• SSBTR is 80G Certified Society
  • SSTR members published a policy paper on Translational Research
  • SSBTR received 12A Certificate
  • SSBTR Members published a Policy Paper on Systems Medicine Education for Developing Countries
  • Congratulation SSBTR Members for publishing a Policy Paper on Systems Medicine
  • Congratulation Mr. Dhar & Dr. Majumder for publishing research report on leukemia treatment
  • Here, in this section we will be intermittently displaying the achievements of our hon'ble members so stay tuned and keep watching this space.

Society for Systems Biology & Translational Research

( Regn. No. S/2L/No. 10387 of 2013-14 of West Bengal Act XXVI of 1961 )
( 12A Certificate Memo No. CIT(E)/10E/745/2017-18/18-19/S-0042/0344-46 )
( 80G Order No. ITBA/EXM/S/80G/2018-19/1014606278(1) dated 27/12/2018 )
Founder Member
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rajat kumar de
9433008009 | rajat@isical.ac.in
Flat 6, 3rd Floor, Block A, Sreya Residency, GF 19/2 Nabapally, Jardabagan, Baguiati, Kolkata 700059
Monday, 11th October, 1965
Same as Present Address
Indian
Male
M.Tech. (Computer Science), Ph.D.
Professor
Machine Intelligence Unit, Indian Statistical Institute, Kolkata

Application of Machine Intelligence in Systems Biology

Developed several machine intelligence based algorithms



  • Whitaker Biomedical Engineering Institute, the Johns Hopkins University, USA, (June 2002 - June 2003)
  • Research Associate, Machine Intelligence Unit, Indian Statistical Institute, Kolkata, (November 1998 - June 1999)
  • Machine Intelligence Unit, Indian Statistical Institute, Kolkata, (October 1993 - October 1998).


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Bioinformatics/Systems Biology:
1) R. K. De and A. Ghosh, Generation of linguistic rules on the genes mediating the development of lung adenocarcinoma, Research in Computing Science (Special Issue on Advances in Computer Science and Engineering), vol. 23, pp. 87-98, 2006.
2) L. Nayak and R. K. De, An algorithm for modularization of MAPK and Calcium signaling pathways: Comparative analysis among different species, Journal of Biomedical Informatics, vol. 40, pp. 726-749, 2007.
3) L. Nayak and R. K. De, Modularized study of human calcium signaling pathway, Journal of Biosciences, vol. 32, no. 5, pp. 1009-1017, 2007.
4) R. K. De and A. Bhattacharya, Clustering on gene expression and fold values: Identification of some possible genes mediating allergic asthma, International Journal of Computational Cognition, vol. 5, no. 1, pp. 35-43, 2007.
5) R. K. De, M. Das, and S. Mukhopadhyay, Learning weights representing enzyme concentration: Identification of metabolic pathways, Far East Journal of Experimental and Theoretical Artificial Intelligence, vol. 1, pp. 23-43, 2008.
6) A. Bhattacharya and R. K. De, Divisive correlation clustering algorithm (DCCA) for grouping of genes: Detecting varying patterns in expression profiles, Bioinformatics, vol. 24, 1359 - 1366, 2008.
7) R. K. De, M. Das, and S. Mukhopadhyay, Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways, BMC Systems Biology, 2:65, 2008.
8) S. Tagore, V. S. Gomase, and R. K. De, Pathway modeling: New face of graphical probabilistic analysis, Journal of Proteomics and Bioinformatics, vol. 1, no. 5, pp. 281-286, 2008.
9) R. K. De and A. Ghosh, Linguistic recognition system for identification of some possible genes mediating the development of lung adenocarcinoma, Information Fusion (Special Issue on Natural Computing in Bioinformatics), vol. 10, no. 3, pp. 260-269, 2009.
10) A. Bhattacharya and R. K. De, Bi-correlation clustering algorithm for determining a set of co-regulated genes, Bioinformatics, vol. 25, no. 21, pp. 2795-2801, 2009.
11) R. K. De and A. Ghosh, Interval based fuzzy systems for identification of important genes from microarray gene expression data: Application to carcinogenic development, Journal of Biomedical Informatics, vol. 42, pp. 1022-1028, 2009.
12) S. Sinha, T. S. Vasulu, and R. K. De, Performance and evaluation of microRNA gene identification tools, Journal of Proteomics and Bioinformatics, vol.2, no. 8, pp. 336-343, 2009.
13) A. Bhattacharya and R. K. De, Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression value, Journal of Biomedical Informatics, vol. 43, no. 4, pp. 560-568, 2010.
14) N. Tomar, L. Nayak, and R. K. De, Comparative analysis of various algorithms in modularizing VEGF signaling pathway: Exploring gradual development over various species, Journal of Biomedical Science and Engineering, vol. 3, no. 10, pp. 931-942, 2010.
15) N. Tomar and R. K. De, Immunoinformatics: An integrated scenario, Immunology, vol. 131, pp. 153-168, 2010.
16) M. Das, S. Mukhopadhyay, and R. K. De, Gradient descent optimization in gene regulatory pathways, PLoS ONE, vol. 5, no. 9, e12475, 2010.
17) A. Bhattacharya and R. K. De, A novel noise handling method to improve clustering of gene expression patterns, BMC Bioinformatics, vol. 12, Suppl 7:A3.
18) S. Tagore and R. K. De, Detecting breakdown points in metabolic networks, Computational Biology and Chemistry, vol. 35, pp. 371-380, 2011.
19) A. Bhattacharya, N. Chowdhury, and R. K. De, Comparative analysis of clustering and biclustering algorithms for grouping of genes: co-function and co-regulation, Current Bioinformatics, vol. 7, pp. 63-76, 2012.
20) R. K. De and S. Tagore, Automated reconstruction of metabolic pathways of Homo sapiens involved in the functioning of GAD1 and GAD2 genes based on structural grammars, Metabolomics: Open Access, S1:005. doi:10.4172/2153-0769.S1-005
21) S. Tagore and R. K. De, SAGPAR: StructurAl Grammar-based automated PAthway Reconstruction, Interdisciplinary Sciences: Computational Life Sciences, vol. 4, no. 2, pp. 116-127, 2012.
22) N. Tomar and R. K. De, Modeling host-pathogen interactions: H. sapiens as a host and C. difficile as a pathogen, Journal of Molecular Recognition, vol. 25, pp. 474-485, 2012.
23) R. K. De and N. Tomar, Modeling the Optimal CCM pathways under Feedback Inhibition using FBA, Journal of Bioinformatics and Computational Biology, vol. 10, no. 6 (2012) 1250019, DOI: 10.1142/S0219720012500199
24) N. Tomar, O. Choudhury, A. Chakrabarty, and R. K. De, An Integrated pathway systems modeling of Saccharomyces cerevisiae HOG pathway: A Petri net based approach, Molecular Biology Reports, vol. 39, no. 11, 2012, DOI: 10.1007/s11033-012-2153-3.
25) M. Das, S. Mukhopadhyay, and R. K. De, Development of an engineering method to optimize polyamine metabolic pathways, Current Bioinformatics. to appear (Current Impact Factor: 0.898).
26) A. Ghosh, B. C. Dhara, and R. K. De, Comparative analysis of cluster validity indices in identifying some possible genes mediating certain cancers, Molecular Informatics, (to appear). (Current Impact Factor: 2.39).
27) N. Tomar and R. K. De, Comparing methods for metabolic network analysis and an application to metabolic engineering, Gene, (to appear). (Current Impact Factor: 2.341).
28) A. Bhattacharya, N. Chowdhury, and R. K. De, Concepts of Relative Sample Outlier (RSO) and Weighted Sample Similarity (WSS) for improving performance of clustering genes: Co-function and co-regulation, International Journal of Data Mining and Bioinformatics, (accepted).
29) L. Nayak, H. Tunga, and R. K. De, Disease comorbidity and the human Wnt signaling pathway: A network-wise Study, OMICS: A Journal of Integrative Biology, (accepted). (Current Impact Factor: 2.441)
30) M. Das, C. A. Murthy, and R. K. De, An optimization rule for in silico identification of targeted overproduction in metabolic pathways, IEEE/ACM Transactions on Computational Biology and Bioinformatics, (accepted).

Computer Science:
1) R. K. De, N. R. Pal, and S. K. Pal, Feature analysis: Neural network and fuzzy set theoretic approaches, Pattern Recognition, vol. 30, pp. 1579-1590, 1997.
2) S. Mitra, R. K. De, and S. K. Pal, Knowledge-based fuzzy MLP for classification and rule generation, IEEE Transactions. on Neural Networks, vol. 8, pp. 1338-1350, 1997.
3) S. K. Pal, J. Basak, and R. K. De, Fuzzy feature evaluation index and connectionist realization, Information Sciences, vol. 105, pp. 173-188, 1998.
4) J. Basak, R. K. De, and S. K. Pal, Fuzzy feature evaluation index and connectionist realization-II: Theoretical analysis, Information Sciences, vol. 111, pp. 1-17, 1998.
5) J. Basak, R. K. De, and S. K. Pal, Unsupervised feature selection using neuro-fuzzy approach, Pattern Recognition Letters, vol. 19, pp. 997-1006, 1998.
6) R. K. De, J. Basak, and S. K. Pal, Neuro-fuzzy feature evaluation with theoretical analysis, Neural Networks, vol. 12, pp. 1429-1455, 1999.
7) S. K. Pal, R. K. De, and J. Basak, Unsupervised feature evaluation: A neuro-fuzzy approach, IEEE Transactions on Neural Networks, vol. 11, pp. 366-376, 2000.
8) R. K. De and S. K. Pal, Pattern classification using fuzzy sets and neural nets: A case based approach, International Journal of Engineering Intelligent Systems, vol. 8, pp. 103-108, 2000.
9) R. K. De and S. K. Pal, A connectionist model for selection of cases, Information Sciences, vol. 132, pp. 179-194, 2001.
10) R. K. De, J. Basak, and S. K. Pal, Unsupervised feature extraction using neuro-fuzzy approach, Fuzzy Sets and Systems, vol. 126, pp. 277-291, 2002.
11) M. Acharyya, R. K. De, and M. K. Kundu, Extraction of features using M-band wavelet packet frame and their neuro-fuzzy evaluation for multi-texture segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 1639-1644, 2003.
12) M. Acharyya, R. K. De, and M. K. Kundu, Segmentation of remotely sensed images using wavelet features and their evaluation in soft computing framework, IEEE Transactions on Geoscience and Remote Sensing, vol. 41, pp. 2900-2905, 2003.



1) A. Ghosh, R. K. De, and S. K. Pal (Eds.), Pattern Recognition and Machine Intelligence, Proc. PReMI'07, Lecture Notes in Computer Science (LNCS), vol. 4815, Springer, Heidelberg, pages 677, 2007.
2) R. K. De, D. P. Mandal, and A. Ghsosh (Eds.), Machine Interpretation of Patterns: Image Analysis and Data Mining, World Scientific, Singapore, 2010.
3) R. K. De and N. Tomar (Eds.), Immunoinformatics: From Biology to Informatics, second edition, under the Series titled Methods in Molecular Biology, by J. Walker (Series Editor), Humana Press, (currently editing the second edition of the book on invitation, expected to be published in 2013).

EDITED BOOKS:
Bioinformatics /Systems Biology:
1) R. K. De, Reverse engineering gene regulatory networks: Artificial neural network based methodologies, in: Bioinformatics and Statistics in Fisheries Research: Vol.-III, (A. K. Roy and N. Sarangi (eds.)), Central Institute of Freshwater Aquaculture (CIFA), pp. 30-41, 2007.
2) L. Nayak, N. Tomar, and R. K. De, Computational phylogeneticity of biological pathways: A developmental study of TCA cycle over a set of organisms, in: Recent Trends in Computational Biology and Computational Statistics Applied in Biotechnology and Bioinformatics, A. K. Roy et. al. (Eds.), New India Publishing AGENCY (NIPA) , New Delhi, India, pp. 337-369.

Computer Science:
1) R. K. De and S. K. Pal, Case-based systems: A neuro-fuzzy method for selecting cases, in: Soft Computing for Case-based Reasoning, (S. K. Pal, T. S. Dillon, and D. S. Yeung, (eds.)), London:Springer Verlag, pp. 241-257, 2000.
2) R. K. De, J. Basak, and S. K. Pal, Neuro-fuzzy model for unsupervised feature extraction with real life applications, in: Neuro-fuzzy Pattern Recognition, (H. Bunke and A. Kandel (eds.)), London:World Scientific, pp. 23-50, 2000.
3) R. K. De and S. K. Pal, Neuro-fuzzy models for feature selection and classification, in: Pattern Recognition: From Classical to Modern Approaches, (S. K. Pal and A. Pal (eds.)), Singapore:World Scientific, pp. 475-506, 2001.



Bioinformatics/Systems Biology:
1) R. K. De and A. Bhattacharya, Identification of over and under expressed genes mediating allergic asthma, in Proc. IEA/AIE 2006 conference held in Annecy, France, during June 27-30, 2006. Lecture Notes in Computer Science, vol. 4031, pp. 943-952, 2006.
2) R. K. De and K. Biswas, Connectionist modeling of dynamic of gene expression and reverse engineering gene regulatory networks, Proc. 2006 International Joint Conference on Neural Networks, Vancouver, BC, Canada, July 16-21, 2006, pp. 7503-7509.
3) R. K. De and L. Nayak, MAPK signaling pathways and their recursive modularization, in Proc. 15th International Conference on Computing (CIC'06), Mexico City, Mexico, pp. 203-208, November 21-24, 2006, IEEE Press.
4) M. Das, R. K. De, and S. Mukhopadhyay, Identification of gene regulatory pathways: A regularization method, Proc. Second International Conference on Pattern Recognition and Machine Intelligence (PReMI'07), Kolkata, India, December 18-22, 2007, Lecture Notes in Computer Science (LNCS), vol. 4815, pp. 425-432.
5) C. A. Murthy, M. Das, R. K. De, and S. Mukhopadhyay, Determination of optimal metabolic pathways through a new learning algorithm, Proc. 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, USA, December 8-11, 2008, IEEE Catalog Number: CFP08182 ISBN: 978-1-4244-2175-6 ISSN: 1051-4651.
6) M. Das, R. K. De, and S. Mukhopadhyay, A constraint based method for optimization in metabolic pathways, Proc. 3rd International Conference on Pattern Recognition and Machine Intelligence (PReMI'09), December 16-20, 2009, New Delhi, India, Lecture Notes in Computer Science (LNCS), vol. 5909, pp. 193-198.
7) R. K. De and A. Ghosh, Neuro-fuzzy methodology for selecting genes mediating lung cancer, Proc. 4th International Conference on Pattern Recognition and Machine Intelligence (PReMI'11), June 26 - 30, 2011, Moscow, Lecture Notes in Computer Science (LNCS) vol. 6744, pp. 388-393.
8) A. Bhattacharya and R. K. De, A methodology for handling a new kind of outliers present in gene expression patterns, Proc. 4th International Conference on Pattern Recognition and Machine Intelligence (PReMI'11), June 26 - 30, 2011, Moscow, Lecture Notes in Computer Science (LNCS) vol. 6744, pp. 394-399.
9) L. Nayak and R. K. De, Developmental trend derived from modules of Wnt signaling pathways, Proc. 4th International Conference on Pattern Recognition and Machine Intelligence (PReMI'11), June 26 - 30, 2011, Moscow, Lecture Notes in Computer Science (LNCS) vol. 6744, pp. 400-405.
10) A. Ghosh and R. K. De, A fuzzy entropy based approach for development of Gene Prediction Networks (GPNs): Detecting altered dependency in carcinogenic state, Proc ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2011 (ACM-BCB 2011), Chicago, IL, USA, August 1-3, 2011, pp. 320-324.
11) M. Das, C. A. Murthy, S. Mukhopadhyay, and R. K. De, A second-order learning algorithm for computing optimal regulatory pathways, Proc. 1st Indo-Japan Conference on Perception and Machine Intelligence, 12 - 13 January 2012, Kolkata, India, pp. 227 - 234, 2012.
12) L. Nayak and R. K. De, Finding better partitions and conserved Modules in WNT signaling pathways, Proc. 13th International Conference on Bioinformatics and Computation Biology (BIOCOMP'12), Las Vegas, USA, July 16-19, 2012.

Computer Science:
1) R. K. De, S. Mitra, and S. K. Pal, Knowledge-based fuzzy MLP for pattern classification, in Proc. Sixth International Fuzzy Systems Association World Congress, (Sao Paulo, Brazil), vol. II, pp. 237-240, 1995.
2) R. K. De, S. Mitra, and S. K. Pal, Neuro-fuzzy knowledge-based system for rule generation, in Proc. Indian Conference on Pattern Recognition, Image Processing and Computer Vision (ICPIC'95), (Kharagpur, India), pp. 130-134, 1995.
3) S. K. Pal, J. Basak, and R. K. De, Feature selection: A neuro-fuzzy approach, in Proc. International Conference on Neural Networks (ICNN'96), (Washington, DC, U.S.A.), pp. 1197-1202, 1996.
4) J. Basak, R. K. De, and S. K. Pal, Unsupervised neuro-fuzzy feature selection, in Proc. 1998 IEEE International Joint Conference on Neural Networks IJCNN'98, (Anchorage, U.S.A.), pp. 18-23, 1998.
5) R. K. De, J. Basak, and S. K. Pal, Unsupervised neuro-fuzzy feature extraction, in Proc. 5th International Conference on Soft Computing IIZUKA'98, (Iizuka, Japan), pp. 577-580, 1998.
6) M. K. Pakhira, R. K. De, S. Bandyopadhyay, and U. Maulik, Pipelined Processing of Genetic Clustering, in Proceedings of the International Conference on Intelligence Sensing and Information Processing, (Chennai, India) pp. 25-28, 2004.
7) M. K. Pakhira and R. K. De, Function optimization using a pipelined genetic algorithm, in Proceedings International Conference on Intelligent Sensors, Sensor Networks and Information Processings, (Melbourne, Australia), IEEE Press, pp. 253-258, December 14-17, 2004.
8) M. K. Pakhira and R. K. De, A hardware pipeline for function optimization using genetic algorithms, in Proc. Genetic and Evolutionary Computation Conference (GECCO-2005), (Washington D. C., USA), June 25-29, 2005, pp. 949-956.



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  • Postdoctoral Fellowship by the Whittaker Biomedical Engineering Institute
  • Research Associateship by CSIR
  • Dr. K. S. Krishnan Senior Research Fellowship by the Department of Atomic Energy, Government of India.

 



Intramural:

  • Development of pattern recognition and machine learning tools for solving certain problems in systems biology - II: During April 2010-March 2013, sponsored by Indian Statistical Institute. (Principal Investigator)
  • Development of pattern recognition and machine learning tools for solving certain problems in systems biology: During April 2008-March 2010, sponsored by Indian Statistical Institute. (Principal Investigator)
  • Computational analysis of biochemical pathways related to gene-activity: During April 2005-March 2008, sponsored by Indian Statistical Institute. (Principal Investigator)
  • Hybridization of knowledge-based and case-based reasoning in neuro-fuzzy framework for pattern recognition problems: During April 2000-March 2005, sponsored by Indian Statistical Institute. (Co-Principal investigator)


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Member Since : 08th October, 2013  | Profile Last Updated On : 12th September, 2016 12:58 AM
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