piyali Chatterjee
Associate Professor and HOD,
Computer Science & Engineering Department

ACADEMIC QUALIFICATION:
Ph.D.: [2012, Jadavpur University]
Post Graduate: [ M.Tech (CSE) 2004, University of Calcutta]
[M.Sc ( Computer & Info Sc) 2002,University of
Under Graduate: [B.Sc (Computer Science Hons.) 2000, University of Calcutta]

TOTAL EXPERIENCE: 17 Years

Linkedin: https://www.linkedin.com/in/piyali-chatterjee-7936b6179/
Official eMail Id: piyali.chatterjee@nsec.ac.in
Professional Experience:
[Associate Professor, Dept. of Computer Sc. & Engg. , NSEC from 01.12.2018 to till date ]
[Assistant Professor, Dept. of Computer Sc. & Engg. , NSEC from 01.07.2010 to 30.11.2018]
[Senior Lecturer, Dept. of Computer Sc. & Engg., NSEC 01.04.2009 to 30.06.2010]
[Lecturer, Dept. of Computer Sc. & Engg., NSEC, from 21.02.2004 to 31.03.2009]


Professional Society Membership:
IEEE Senior member, Computational Intelligence Society,


Awards & Honors Received:
Fellow, Nikhil Bharat Shiksha Parishad, Regd. & Licensed Org. under MCA , Govt. of India


Association with Outside World:
Examiner and Paper Setter, MAKAUT
External Examiner of Project Evaluation, Jadavpur University
Co-Principal Investigator in Collaborative sponsored research, Jadavpur University


No of Journal Paper Published: 19

No Conference Paper Published: 18

Research Areas:
Bioinformatics, Machine Learning


Resarch Collaboration:
Collaborative research with Prof. Mita Nasipuri, Prof. Subhadip Basu, Jadavpur University, Dr. Daruisz Plewcyznski, Warshaw University, Poland


Sponsored Projects:
Project Title: Development of some analytical tools for analysis of large-scale protein-protein interaction networks, no. BT/PR16356/BID/7/596/2016, cost: 48 lakhs, Funded by Government of India, Ministry of Science & Technology, Department of Biotechnology, role: Co-Principal Investigator


Ph.D. Students Awarded:>
SOVAN SAHA, Jadavpur University > < Thesis title: Some Studies on analyses of Protein-Protein Interaction Networks , REGD. in CSE, JADAVPUR UNIVERSITY (Reg. No. 1011511002, 02.02.2016)>


No. of M.Tech/MBA/MCA Final Year Projects Handled: 12

No. of B.Tech/BBA/BCA/B.Sc. Final Year Projects Handled: 25

No of Conferences/Invited Talks/Seminars/ Attended: 26

COURSES UNDERTAKEN:
Undergraduate: Computer Graphics, Artificial Intelligence, Pattern Recognition
Postgraduate: Theory of Computation, Bioinformatics

Administrative Responsibilities:
Head of the Department, Computer Science & Engineering
Central Academic Committee, Member,
Internal Quality Assurance Committee, Member,
Disciplinary Committee, Member


Name of Final Year Projects (Currently Handling):
2022
1. PREDICTIONOF COVID-19 DRUG TARGETS BASED ON PROTEIN SEQUENCE AND NETWORK PROPERTIES USING MACHINE LEARNING ALGORITHM
2. Analysis of high quality Negative Protein-Protein Interaction dataset


List of Publication of Journals Papers:
1. Saha S, Chatterjee P, Nasipuri M, Basu S. 2021. Detection of spreader nodes in human-SARS-CoV protein-protein interaction network. PeerJ 9:e12117 https://doi.org/10.7717/peerj.12117, Impact factor: 2.984

2. Saha S, Halder AK, Bandyopadhyay SS, Chatterjee P, Nasipuri M, Bose D, Basu S, “Drug repurposing for COVID-19 using computational screening: Is Fostamatinib/R406 a potential candidate?,”Methods,2021, ISSN 1046-2023,https://doi.org/10.1016/j.ymeth.2021.08.007, Impact factor: 3.641

3. Bandyopadhyay SS, Halder AK, Zar?ba-Kozio? M, Bartkowiak-Kaczmarek A, Dutta A, Chatterjee P, N asipuri M, Wójtowicz T, Wlodarczyk J, Basu S. RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data. International Journal of Molecular Sciences. 2021; 22(18):9901. https://doi.org/10.3390/ijms22189901, Impact factor: 5.923

4. Saha S, Prasad A, Chatterjee P, Basu S, Nasipuri M, “Modified FPred-Apriori: improving function prediction of target proteins from essential neighbours by finding their association with relevant functional groups using Apriori algorithm” , International Journal of Advanced Intelligence Paradigms, Vol. 19, No. 1, 61-83, Inderscience Publishers (IEL), Impact factor: 0.63

5. Halder AK, Bandyopadhyay SS, Chatterjee P, Nasipuri M, Plewczynski D, “JUPPI: A multi-level feature based method for PPI prediction and a refined strategy for performance assessment,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10.1109/TCBB.2020.3004970, IEEE. Impact Factor 2.428.

6. Saha S, Chatterjee P, Basu S, Nasipuri M, Plewczynski D. 2019. FunPred 3.0: improved protein function prediction using protein interaction network. PeerJ 7:e6830https://doi.org/10.7717/peerj.6830 Impact Factor: 2.118.

7. Sengupta K, Saha S, Chatterjee P, Kundu M, Nasipuri M, Basu S, “Identification of Essential proteins by detecting Topological and Functional Clusters in Protein Interaction Network of Saccharomyces Cerevisae , Jounal of Natural Computing research (IJNCR) vol:8 (1) , pages 31-51, Int J Nat Comput Res 8:21. doi: 10.4018/IJNCR.2019010103, 2019.

8. Halder, A.K., Chatterjee, P., M., Nasipuri, Plewczynski, D., Basu, Subhadip, “3gClust: Human Protein Cluster Analysis,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.(2018). Impact Factor: 2.428.

9. Saha S, Prasad A, Chatterjee P, Nasipuri M, Basu S,” Protein Function Prediction from Protein-Protein Interaction Network using Gene ontology based neighborhood analysis and physicho-chemical features, Int’l Journal of Bioinformatics and Computational Biology, Vol: 16(6) , World Scientific Publishing Europe Ltd, https://doi.org/10.1142/S0219720018500257, ISSN (print): 0219-7200 | ISSN (online): 1757-6334. Impact Factor : 0.9

10. Saha S, Sengupta K, Chatterjee P, Basu S, Nasipuri M, “Analysis of Protein interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network”, Int’l journal of Briefings in Functional Genomics, DOI: 10.1093/bfgp/elx024, 2017. Impact Factor: 3.783.

11. Saha S, Prasad A, Chatterjee P, Basu S, Nasipuri M (2017c), “Modified FPred-Apriori: improving function prediction of target proteins from essential neighbours by finding their association with relevant functional groups using Apriori algorithm. Int J Adv Intell Paradig. Inderscience. (In Press).

12. Chatterjee,P., Basu,S., Zubek, J., Kundu,M., Nasipuri, M. and Plewczynski, D., “PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach,” Int’l J. of Molecular Modeling, vol. 22 No. 72 ,10.1007/s00894-016-2933-0, 2016.2015 . Impact Factor: 1.490

13. Chowdhury P, Jha N, Chatterjee P, “DOM_SVM: Protein Domain Boundary Prediction using Support Vector Machine Classifier “, IJPBS, vol. 5 (2), pp.245-266, 2015.

14.Saha S, Chatterjee P, Basu S, Kundu M, Nasipuri M , “FunPred-1: Protein function prediction from a protein interaction network using neighborhood analysis. Cell Mol Biol Lett. Vol.19 No.4: 675-91. doi: 10.2478/s11658-014-0221-5. Epub 2014 Nov 25., 2014 Impact factor : 1.291

15. Saha S, Chatterjee P, “Protein function prediction from protein interaction network using physico- chemical properties of amino acids,” Int’l J. Pharmacy and Biological Sciences, vol. 4, No. 2, pp.55-65, (e-ISSN-2230-7605) 2014.

16. Sinha Roy C, Chatterjee P, “PFP_Min: A Graph Theoretic Approach for prediction of Protein Function from Protein Interaction Network,” Int’l IOSR J. Pharmacy and Biological Sciences, vol.9 No. 3, pp. 30-36, (e-ISSN 2278-3008) 2014.

17. Chatterjee P, Basu S, Kundu M, Nasipuri M, Plewczynski D, “ PPI_SVM: Prediction of Protein-Protein Interactions using machine learning, domain-domain affinities and frequency tables”, Int’l J. Cellular Molecular Biology Letters, vol. 16, No.2, pp.264-278, 2011.Impact factor : 1.291

18.Chatterjee P, Basu S, Kundu M, Nasipuri M, Plewczynski D , “PSP_MCSVM: Prediction of protein secondary structure using two-stage multi-class support vector machine”, Int’l J. of Molecular Modeling, vol. 17, pp. 2191–2201, DOI 10.1007/s00894-011-1102-8, 2011.Impact Factor: 1.834

19.Chatterjee P, Basu S, Kundu M, Nasipuri M, “Improved prediction of Multi-domains in protein chains using a Support Vector Machine,” Int’l J. of Recent Trends in Engineering, vol. 2, no. 3, pp.78-81, 2009.



List of Publication of Conference Proceedings:
1. Dutta A, Bandyopadhyay SS, Halder AK, Chatterjee P, Nasipuri M, Basu S, “Protein structure Clustering using Multivariate Mutual Information based sequence features”, ICETSD, 2019.

2. Bandyopadhyay SS, Halder AK, Chatterjee P, Nasipuri M, Basu S, “HdK-Means: Hadoop Based Parallel K-Means Clustering for Big Data” 2017 IEEE Calcutta Conference (CALCON),pp.452-456, 978-1-5386-3745-6/17/$31.00 ©2017 IEEE, 2017.

3. Saha S, Chatterjee P, Basu S, Nasipuri M “Functional Group Prediction of Un annotated Protein by Exploiting its Neighborhood Analysis in Saccharomyces Cerevisiae Protein Interaction Network” in the Proceedings of 3rd International Doctoral Symposium on Applied Computation and Security Systems (ACSS), 165–177,2017.

4.Saha S, Chatterjee P, Basu S, Nasipuri M “Gene Ontology Based Function Prediction of Human Protein Using Protein Sequence and Neighborhood Property of PPI Network” in the Proceedings of 5th International Conference on Frontiers of Intelligent Computing: Theory and applications (FICTA ) 109–118, 2017.

5.Chatterjee P, Basu S, Zubek J, Kundu M, Nasipuri M, Plewczynski D, “PDP-RF: Protein Domain Boundary Prediction Using Random Forest Classifier. Pattern Recognition and Machine Intelligence, Lecture Notes in Computer Science Volume 9124, 2015, pp 441-450, 23 Jun, 2015.

6.Chakraborty S, Das S, Chatterjee P ,”Prediction of Domain Boundaries in Protein Sequences using Predicted Secondary Structure and physicochemical Properties of Amino Acids”, 2014 International Conference on Circuit, Power and Computing Technologies [ICCPCT]pp. 1022-1026.,2014.

7.Payal S, Chatterjee P, Basu S, Kundu M, Nasipuri M, “Comparisons of Different Feature Sets for Predicting Carbohydrate-Binding Proteins from Amino Acid Sequences Using Support Vector Machine, “BICTA (1) 2012: 519-529, 2012.

8.Saha S, Chatterjee P, Basu S, Kundu M, Nasipuri M “Improved Prediction of Protein function from Protein Interaction Network using Intelligent Neighborhood approach,” Int’l Conference on Communications, Devices and Intelligent Systems (CODIS),pp. 608-611,2012.

9.Chatterjee P, Basu S, Kundu M, Nasipuri M, “Improving prediction of interdomain linkers in protein sequences using a consensus approach,” Int’l Conf InConINDIA-2012, India, pp.111-118, 2012.

10. Chatterjee T, Chatterjee P, Basu S, Kundu M, Nasipuri M, “Protein function prediction by Minimum Distance Classifier from Protein Interaction Network,” Int’l Conference on Communications, Devices and Intelligent Systems (CODIS),pp. 608-611,2012.

11. Das P, Chatterjee P, Basu S, Nasipuri M, “ Prediction of Protein –Protein Interaction using validated domain-domain interaction,” Int’l Conference Indicon’2011, DOI: 10.1109/INDICON.2011.6139330.

12. Chatterjee P, Basu S, Nasipuri M, “Improving prediction of protein secondary structure using physicochemical properties of amino acids”, Proc. Int’l Symp. Biocomputing, Article No: 10, ISBN: 978-1-60558-722-6, 2010.

13. Chatterjee P, Basu S, Kundu M, Nasipuri M, Basu DK“Protein Secondary structure Prediction through Combinations of Decisions from Multiple MLP classifiers,” Proc. Int’l Conf. MS’07, India, pp.206-210, 2007. 14. S. Saha, P. Chatterjee, S. Basu and M. Nasipuri, "Multiple Functions Prediction of Yeast Saccharomyces Cerevisiae Proteins using Protein Interaction Information, Sequence Similarity and FunCat Taxonomy," 2020 IEEE 1st International Conference for Convergence in Engineering (ICCE), Kolkata, India, 2020, pp. 170-174, doi: 10.1109/ICCE50343.2020.9290574.


List Books / Book Chapters:
1.Sekhar Bandyopadhyay S., Kumar Halder A., Chatterjee P., Sroka J., Nasipuri M., Basu S. (2021) Analysis of Large-Scale Human Protein Sequences Using an Efficient Spark-Based DBSCAN Algorithm. In: Bhattacharjee D., Kole D.K., Dey N., Basu S., Plewczynski D. (eds) Proceedings of International Conference on Frontiers in Computing and Systems. Advances in Intelligent Systems and Computing, vol 1255. Springer, Singapore. https://doi.org/10.1007/978-981-15-7834-2_56 2. K. Sengupta, S. Saha, P. Chatterjee, M. Kundu, S. Basu, M. Nasipuri, Ranked Gene Ontology based Protein Function Prediction by Analysis of Protein-Protein Interactions, Information and Decision Sciences. Advances in Intelligent Systems and Computing, vol. 701, Springer, Singapore, DOI: :10.1007/978-981-10-7563-6_43, ISBN: 978-981-10-7562-9.

3. Prasad,A., Saha,S., Chatterjee, P., Basu, S., and Nasipuri, M., “Protein Function Prediction from Protein Interaction Network using Bottom-Up L2L Apriori Algorithm”, in First International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2017, vol. 776, 3-16, Pub: Springer Singapore, 2017, https://doi.org/10.1007/978-981-10-6430-2_1, ISBN : 978-981-10-6429-6.

4. Mitra,R., Chatterjee, P., Basu, S. Kundu, M., Nasipuri,M., “PLoc-Euk: An ensemble classifier for prediction of Eukaryotic Protein Subcellular Localization”, Advances in Intelligent Systems and Computing book series (AISC, volume 516), 119-127, DOI: https://doi.org/10.1007/978-981-10-3156-4_12, Print ISBN : 978-981-10-3155-7.

5. Saha, S., Chatterjee, P. “Protein Function Prediction from Protein Interaction Network: A Two Pass Neighborhood Approach”, ISBN-10: 3659402788, ISBN-13: 9783659402784, Lambert Academic Publishing, May 2013
Last Updated on 2022-06-04 08:04:45