Selected Publications

Google Scholar Link

  1. Chen, Zhuomin, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, and Dongsheng Luo. “Interpreting Graph Neural Networks with In-Distributed Proxies.” Proceedings of 41st International Conference on Machine Learning (ICML 2024), arXiv preprint arXiv:2402.02036 (2024).
  2. Tanvir, Raihanul Bari, Md Mezbahul Islam, Masrur Sobhan, Dongsheng Luo, and Ananda Mohan Mondal. “MOGAT: A Multi-Omics Integration Framework Using Graph Attention Networks for Cancer Subtype Prediction.” International Journal of Molecular Sciences 25, no. 5 (2024): 2788.
  3. Sobhan, Masrur, and Ananda Mohan Mondal. “Evaluating SHAP’s Robustness in Precision Medicine: Effect of Filtering and Normalization.” In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 3157-3164. IEEE, 2023.
  4. Tanvir, Raihanul Bari, Ricardo Ruiz, Samuel Ebert, Masrur Sobhan, Abdullah Al Mamun, and Ananda Mohan Mondal. “Quantifying Intratumor Heterogeneity by Key Genes Selected using Concrete Autoencoder.” In International Conference on Pattern Recognition and Machine Intelligence, pp. 844-852. Cham: Springer Nature Switzerland, 2023.
  5. Leizaola, Daniela, Masrur Sobhan, Kacie Kaile, Ananda Mohan Mondal, and Anuradha Godavarty. “Deep learning algorithms to classify Fitzpatrick skin types for smartphone-based NIRS imaging device.” In Next-Generation Spectroscopic Technologies XV, vol. 12516, pp. 12-17. SPIE, 2023.
  6. Tanvir, Raihanul Bari, Md Mezbahul Islam, Masrur Sobhan, Dongsheng Luo, and Ananda Mohan Mondal. “MOGAT: An Improved Multi-Omics Integration Framework Using Graph Attention Networks.” bioRxiv (2023): 2023-04.
  7. Balbin, Christian A., Janelle Nunez-Castilla, Vitalii Stebliankin, Prabin Baral, Masrur Sobhan, Trevor Cickovski, Ananda Mohan Mondal et al. “Epitopedia: identifying molecular mimicry between pathogens and known immune epitopes.” ImmunoInformatics 9 (2023): 100023.
  8. Sobhan, Masrur, Daniela Leizaola, Anuradha Godavarty, and Ananda Mohan Mondal. “Subject skin tone classification with implications in wound imaging using deep learning.” In 2022 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 1640-1645. IEEE, 2022.
  9. Tanvir, Raihanul Bari, Masrur Sobhan, and Ananda Mohan Mondal. “An autoencoder based bioinformatics framework for predicting prognosis of breast cancer patients.” In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 3160-3166. IEEE, 2022.
  10. Sobhan, Masrur, and Ananda Mohan Mondal. “Explainable machine learning to identify patient-specific biomarkers for lung cancer.” In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 3152-3159. IEEE, 2022.
  11. Nunez-Castilla, Janelle, Vitalii Stebliankin, Prabin Baral, Christian A. Balbin, Masrur Sobhan, Trevor Cickovski, Ananda Mohan Mondal et al. “Potential autoimmunity resulting from molecular mimicry between SARS-CoV-2 spike and human proteins.” Viruses 14, no. 7 (2022): 1415.
  12. Kaile, Kacie, Masrur Sobhan, Ananda Mondal, and Anuradha Godavarty. “Machine learning algorithms to classify Fitzpatrick skin types during tissue oxygenation mapping.” In Optical Tomography and Spectroscopy, pp. JM3A-4. Optica Publishing Group, 2022.
  13. Stebliankin, Vitalii, Prabin Baral, Christian Balbin, Janelle Nunez-Castilla, Masrur Sobhan, Trevor Cickovski, Ananda Mohan Mondal et al. “EMoMiS: a pipeline for epitope-based molecular mimicry search in protein structures with applications to SARS-CoV-2.” BioRxiv (2022): 2022-02.
  14. Sobhan, Masrur, Kacie Kalie, Abdullah Al Mamun, Anuradha Godavarty, and Ananda Mohan Mondal. “Skin tone benchmark dataset for diabetic foot ulcers and machine learning to discover the salient features.” In International Conference on Image Processing, Computer Vision, & Pattern Recognition. 2022.
  15. Al Mamun, Abdullah, Raihanul Bari Tanvir, Masrur Sobhan, Kalai Mathee, Giri Narasimhan, Gregory E. Holt, and Ananda Mohan Mondal. “Multi-run concrete autoencoder to identify prognostic lncRNAs for 12 cancers.” International journal of molecular sciences 22, no. 21 (2021): 11919.
  16. Balbin, Christian A., Janelle Nunez-Castilla, Vitalii Stebliankin, Prabin Baral, Masrur Sobhan, Trevor Cickovski, Ananda Mohan Mondal et al. “Epitopedia: identifying molecular mimicry between pathogens and known immune epitopes.” ImmunoInformatics 9 (2023): 100023.
  17. Nunez-Castilla, Janelle, Vitalii Stebliankin, Prabin Baral, Christian A. Balbin, Masrur Sobhan, Trevor Cickovski, Ananda Mohan Mondal et al. “Spike mimicry of thrombopoietin may induce thrombocytopenia in COVID-19.” BioRxiv (2021): 2021-08.
  18. Sobhan, Masrur, Abdullah Al Mamun, Raihanul Bari Tanvir, Mario Jacas Alfonso, Pablo Valle, and Ananda Mohan Mondal. “Deep learning to discover genomic signatures for racial disparity in lung cancer.” In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2990-2992. IEEE, 2020.
  19. Al Mamun, Abdullah, Wenrui Duan, and Ananda Mohan Mondal. “Pan-cancer feature selection and classification reveals important long non-coding RNAs.” In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2417-2424. IEEE, 2020.
  20. Tanvir, Raihanul Bari, and Ananda Mohan Mondal. “Stage-Specific Co-expression Network Analysis for Cancer Biomarker Discovery.” In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1813-1819. IEEE, 2020.
  21. Al Mamun, Abdullah, Masrur Sobhan, Raihanul Bari Tanvir, Charles J. Dimitroff, and Ananda M. Mondal. “Deep learning to discover cancer glycome genes signifying the origins of cancer.” In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2425-2431. IEEE, 2020.
  22. Maharjan, Mona, Raihanul Bari Tanvir, Kamal Chowdhury, Wenrui Duan, and Ananda Mohan Mondal. “Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies.” BMC bioinformatics 21 (2020): 1-19.
  23. Gonzalez, Israel Castillo, Mona Maharjan, Ananda Mohan Mondal, and Lidia Kos. “Dystroglycan receptor and FER maintain melanoma dormancy in the vascular niche.” Cancer Research 80, no. 16_Supplement (2020): 3956-3956.
  24. Aqila, Tasmia, Abdullah Al Mamun, and Ananda Mohan Mondal. “Pseudotime based discovery of breast cancer heterogeneity.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2049-2054. IEEE, 2019.
  25. Tanvir, Raihanul Bari, and Ananda Mohan Mondal. “Cancer biomarker discovery from gene co-expression networks using community detection methods.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2097-2104. IEEE, 2019.
  26. Tsaku, Nelson Zange, Sai Chandra Kosaraju, Tasmia Aqila, Mohammad Masum, Dae Hyun Song, Ananda M. Mondal, Hyun Min Koh, and Mingon Kang. “Texture-based deep learning for effective histopathological cancer image classification.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 973-977. IEEE, 2019.
  27. Al Mamun, Abdullah, and Ananda Mohan Mondal. “Feature Selection and Classification Reveal Key lncRNAs for Multiple Cancers.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2825-2831. IEEE, 2019.
  28. Al Mamun, Abdullah, and Ananda Mohan Mondal. “Long non-coding RNA based cancer classification using deep neural networks.” In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 541-541. 2019.
  29. Tanvir, Raihanul Bari, Mona Maharjan, and Ananda Mohan Mondal. “Community Based Cancer Biomarker Identification from Gene Co-expression Network.” In Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 545-545. 2019.
  30. Maharjan, Mona, Raihanul Bari Tanvir, Kamal Chowdhury, and Ananda Mohan Mondal. “Determination of biomarkers for diagnosis of lung Cancer using Cytoscape-based GO and pathway analysis.” In The 20th International Conference on Bioinformatics and Computational Biology. 2019.
  31. Tanvir, R. B., T. Aqila, M. Maharjan, A. A. Mamun, and A. M. Mondal. “Graph Theoretic and Pearson Correlation-Based Discovery of Network Biomarkers for Cancer. Data. 2019; 4: 81.”
  32. Tsaku, Nelson Zange, Sai Chandra Kosaraju, Tasmia Aqila, Mohammad Masum, Dae Hyun Song, Ananda M. Mondal, Hyun Min Koh, and Mingon Kang. “Texture-based deep learning for effective histopathological cancer image classification.” In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 973-977. IEEE, 2019.
  33. Mondal, Ananda Mohan, Cornelia Ada Schultz, Markea Sheppard, Jasmine Carson, Raihanul Bari Tanvir, and Tasmia Aqila. “Graph Theoretic Concepts as the Building Blocks for Disease Initiation and Progression at Protein Network Level: Identification and Challenges.” In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2713-2719. IEEE, 2018.
  34. Kenne, Gabriel J., Phani M. Gummadidala, Mayomi H. Omebeyinje, Ananda M. Mondal, Dominic K. Bett, Sandra McFadden, Sydney Bromfield et al. “Activation of aflatoxin biosynthesis alleviates total ROS in Aspergillus parasiticus.” Toxins 10, no. 2 (2018): 57.
  35. Bett, Dominic K., and Ananda Mohan Mondal. “Diffusion kernel to identify missing PPIs in protein network biomarker.” In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1614-1619. IEEE, 2015.
  36. Timalsina, Prayas, Kevin Charles, and Ananda Mohan Mondal. “STRING PPI score to characterize protein subnetwork biomarkers for human diseases and pathways.” In 2014 IEEE International Conference on Bioinformatics and Bioengineering, pp. 251-256. IEEE, 2014.
  37. Mondal, Ananda, and Jianjun Hu. “Network based prediction of protein localisation using diffusion kernel.” International journal of data mining and bioinformatics 9, no. 4 (2014): 386-400.
  38. Charles, Kevin, Andrews Afful, and Ananda Mohan Mondal. “Protein Subnetwork Biomarkers for Yeast Using Brute Force Method.” In Proceedings of the International Conference on Bioinformatics & Computational Biology (BIOCOMP), p. 1. The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), 2013.
  39. Mondal, Ananda Mohan, and Jianjun Hu. “Scored protein-protein interaction to predict subcellular localizations for yeast using diffusion kernel.” In Pattern Recognition and Machine Intelligence: 5th International Conference, PReMI 2013, Kolkata, India, December 10-14, 2013. Proceedings 5, pp. 647-655. Springer Berlin Heidelberg, 2013.
  40. Lin, Jhih-Rong, Ananda Mohan Mondal, Rong Liu, and Jianjun Hu. “Minimalist ensemble algorithms for genome-wide protein localization prediction.” BMC bioinformatics 13 (2012): 1-12.
  41. Mondal, Ananda Mohan, and Jianjun Hu. “Protein Localization by Integrating Multiple Protein Correlation Networks.” Proteins 5252 (2004): 4319.
  42. Mondal, Ananda Mohan, Jhih-rong Lin, and Jianjun Hu. “Network based subcellular localization prediction for multi-label proteins.” In 2011 IEEE international conference on bioinformatics and biomedicine workshops (BIBMW), pp. 473-480. IEEE, 2011.
  43. Ananda, M. Mondal, and Jianjun Hu. “NetLoc: Network based protein localization prediction using protein-protein interaction and co-expression networks.” In 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 142-148. IEEE, 2010.
  44. Mondal, A. M., and Shamsuddin Ilias. “Analysis of numerical instability in single-stage gas permeation.” Journal of membrane science 262, no. 1-2 (2005): 5-10.
  45. Mondal, A. M., and Shamsuddin Ilias. “Dehydrogenation of cyclohexane in a palladium-ceramic membrane reactor by equilibrium shift.” Separation science and technology 36, no. 5-6 (2001): 1101-1116.
  46. Mondal, Ananda Mohan. “Stability in single-stage gas permeation and dehydrogenation of cyclohexane in Pd-ceramic membrane reactor.” PhD diss., North Carolina Agricultural and Technical State University, 1998.