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Journals (published/accepted)
  • D. Sinha, D. Sengupta and S. Bandyopadhyay, "ParSel: Parallel Selection of Micro-RNAs for Survival Classi cation in Cancers", Molecular Informatics, DOI:10.1002/minf.201600141, 2017 (accepted)
  • S. Bandyopadhyay and K Mallick, "A new feature vector based on Gene Ontology terms for protein-protein interaction prediction",IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi 10.1109/TCBB.2016.2555304, 2017 (accepted).
  • M. Bhattacharyya, S. Maity and S. Bandyopadhyay, "Exploring the Missing Links Between Dietary Habits and Diseases", IEEE Transactions on NanoBioscience (accepted).
  • S. Malllik and S. Bandyopadhyay, "Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis", IEEE Transactions on Computational Biology and Bioinformatics (accepted).
  • D. Sengupta, S. Bandyopadhyay and D. Sinha, "A Scoring Scheme for Online Feature Selection: Simulating Model Performance Without Retraining", IEEE Transactions on Neural Networks and Learning Systems, vol. 28. no. 2. pp. 405-414, Feb 2017.
  • S. Joardar, A. Chatterjee, S. Bandyopadhyay and U. Maulik, \Multi-size Patch based Collaborative Representation for Palm Dorsa Vein Pattern Recognition by Enhanced Ensemble Learning with Modi ed Interactive Arti cial Bee Colony Algorithm",Engineering Applica- tions of Arti cial Intelligence, Elsevier, vol. 60, pp. 151-163, 2017.
  • S. Ray and S. Bandyopadhyay, \Discovering Condition Speci c Topological Pattern Changes in Coexpression Network: An Application to HIV1 Progression", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.13, no. 6, pp. 1086-1099, 2016.
  • M. Bhattacharyya, J. Nath and S. Bandyopadhyay, \Identifying Signi cant microRNAmRNA Pairs Associated with Breast Cancer Subtypes" Molecular Biology Reports, vol. 43, no. 7, pp. 591-599, DOI: 10.1007/s11033-016-4021-z, 2016.
  • S. Ray, and S. Bandyopadhyay, \NMF Based Approach for Integrating Multiple Data Sources to Predict HIV-1-human PPIs BMC Bioinformatics, 17: 121, doi: 10.1186/s12859-016- 0952-6, 2016.
  • A. Mukhopadhyay, U. Maulik and S. Bandyopadhyay, \A Survey of Evolutionary Multiobjective Clustering"ACM Computing Surveys, vol. 47, Iss. 4, Article No. 61, 2015.
  • S. Acharya, S. Saha and S. Bandyopadhyay, "Use of Line Based Symmetry for Developing Cluster Validity Indices", Soft Computing, Volume 20, Number 9, Pages 34613474 (2016), doi:10.1007/s00500-015-1848-5.
  • D. Sengupta, I. Aich, and S. Bandyopadhyay. " Feature Selection Using Feature Dissimilarity Measure and DensityBbased Clustering: Application to Biological Data", Journal of Biosciences, vol. 40, no. 4 , pp. 721-730, 2015.
  • S. Saha, R. Spandana, A. Ekbal, and S. Bandyopadhyay, " Simultaneous Feature Selection and Symmetry Based Clustering Using Multiobjective Framework", Applied Soft Computing, vol. 29, pp. 479-486, 2015.
  • S. Bandyopadhyay, D. Ghosh, R. Mitra and Z. Zhao, " MBSTAR: Multiple Instance Learning for Predicting Speci c Functional Binding sites in microRNA targets", Scienti c Reports (Nature Publishing Group), 5, Article number: 8004, doi:10.1038/srep08004, 2015.
  • M. Aqil, S. Mallik, S. Bandyopadhyay, U. Maulik and S. Jameel, " Transcriptomic Analysis of mRNAs in Human Monocytic Cells Expressing the HIV-1 Nef Protein and Their Exosomes", BioMed Research International, vol. 2015, article id: 492395, pp. 1-10, 2015.
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