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ORCIDRajat K. De
Rajat Kumar De
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2020 – today
- 2025
[j48]Abhisek Bakshi
, Souvik Sengupta, Rajat K. De, Abhijit Dasgupta:
Efficient parameter estimation in biochemical pathways: Overcoming data limitations with constrained regularization and fuzzy inference. Expert Syst. Appl. 259: 125339 (2025)- 2024
- [j47]Chayan Maitra, Dibyendu Bikash Seal, Rajat K. De:
NeuroDAVIS: A neural network model for data visualization. Neurocomputing 573: 127182 (2024) - [j46]Rituparna Sinha, Rajat Kumar Pal, Rajat Kumar De:
A novel method addressing NGS-based mappability bias for sensitive detection of DNA alterations. J. Bioinform. Comput. Biol. 22(3): 2450009:1-2450009:18 (2024) - [j45]Prasun Dutta, Rajat K. De:
DN3MF: deep neural network for non-negative matrix factorization towards low rank approximation. Pattern Anal. Appl. 27(4): 112 (2024) - [j44]Rituparna Sinha, Rajat Kumar Pal, Rajat K. De:
ENLIGHTENMENT: A Scalable Annotated Database of Genomics and NGS-Based Nucleotide Level Profiles. IEEE ACM Trans. Comput. Biol. Bioinform. 21(1): 155-168 (2024) - [i3]Prasun Dutta, Rajat K. De:
Input Guided Multiple Deconstruction Single Reconstruction neural network models for Matrix Factorization. CoRR abs/2405.13449 (2024) - [i2]Tao Zhang, Rajagopal Venkatesaramani, Rajat K. De, Bradley A. Malin, Yevgeniy Vorobeychik:
A Game-Theoretic Approach to Privacy-Utility Tradeoff in Sharing Genomic Summary Statistics. CoRR abs/2406.01811 (2024) - 2023
- [j43]Dibyendu Bikash Seal, Vivek Das, Rajat K. De:
CASSL: A cell-type annotation method for single cell transcriptomics data using semi-supervised learning. Appl. Intell. 53(2): 1287-1305 (2023) - [j42]Susobhan Baidya, Sankhayan Choudhury, Rajat Kumar De:
A Novel CRISPR-MultiTargeter Multi-agent Reinforcement learning (CMT-MARL) algorithm to identify editable target regions using a Hybrid scoring from multiple similar sequences. Appl. Intell. 53(8): 9562-9579 (2023) - [c19]Chayan Maitra, Dibyendu Bikash Seal, Vivek Das, Yevgeniy Vorobeychik, Rajat K. De:
UMINT-FS: UMINT-guided Feature Selection for multi-omics datasets. BIBM 2023: 594-601 - [e2]Pradipta Maji, Tingwen Huang, Nikhil R. Pal, Santanu Chaudhury, Rajat K. De:
Pattern Recognition and Machine Intelligence - 10th International Conference, PReMI 2023, Kolkata, India, December 12-15, 2023, Proceedings. Lecture Notes in Computer Science 14301, Springer 2023, ISBN 978-3-031-45169-0 [contents] - [i1]Chayan Maitra, Dibyendu Bikash Seal, Rajat K. De:
NeuroDAVIS: A neural network model for data visualization. CoRR abs/2304.01222 (2023) - 2022
- [j41]Rituparna Sinha, Rajat Kumar Pal, Rajat K. De:
GenSeg and MR-GenSeg: A Novel Segmentation Algorithm and its Parallel MapReduce Based Approach for Identifying Genomic Regions With Copy Number Variations. IEEE ACM Trans. Comput. Biol. Bioinform. 19(1): 443-454 (2022) - [j40]Debraj Ghosh, Rajat K. De:
Block Search Stochastic Simulation Algorithm (BlSSSA): A Fast Stochastic Simulation Algorithm for Modeling Large Biochemical Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 2111-2123 (2022) - [j39]Abhijit Dasgupta, Abhisek Bakshi, Srijani Mukherjee, Kuntal Das, Soumyajeet Talukdar, Pratyayee Chatterjee, Sagnik Mondal, Puspita Das, Subhrojit Ghosh, Archisman Som, Pritha Roy, Rima Kundu, Akash Sarkar, Arnab Biswas, Karnelia Paul, Sujit Basak, Krishnendu Manna, Chinmay Saha, Satinath Mukhopadhyay, Nitai P. Bhattacharyya, Rajat K. De:
Epidemiological challenges in pandemic coronavirus disease (COVID-19): Role of artificial intelligence. WIREs Data Mining Knowl. Discov. 12(4) (2022) - [c18]Dibyendu Bikash Seal, Vivek Das, Rajat K. De:
scARMF: Association Rule Mining-based feature selection Framework for Single-Cell transcriptomics data. BIBM 2022: 3144-3151 - 2020
- [j38]Abhijit Dasgupta, Nirmalya Chowdhury, Rajat K. De:
Metabolic pathway engineering: Perspectives and applications. Comput. Methods Programs Biomed. 192: 105436 (2020) - [j37]Abhijit Dasgupta, Losiana Nayak, Ritankar Das, Debasis Basu, Preetam Chandra, Rajat K. De:
Pattern and Rule Mining for Identifying Signatures of Epileptic Patients from Clinical EEG Data. Fundam. Informaticae 176(2): 141-166 (2020) - [j36]Rishika Sen, Somnath Tagore, Rajat K. De:
ASAPP: Architectural Similarity-Based Automated Pathway Prediction System and Its Application in Host-Pathogen Interactions. IEEE ACM Trans. Comput. Biol. Bioinform. 17(2): 506-515 (2020)
2010 – 2019
- 2019
- [j35]Rishika Sen, Somnath Tagore, Rajat K. De:
Cluster Quality based Non-Reductional (CQNR) oversampling technique and effector protein predictor based on 3D structure (EPP3D) of proteins. Comput. Biol. Medicine 112 (2019) - [j34]Rishika Sen, Losiana Nayak, Rajat K. De:
PyPredT6: A python-based prediction tool for identification of Type VI effector proteins. J. Bioinform. Comput. Biol. 17(3): 1950019:1-1950019:18 (2019) - [j33]Sandip Samaddar, Rituparna Sinha, Rajat K. De:
A Model for Distributed Processing and Analyses of NGS Data under Map-Reduce Paradigm. IEEE ACM Trans. Comput. Biol. Bioinform. 16(3): 827-840 (2019) - [c17]Abhijit Dasgupta, Ritankar Das, Losiana Nayak, Ashis Datta, Rajat K. De:
Two-Class in Silico Categorization of Intermediate Epileptic EEG Data. PReMI (2) 2019: 184-192 - 2018
- [j32]Indrani Ray, Abhijit Dasgupta, Rajat K. De:
Succinate aggravates NAFLD progression to liver cancer on the onset of obesity: An in silico model. J. Bioinform. Comput. Biol. 16(4): 1850008:1-1850008:15 (2018) - 2017
- [j31]Indrani Ray, Anindya Bhattacharya, Rajat K. De:
OCDD: an obesity and co-morbid disease database. BioData Min. 10(1): 33:1-33:11 (2017) - [j30]Debraj Ghosh, Rajat K. De:
Slow update stochastic simulation algorithms for modeling complex biochemical networks. Biosyst. 162: 135-146 (2017) - [c16]Abhijit Dasgupta, Losiana Nayak, Ritankar Das, Debasis Basu, Preetam Chandra, Rajat K. De:
Feature Selection and Fuzzy Rule Mining for Epileptic Patients from Clinical EEG Data. PReMI 2017: 87-95 - 2016
- [j29]Anupam Ghosh, Rajat K. De:
Fuzzy Correlated Association Mining: Selecting altered associations among the genes, and some possible marker genes mediating certain cancers. Appl. Soft Comput. 38: 587-605 (2016) - [j28]Losiana Nayak, Nitai P. Bhattacharyya, Rajat K. De:
Wnt signal transduction pathways: modules, development and evolution. BMC Syst. Biol. 10(S-2): 44 (2016) - 2015
- [j27]Susobhan Baidya, Rajat Kumar De:
A novel locally guided genome reassembling technique using an artificial ant system. Appl. Intell. 43(2): 397-411 (2015) - [j26]Somnath Tagore, Rajat K. De:
Evolutionary growth of certain metabolic pathways involved in the functioning of GAD and INS genes in Type 1 Diabetes Mellitus: Their architecture and stability. Comput. Biol. Medicine 61: 19-35 (2015) - [j25]Anindya Bhattacharya, Nirmalya Chowdhury, Rajat K. De:
Concepts of relative sample outlier (RSO) and weighted sample similarity (WSS) for improving performance of clustering genes: co-function and co-regulation. Int. J. Data Min. Bioinform. 11(3): 314-330 (2015) - [c15]Losiana Nayak, Nitai P. Bhattacharyya, Rajat K. De:
A module tree of Wnt signal transduction pathways. BIBM 2015: 43-48 - [c14]Abhijit Dasgupta, Ritankar Das, Losiana Nayak, Rajat K. De:
Analyzing epileptogenic brain connectivity networks using clinical EEG data. BIBM 2015: 815-821 - 2014
- [j24]Anupam Ghosh, Bibhas Chandra Dhara, Rajat K. De:
Selection of genes mediating certain cancers, using a neuro-fuzzy approach. Neurocomputing 133: 122-140 (2014) - [j23]Anupam Ghosh, Rajat K. De:
Development of a fuzzy entropy based method for detecting altered gene-gene interactions in carcinogenic state. J. Intell. Fuzzy Syst. 26(6): 2731-2746 (2014) - 2013
- [j22]Mouli Das, C. A. Murthy, Rajat K. De:
An Optimization Rule for In Silico Identification of Targeted Overproduction in Metabolic Pathways. IEEE ACM Trans. Comput. Biol. Bioinform. 10(4): 914-926 (2013) - [c13]Anupam Ghosh, Rajat K. De:
Gaussian Fuzzy Index (GFI) for Cluster Validation: Identification of High Quality Biologically Enriched Clusters of Genes and Selection of Some Possible Genes Mediating Lung Cancer. PReMI 2013: 680-687 - 2012
- [j21]Rajat K. De, Namrata Tomar:
Modeling the Optimal Central carbon metabolic pathways under Feedback Inhibition using flux Balance Analysis. J. Bioinform. Comput. Biol. 10(6) (2012) - [c12]Mouli Das, C. A. Murthy, Subhasis Mukhopadhyay, Rajat K. De:
A Second-Order Learning Algorithm for Computing Optimal Regulatory Pathways. PerMIn 2012: 227-234 - 2011
- [j20]Anindya Bhattacharya, Rajat K. De:
A novel noise handling method to improve clustering of gene expression patterns. BMC Bioinform. 12(S-7): A3 (2011) - [j19]Somnath Tagore, Rajat K. De:
Detecting breakdown points in metabolic networks. Comput. Biol. Chem. 35(6): 371-380 (2011) - [c11]Anupam Ghosh, Rajat K. De:
A fuzzy entropy based approach for development of gene prediction networks (GPNs): detecting altered dependency in carcinogenic state. BCB 2011: 320-324 - [c10]Rajat K. De, Anupam Ghosh:
Neuro-fuzzy Methodology for Selecting Genes Mediating Lung Cancer. PReMI 2011: 388-393 - [c9]Anindya Bhattacharya, Rajat K. De:
A Methodology for Handling a New Kind of Outliers Present in Gene Expression Patterns. PReMI 2011: 394-399 - [c8]Losiana Nayak, Rajat K. De:
Developmental Trend Derived from Modules of Wnt Signaling Pathways. PReMI 2011: 400-405 - 2010
- [j18]Anindya Bhattacharya, Rajat K. De:
Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values. J. Biomed. Informatics 43(4): 560-568 (2010)
2000 – 2009
- 2009
- [j17]Anindya Bhattacharya, Rajat K. De:
Bi-correlation clustering algorithm for determining a set of co-regulated genes. Bioinform. 25(21): 2795-2801 (2009) - [j16]Rajat K. De, Anupam Ghosh:
Linguistic recognition system for identification of some possible genes mediating the development of lung adenocarcinoma. Inf. Fusion 10(3): 260-269 (2009) - [j15]Rajat K. De, Anupam Ghosh:
Interval based fuzzy systems for identification of important genes from microarray gene expression data: Application to carcinogenic development. J. Biomed. Informatics 42(6): 1022-1028 (2009) - [c7]Mouli Das, Subhasis Mukhopadhyay, Rajat K. De:
A Constraint Based Method for Optimization in Metabolic Pathways. PReMI 2009: 193-198 - 2008
- [j14]Anindya Bhattacharya, Rajat K. De:
Divisive Correlation Clustering Algorithm (DCCA) for grouping of genes: detecting varying patterns in expression profiles. Bioinform. 24(11): 1359-1366 (2008) - [j13]Rajat K. De, Mouli Das, Subhasis Mukhopadhyay:
Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways. BMC Syst. Biol. 2: 65 (2008) - [c6]C. A. Murthy, Mouli Das, Rajat K. De, Subhasis Mukhopadhyay:
Determination of optimal metabolic pathways through a new learning algorithm. ICPR 2008: 1-4 - 2007
- [j12]Losiana Nayak, Rajat K. De:
An algorithm for modularization of MAPK and calcium signaling pathways: Comparative analysis among different species. J. Biomed. Informatics 40(6): 726-749 (2007) - [c5]Mouli Das, Rajat K. De, Subhasis Mukhopadhyay:
Identification of Gene Regulatory Pathways: A Regularization Method. PReMI 2007: 425-432 - [e1]Ashish Ghosh, Rajat K. De, Sankar K. Pal:
Pattern Recognition and Machine Intelligence, Second International Conference, PReMI 2007, Kolkata, India, December 18-22, 2007, Proceedings. Lecture Notes in Computer Science 4815, Springer 2007, ISBN 978-3-540-77045-9 [contents] - 2006
- [c4]Rajat K. De, Anindya Bhattacharya:
Identification of Over and Under Expressed Genes Mediating Allergic Asthma. IEA/AIE 2006: 943-952 - [c3]Rajat K. De, Kasturi Biswas:
Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks. IJCNN 2006: 3813-3819 - 2005
- [c2]Malay Kumar Pakhira, Rajat K. De:
A hardware pipeline for function optimization using genetic algorithms. GECCO 2005: 949-956 - 2003
- [j11]Mausumi Acharyya, Rajat K. De, Malay Kumar Kundu:
Extraction of Features Using M-Band Wavelet Packet Frame and Their Neuro-Fuzzy Evaluation for Multitexture Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 25(12): 1639-1644 (2003) - [j10]Mausumi Acharyya, Rajat K. De, Malay Kumar Kundu:
Segmentation of remotely sensed images using wavelet features and their evaluation in soft computing framework. IEEE Trans. Geosci. Remote. Sens. 41(12): 2900-2905 (2003) - 2002
- [j9]Rajat K. De, Jayanta Basak, Sankar K. Pal:
Unsupervised feature extraction using neuro-fuzzy approach. Fuzzy Sets Syst. 126(3): 277-291 (2002) - 2001
- [j8]Rajat K. De, Sankar K. Pal:
A connectionist model for selection of cases. Inf. Sci. 132(1-4): 179-194 (2001) - [p1]Rajat K. De, Sankar K. Pal:
Case Based Systems: A Neuro-Fuzzy Method for Selecting Cases. Soft Computing in Case Based Reasoning 2001: 241-257 - 2000
- [j7]Sankar K. Pal, Rajat K. De, Jayanta Basak:
Unsupervised feature evaluation: a neuro-fuzzy approach. IEEE Trans. Neural Networks Learn. Syst. 11(2): 366-376 (2000)
1990 – 1999
- 1999
- [j6]Rajat K. De, Jayanta Basak, Sankar K. Pal:
Neuro-fuzzy feature evaluation with theoretical analysis. Neural Networks 12(10): 1429-1455 (1999) - 1998
- [j5]Sankar K. Pal, Jayanta Basak, Rajat K. De:
Fuzzy Feature Evaluation Index and Connectionist Realization. Inf. Sci. 105(1-4): 173-188 (1998) - [j4]Jayanta Basak, Rajat K. De, Sankar K. Pal:
Fuzzy Feature Evaluation Index and Connectionist Realization - II. Theoretical Analysis. Inf. Sci. 111(1-4): 1-17 (1998) - [j3]Jayanta Basak, Rajat K. De, Sankar K. Pal:
Unsupervised feature selection using a neuro-fuzzy approach. Pattern Recognit. Lett. 19(11): 997-1006 (1998) - 1997
- [j2]Rajat K. De, Nikhil R. Pal, Sankar K. Pal:
Feature analysis: Neural network and fuzzy set theoretic approaches. Pattern Recognit. 30(10): 1579-1590 (1997) - [j1]Sushmita Mitra, Rajat K. De, Sankar K. Pal:
Knowledge-based fuzzy MLP for classification and rule generation. IEEE Trans. Neural Networks 8(6): 1338-1350 (1997) - 1996
- [c1]Sankar K. Pal, Jayanta Basak, Rajat K. De:
Feature selection: a neuro-fuzzy approach. ICNN 1996: 1197-1202
Coauthor Index
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